Bidirectional regulation of social memory by two distinct types of GABAergic neurons in the lateral septum

Domain: biology
Published: 2026-03-17
Editorial outcome: minor_revision

Abstract
Humans and animals memorize and recognize familiar conspecifics during social interactions, known as social memory. While the hippocampus is crucial for social memory, the dynamic regulation of social memory remains unclear. Here, using male mice, we identified two molecularly distinct subpopulations of GABAergic neurons in the mouse lateral septum (LS) expressing somatostatin (SST) and calbindin 1 (CB), respectively, with complementary distribution patterns. Activation of SST+ neurons enhances social memory acquisition, whereas activation of CB+ neurons inhibits it. Optogenetic manipulation of SST+ neurons regulates theta oscillations, correlating with their impact on social memory. SST+-dLS neurons and CB+-vLS neurons preferentially receive stronger excitatory inputs from the dorsal (vCA1d) and ventral (vCA1v) parts of vCA1, respectively. Functionally, the vCA1d→SST+-dLS→lateral hypothalamic area (LHA) circuit promotes social memory acquisition, whereas the vCA1v→CB+-vLS→anterior hypothalamic nucleus (AHN) pathway suppresses it. This study uncovers two parallel neural circuits underpinning the dynamic regulation of social memory in male mice.

Introduction
Social behaviors encompass a range of interactions between conspecifics and involve continuous integration of acute sensory inputs, internal social states, and decision-making1. Internal social states, combined with emotion and memory, provide the basis for transforming sensory inputs into behavioral decisions1. During social interactions, animals can memorize and recognize familiar conspecifics2. This social recognition memory is an important cue for determining forms of social behavior, i.e. social approach or avoidance2. Deficits in social memory are commonly observed in neurodevelopmental and neurodegenerative diseases3,4. Previous studies have identified several hippocampal subregions—including dorsal CA2 (dCA2)2,5,6, dorsal CA3 (dCA3)7,8, ventral CA1 (vCA1) neurons9-14—and their synaptic connections15-20, as being critical for social memory. However, the dynamic regulation of social memory outside the hippocampus remains to be elucidated. Anatomical and functional studies suggest that the vCA1 sends many axonal branches and forms strong functional connections with the lateral septum (LS)21,22. Early studies also suggest that interfering with vasopressin and oxytocin signaling in the LS modulates social recognition memory23-27. In addition, excitatory synaptic inputs from dCA3 and inhibitory synaptic inputs from medial prefrontal cortex (mPFC) to the the dorsal LS (dLS) have been implicated in social memory regulation7,20. However, deletion of G-protein coupled metabotropic glutamate receptor 5 (mGluR5) in the LS or silencing of dopamine receptor 3 (Drd3)+-LS neurons impaired sociability without affecting social novelty preference28,29. In contrast, deletion of the oxytocin receptor (Oxtr) did not affect sociability but significantly impaired preference for social novelty28, highlighting the functional heterogeneity of the LS in regulating distinct aspects of social behaviors. These findings suggest that the LS contains molecularly and functionally heterogeneous subcircuits that contribute to different aspects of social behaviors30. Therefore, it remains unclear how social behavior is regulated by different LS subcircuits and how their synaptic strength is shaped by social experience.

More than 90% of LS neurons are GABAergic31,32. Previous studies have indicated that LS neurons express different molecular markers, i.e., somatostatin (SST), neurotensin (NTS), calbindin 1 (Calb1 or CB), calretinin (CR), Oxtr, Drd3, adenosine A receptors (A R), and type 2 corticotropin-releasing factor receptor (Crfr2)29,31,33-39. Increasing evidence suggests that different subsets of LS neurons are engaged in distinct animal behaviors. For example, activation of Crfr2+ or Oxtr+ neurons can promote anxiety levels in mice34,40, while the NTS+-LS→hypothalamic tuberal nucleus (TU) and NTS+-LS→anterior hypothalamic nucleus (AHN) pathways can regulate hedonic feeding and social trauma37,38, respectively. In addition, CA2→LS and LS→ventromedial hypothalamus (VMH) projections are implicated in social aggressive behaviors32,41. Arginine-vasopressin (AVP) released from bed nuclei of the stria terminalis (BNST) terminals in the LS may facilitate social aggression by modulating CA2→dLS synapses42. Recent transcriptomic studies identified multiple molecular distinct neuronal clusters in the LS43,44,45,46,47,48. However, it is uncertain whether LS neuronal subsets defined by molecular markers represent functionally distinct subcircuits in regulating social behaviors30. Given the broad behavioral roles of LS, several models have been proposed to explain its circuit heterogeneity. Besnard and Leroy proposed that parallel LS subcircuits may function as independent units, each receiving inputs from and sending outputs to distinct brain regions to regulate specific behavioral states30. Since most LS neurons are GABAergic31,32, lateral inhibition may further shape interactions between these units. However, it remains unclear how LS subpopulations are defined, spatially or molecularly separated, and how different neuronal clusters dynamically regulate social behaviors.

In the present study, we identified two distinct subpopulations of GABAergic neurons in the LS, that express SST and CB, respectively. Both types of neurons respond to socially relevant sensory stimuli, suggesting a potential role in social behaviors. Interestingly, we found that SST+ neurons are necessary and sufficient for social memory acquisition, whereas activation of CB+ neurons inhibits it. Furthermore, SST+ neurons play an essential role in the regulation of the theta rhythm oscillations that emerge during social memory acquisition. In addition, social memory acquisition selectively potentiates synaptic connections to SST+-dLS neurons. Importantly, we discovered two parallel pathways with distinct effects: the vCA1d→SST+-dLS→lateral hypothalamic area (LHA) circuit promotes social memory, whereas the vCA1v→CB+-vLS→AHN circuit reduces it. Thus, our study highlights two parallel subcortical neural circuits that underpins social memory acquisition, demonstrating that social memory expression is dynamically modulated by two parallel subcircuits in the LS.

Results
Identification of neuronal subpopulations in the LS

Here, to reveal the cellular composition of the LS, we used single-nucleus RNA sequencing (snRNA-seq) and analyzed the transcriptomes of 21 023 nuclei (Supplementary Fig. 1). Based on clustering analysis, we identified non-neuronal cells as well as GABAergic (Slc32a1+) and glutamatergic (Slc17a6+) neurons (Supplementary Fig. 1 and 2), which likely originated from the nearby medial septum49. After excluding non-neuronal cell types and nearby non-LS neurons, GABAergic neurons in the LS were clustered into nine neuronal subpopulations (Fig. 1a; Supplementary Fig. 1 and 2). Seven of these clusters (#6, #7, #8, #9, #10, #13, #14) corresponded to previously reported LS neuronal populations43,44,45,46,47,48. Specifically, cluster #6 aligned with neurons expressing Pax643,44,45, or Wnt5a46; cluster #7 with Crhr2-expressing neurons43,44,45; clusters #8 and #9 with Drd2- and Rai14-expressing populations43; cluster #10 with neurons expressing Rnf20744 or MYO5B47; cluster #13 with neurons expressing Ntf343or Slc18a245; cluster #14 with populations defined by Nts43,48, Sst45, or Hs3st247. Among these clusters, SST+ and Calb1+ (CB+) neurons are of particular interest because both are widely used molecular markers of functionally distinct neuronal types in the neocortex, thalamic reticular nucleus (TRN), and elsewhere50,51. To test whether SST+ and CB+ neurons also represent two distinct neuronal subtypes in the LS, we analyzed the transcriptional profiles of both neuronal subpopulations. Indeed, SST+ and CB+ neurons in the LS showed distinct molecular profiles, with SST+ neurons specifically expressing neurotensin (Nts) and glucagon-like peptide-1 receptor (Glp1r), and CB+ neurons specifically expressing serotonin 2c receptor (Htr2c) and prolactin receptor (Prlr) (Fig. 1b, c). To validate these findings, we performed additional RNAscope in situ hybridization. Consistent with the snRNA-seq results, 65.69% ± 0.92% of Sst+ neurons co-expressed Glp1r and 52.55% ± 2.40% of Sst + neurons co-expressed Nts (Supplementary Fig. 3a, b). In contrast, 70.52% ± 1.37% of Calb1+ neurons co-expressed Htr2c, and 81.53 % ± 3.50 % of Calb1+ neurons co-expressed Prlr (Supplementary Fig. 3c, d). These data suggest that SST+ and CB+ neurons represent two molecularly distinct subpopulations.

To study the functions of LS SST+ and CB+ neurons, we used SST-Cre and CB-Cre mice to label the two subpopulations. We performed single-molecule fluorescent in situ hybridization (smFISH) against Sst in LS slices from SST-Cre/LSL-H2B-GFP (SST-H2B-GFP) mice expressing nucleus-localized green fluorescent protein (GFP) in SST+ neurons and confirmed the specificity of SST-Cre mice (Supplementary Fig. 4a, b). Immunohistochemical (IHC) staining against CB in CB-Cre/Ai14 mice expressing tdTomato in CB+ neurons also revealed high specificity (Supplementary Fig. 4c, d).

The LS can be divided into dorsal, ventral, and intermediate subregions (dLS, vLS, and iLS, respectively). To capture the finer spatial distribution patterns of SST+ and CB+ neurons in the LS, we performed IHC staining for CB and NeuN in brain sections from SST-Cre/Ai14 (SST-Ai14) mice expressing tdTomato in SST+ neurons. Notably, two largely non-overlapping subpopulations of neurons (SST+ and CB+) were identified in the LS (Fig. 1d, e). Surprisingly, the SST+ and CB+ neurons showed complementary patterns in the three subregions (Fig. 1d; Supplementary Fig. 5); i.e., high SST+ neuronal density in the dLS, but high CB+ neuronal density in the iLS/vLS (Fig. 1d; Supplementary Fig. 5). In total, 25.18% ± 1.05% of LS neurons expressed SST, 21.55% ± 1.46% of neurons expressed CB and 1.70% ± 0.15% expressed both (Fig. 1f). We next examined their distribution along the anterior–posterior LS axis. The proportion of SST+ neurons decreased gradually from anterior to posterior, while CB+ neurons showed the opposite trend (Fig. 1g-i; Supplementary Fig. 5). Because neurons expressing estrogen receptor 1 (Esr1+) neurons have been identified as a distinct functional unit in the vLS43, we asked whether they correspond to CB⁺ neurons in this region. To address this, we performed immunostaining for CB in Esr1-Cre/Ai14 (Esr1-Ai14) mice (Supplementary Fig. 6). We found that 27.53% ± 0.97% of tdTomato+ neurons co-expressed CB, and 12.01% ± 1.93% of CB+ neurons co-expressed tdTomato, indicating that Esr1+ and CB+ neurons in the vLS only partially overlap and likely represent distinct molecular subpopulations.

To test whether SST+ and CB+ neurons have different morphological or electrophysiological properties, we recorded 10 SST+ and 11 CB+ neurons using whole-cell patch-clamp recordings in LS slices prepared from SST-Ai14 and CB-Ai14 mice, respectively, and reconstructed their morphology using biocytin-avidin labeling (Supplementary Fig. 7a). Group analyses showed that CB+ neurons had smaller somata compared to SST+ neurons, but similar dendritic and axonal complexity (Supplementary Fig. 7b-d). Both neurons showed comparable excitability (Supplementary Fig. 7e-f), although CB+ neurons had larger sag amplitudes, mediated by hyperpolarization-activated cyclic nucleotide-gated (HCN) channels52 (Supplementary Fig. 7g, h). The snRNA-seq results also indicated that CB+ neurons expressed a higher level of Hcn1 (Supplementary Fig. 7i), confirming more functional HCN channels.

Together, our results indicate that SST+ and CB+ neurons represent two unique functional units with complementary distribution patterns, distinct molecular profiles and electrophysiological properties. Therefore, we decided to focus on these two neuronal populations in the following studies.

SST+ and CB+ neurons actively engage in social interactions

To determine whether SST+ and CB+ neurons respond to social behaviors, we performed immunohistochemical staining for c-fos, a marker of neuronal activation (Supplementary Fig. 8a). Notably, 10-min social interaction significantly activated LS neurons (Supplementary Fig. 8b). The social stimulus increased the densities of c-fos+/SST+ neurons in all three subregions, while primarily affecting c-fos+/CB+ neurons in the iLS/vLS (Supplementary Fig. 8c-e). These results indicate that both SST+ and CB+ neurons are recruited during social interactions, with distinct activation patterns.

To examine their firing properties, we performed in-vivo electrophysiology to monitor single-neuron spiking activity when the subject mouse investigated a confined stranger mouse for 5 min (Supplementary Fig. 9a, b). We unilaterally injected a Cre-dependent AAV expressing light-sensitive hyperpolarizing opsin archaerhodopsin (ArchT) and tdTomato (AAV-DIO-ArchT-tdTomato) into the LS of SST-Cre and CB-Cre mice, respectively (Supplementary Fig. 9a). Using optogenetic tagging (see Methods), we delivered 532-nm light to identify ArchT-positive neurons (Supplementary Fig. 9c-e). Among SST⁺ neurons, 44.4% (8/18) displayed a significant increase in firing rate compared to the baseline period, while 11.1% (2/18) displayed a significant reduction in firing rate (Supplementary Fig. 9g). On average, SST+ neurons had a significantly higher firing rate during social interaction (Supplementary Fig. 9f; 9g, right), consistent with the increased number of c-fos+/SST+ neurons (Supplementary Fig. 8). In contrast, CB⁺ neurons displayed more heterogeneous responses: 20% (4/20) increased and 20% (4/20) decreased their firing rates, resulting in no overall population change (Supplementary Fig. 9h, i).

To characterize the temporal dynamics of single-unit activity of SST+ neurons in a more controllable social context, head-fixed subject mice were allowed to run freely on a previously established running wheel53 while exposed to an anesthetized stranger or a novel object (Supplementary Fig. 9j). Most SST+ neurons (63.64%, 14/22) increased firing in response to the anesthetized stranger, whereas fewer SST+ neurons (18.18%, 4/22) responded to the novel object (Supplementary Fig. 9k). At the population level, responses to the stranger were significantly stronger than those to the object (Supplementary Fig. 9l-m).

Together, these findings show that both SST+ and CB+ neurons in the LS respond during social interactions, but SST+ neurons are more strongly activated.

Activation of SST+ neurons enhances social memory acquisition

Considering the active engagement of SST+ and CB+ neurons in social interactions (Supplementary Fig. 8 and Fig. 9), we next explored their roles in regulating social behaviors using the classical three-chamber social test (Fig. 2a). To silence SST+ neurons, we bilaterally injected a Cre-dependent AAV expressing TeNT (tetanus neurotoxin, light chain) and enhanced green fluorescent protein (EGFP) (AAV-DIO-EGFP-2A-TeNT) into the LS of SST-Cre mice (SST-TeNT group, Fig. 2b). We found that TeNT silencing of SST+ neurons did not alter the locomotion in the open field test (OFT) (Supplementary Fig. 10a, b), but it significantly reduced anxiety levels in the elevated plus maze (EPM) (Supplementary Fig. 10c, d), similar with the anxiogenic effects of activating LS Crfr2+ neurons34. Moreover, SST-TeNT mice exhibited normal sociability (Supplementary Fig. 10e), but impaired social novelty preference compared to the control mice (Fig. 2c). A social discrimination (SD) index was calculated for each mouse to enable direct comparison of mice within different groups. The SD index in the SST-TeNT mice decreased markedly, suggesting an impairment in social novelty preference (Fig. 2c). Furthermore, the SST-TeNT mice showed normal preference for the novel object compared to the familiar object upon presentation (Supplementary Fig. 10f, g), suggesting normal recognition. Social novelty preference relies on the social memory of the familiar mice, enabling discrimination between novel and familiar mice during social novelty test9. To test whether TeNT blockade of SST+ neurons abolished social memory, we next performed a classic five-trial social memory test2 (Fig. 2d). As previously reported, the control mice showed normal social memory in trials 2-4, as indicated by a decrease in the time spent interacting with the now familiar mouse, but in trial 5 the duration of interactions with a novel mouse recovered to baseline levels (Fig. 2e). In contrast, the SST-TeNT mice showed impaired habituation to the familiar mouse, as indicated by equal interaction times for trials 1-5 (Fig. 2e), thus confirming the necessity of SST+-LS neurons for social memory.

To determine whether SST+ neurons are required for social memory acquisition and/or recall, we injected AAV-DIO-ArchT-tdTomato (SST-ArchT) or AAV-DIO-tdTomato alone (Control) into the LS of SST-Cre mice. We then delivered a green laser (532 nm) during memory acquisition or recall (Fig. 2f, g). Patch-clamp recordings confirmed that green light effectively suppressed SST neuronal firing (Supplementary Fig. 11a). Inhibition of SST+ neurons via ArchT during the memory acquisition phase disrupted social memory (Fig. 2h; Supplementary Fig. 11b), whereas light delivery during the memory recall phase had no effect (Fig. 2i). Baseline sociability remained unchanged (Supplementary Fig. 11c, d). To further confirm that SST+ neurons are specifically required during social memory acquisition, we repeated this experiment with two rounds of acquisition and recall. We found that optogenetic silencing of SST+ neurons during the first acquisition disrupted the mouse’s ability to distinguish between S1 and S2. This disruption also extended to the next round, impairing discrimination between S3 and S4 (Supplementary Fig. 12). These results further support that SST+ neuron activity is essential for the acquisition—but not the recall—of social memory. Furthermore, optogenetic stimulation did not elicit significant real-time place preference (Supplementary Fig. 11e), confirming that inhibition of SST+ neurons did not produce rewarding or aversive effects.

To determine whether activation of SST+ neurons during memory acquisition is sufficient for enhancing social memory, we applied a more challenging social memory task. First, we performed social memory recall with a 0–60-min interval after memory acquisition and found that social memory gradually decreased as the interval increased (Supplementary Fig. 11g). We then used a 40-min interval, under which control mice barely discriminated between familiar and novel mice (Supplementary Fig. 11g). Afterwards, we expressed Cre-dependent depolarizing opsin channelrhodopsin (ChR2) in SST+ neurons (Fig. 2j). Patch-clamp recordings confirmed that 473-nm laser pulses reliably evoked action potentials in SST+ neurons at multiple frequencies (Fig. 2k). Optogenetic activation of SST+ neurons did not change baseline sociability (Supplementary Fig. 11f), but significantly enhanced social memory recall 40 min later (Fig. 2l). Therefore, activation of SST+ neurons is both necessary and sufficient for social memory acquisition.

SST+ neurons regulate social-related theta oscillations

To investigate how SST⁺ neurons influence social memory acquisition, we examined local field potential (LFP) dynamics in the LS during social interaction. LFPs were recorded in freely moving C57BL/6 mice during a 20‑min session with a single stranger mouse to avoid confounds from switching between different conspecifics (Fig. 3a-c). We observed a significant increase in the spectral power of theta rhythm oscillations (4–12 Hz) during all four periods (P1–P4) (Fig. 3d, e), but no change in the power of other bands (1–3, 13–30, and 31–80 Hz) (Fig. 3e). Theta power remained elevated during both social bouts and non-social intervals (Fig. 3d, e), suggesting a sustained change in network state rather than a transient sensory response. Given the importance of theta oscillations in memory encoding and retrieval54,55, these findings suggest that theta enhancement is a potential mechanism for social memory acquisition.

Theta oscillations are shaped by cell-type-specific firing patterns, with GABAergic neurons often playing a key role56,57. To determine whether SST⁺ neuron activity is coupled to theta rhythms, we performed simultaneous LFP and single-unit recordings from optogenetically tagged SST⁺ neurons during social interaction (Fig. 3a; Supplementary Fig. 9a-d). We analyzed the temporal firing patterns of SST+ neurons during theta oscillations (Fig. 3f). The Rayleigh test was applied to determine whether SST neuronal spikes were significantly locked to theta phases58,59 (Fig. 3g). Similar to LFP activity, the proportion of significantly phase-locked SST+ neurons increased markedly (Fig. 3h). Group analysis indicated that SST+ neurons preferentially fired during the descending phase of theta oscillations (Fig. 3i), suggesting they are actively engaged in shaping theta activity. In line with this, a recent study demonstrated that vCA1 neurons encode social stimuli using both firing rate and theta-phase coding60, Together, these findings suggest that theta-phase–locked firing of SST⁺ neurons may provide a temporal framework for social memory acquisition.

To test whether theta enhancement is specific to social contexts, we compared theta power across three conditions: 10‑min social interaction, 20-min exploration of empty chamber, and 10-min exploration of a novel object (Supplementary Fig. 13a). Theta power selectively increased during social interaction, emerging within the second 2 min and persisting throughout stimulus presence (Supplementary Fig. 13b). In contrast, theta power remained at baseline during non‑social conditions. However, the proportion of phase-locked SST+ neurons stayed elevated even in non‑social conditions (Supplementary Fig. 13c). Together, these results indicate that theta oscillation enhancement is context-dependent.

To elucidate whether SST+ neurons are required for social-related theta oscillations, we bilaterally injected AAV-DIO-ArchT-tdTomato and implanted an LFP-recording optrode into the LS of SST-Cre mice (Fig. 3j). ArchT-silencing of SST+ neurons blocked the increase in theta oscillation power (Fig. 3k), suggesting that activation of SST+ neurons is necessary for theta oscillations. Conversely, to test if SST+ neurons can drive theta oscillations, we bilaterally injected AAV-DIO-ChR2-EYFP and implanted an LFP-recording optrode into the LS of SST-Cre mice (Fig. 3l). Optogenetic theta-frequency stimulation of SST+ neurons enhanced theta oscillation power in the open field chamber (Fig. 3m), highlighting the role of SST+ neurons in driving theta oscillations.

We next explored the synaptic mechanism underlying this effect. Feedback inhibition from GABAergic neurons is thought to promote rhythm oscillations59,61,62. To examine local connectivity, we injected AAV-DIO-ChR2-EYFP into the LS of SST-Cre/Ai14 mice and performed patch-clamp recordings from tdTomato-negative LS neurons in acute slices (Fig. 3n, o). In the presence of tetrodotoxin (TTX) and 4-aminopyridine (4-AP), all recorded SST⁻ neurons (38/38) exhibited monosynaptic inhibitory postsynaptic currents (IPSCs) in response to laser stimulation (Fig. 3p, q). These IPSCs were abolished by the GABA receptor antagonist (PTX) but unaffected by glutamate receptor antagonists (CNQX and D-AP5), confirming GABAergic transmission (Fig. 3p, q). These results demonstrated that SST+ neurons directly inhibit other neurons in the LS. Combined with the extensive local axonal arborizations of SST⁺ neurons (Supplementary Fig. 7a, d). these results suggest that SST⁺ neurons provide recurrent inhibition, supporting theta oscillations within the LS59,62.

Activation of CB+ neurons suppresses social memory acquisition

As shown above, both SST+ and CB+ neurons actively engage in social interactions (Supplementary Fig. 8). To determine the role of CB+ neurons in social behaviors, we employed a chemogenetic approach to activate these neurons. We injected a Cre-dependent AAV expressing mCherry-tagged hM3Dq, a designer receptor exclusively activated by designer drugs (DREADD)63, into the LS of CB-Cre mice (Supplementary Fig. 14a). Patch-clamp recordings confirmed that clozapine-N-oxide (CNO), a DREADD activator, significantly depolarized the membrane potential and increased the firing rate of hM3Dq-expressing neurons (Supplementary Fig. 14b, c). After 3 weeks of recovery, we intraperitoneally (i.p.) injected CNO 30 min before behavioral tests (Supplementary Fig. 14h). Chemogenetic activation of CB+ neurons did not alter baseline locomotion, anxiety or novel object preference (Supplementary Fig. 14d-g, o-q, t). The two control groups, i.e., control and CB-hM3Dq mice receiving saline injection, exhibited normal sociability and social memory (Supplementary Fig. 14i, j, r, s). In contrast, the CNO-injected CB-hM3Dq mice exhibited significantly impaired social memory, with no change in baseline sociability (Supplementary Fig. 14i, j). In the five-trial social memory test, the CNO-injected CB-hM3Dq mice showed impaired social memory as indicated by equal interaction times for trials 1-5 (Supplementary Fig. 14k), confirming that chemogenetic activation of CB+-LS neurons blocked social memory.

To address whether CB+ neurons are crucial for social memory acquisition and/or social memory recall, we bilaterally injected AAV-DIO-ChR2-EYFP (CB-ChR2) or AAV-DIO-EYFP alone (Control) into the LS of CB-Cre mice (Fig. 4a), then delivered blue laser pulses during memory acquisition or recall (Fig. 4b, c). ChR2 activation of CB+ neurons did not change baseline sociability (Supplementary Fig. 14l, m). However, optogenetic activation of CB+ neurons during the memory acquisition phase significantly impaired social memory, whereas activation during the memory recall phase did not impact social memory at all (Fig. 4b, c).

To test whether inhibition of CB+ neurons influences social memory, we bilaterally injected AAV-DIO-ArchT-tdTomato (CB-ArchT) or AAV-DIO-tdTomato alone (Control) into the LS of CB-Cre mice (Fig. 4d). ArchT inhibition of CB+ neurons did not change baseline sociability or real-time place preference (Fig. 4e; Supplementary Fig. 14n). However, compared to the control mice, optogenetic inhibition of CB+ neurons during social memory acquisition improved social memory recall after a 40-min interval (Fig. 4f), mimicking the effect of SST⁺ neuron activation (Fig. 2l). Together, these results reveal a bidirectional relationship in which SST⁺ neurons facilitate, and CB⁺ neurons suppress, social memory acquisition.

Mutual inhibition between SST⁺ and CB⁺ neurons

Given the opposite effect on social memory, we hypothesized that CB+ neurons may inhibit SST+ neurons in the LS. To test this, we bilaterally injected AAV-DIO-ChR2-EYFP and AAV-fDIO-H2B-mCherry into the LS of CB-Cre/SST-Flp mice and recorded SST+ neurons (mCherry+) in LS slices (Fig. 4g, h). Light stimulation evoked IPSCs in all recorded SST⁺ neurons (32/32), indicating widespread CB⁺→SST⁺ connectivity (Fig. 4i, j). Perfusion of TTX/4-AP and PTX confirmed these connections were monosynaptic and GABAergic (Fig. 4i, j). To determine whether SST⁺ neurons reciprocally inhibit CB⁺ neurons, we expressed ChR2 in SST⁺ neurons and H2B-mCherry in CB⁺ neurons of CB-Cre/SST-Flp mice (Supplementary Fig. 15a, b). Light stimulation elicited IPSCs in all recorded CB⁺ neurons (26/26), which were abolished by TTX/4-AP and PTX, confirming monosynaptic SST⁺→CB⁺ inhibition (Supplementary Fig. 15c, d).

To assess whether these reciprocal interactions occur in vivo, we employed opto-tagging to isolate single units of SST⁺ and CB⁺ neurons. We injected AAV-DIO-ArchT-tdTomato unilaterally into the LS of SST-Cre and CB-Cre mice, and conducted optrode recording in these head-fixed animals (Supplementary Fig. 16a, b). Spike waveform analysis revealed that SST+ neurons have longer trough-to-peak durations, wider half-width, and larger peak-trough ratios than CB+ neurons (Supplementary Fig. 16c, d). Using these features, we identified putative CB⁺ (pCB⁺) neurons in SST-ArchT mice and putative SST⁺ (pSST⁺) neurons in CB-ArchT mice.

To mimic social interaction, head-fixed mice were presented with an anesthetized stranger (Supplementary Fig. 16b). We identified 15 pCB+ neurons and 14 pSST+ neurons from recordings in SST-ArchT and CB-ArchT mice, respectively (Supplementary Fig. 16d). Silencing SST⁺ neurons increased firing in 5 of 15 pCB⁺ neurons at baseline and in 12 of 15 pCB⁺ neurons during social stimulus presentation (Supplementary Fig. 16e-g), suggesting that SST⁺ neurons exert stronger inhibition on CB⁺ neurons during social interaction. In contrast, silencing CB⁺ neurons increased firing in a similar proportion of pSST⁺ neurons under baseline and social conditions (Supplementary Fig. 16h-j), indicating that CB+ neurons provide relatively stable inhibition of SST+ neurons. Together, these results demonstrate reciprocal inhibition between SST⁺ and CB⁺ neurons in vivo, and that this interaction may help stabilize social memory.

SST+-dLS neurons and CB+-vLS neurons preferentially receive stronger glutamatergic inputs from vCA1d and vCA1v pyramidal neurons

Having established the critical roles of SST+ and CB+ neurons in social memory acquisition, we next examined whether they have distinct synaptic connections. To obtain cell type-specific maps of synaptic inputs for both neurons, we utilized pseudotyped rabies virus (RV)-mediated trans-synaptic tracing to label monosynaptic inputs for SST+-dLS and CB+-vLS neurons (Fig. 5a; Supplementary Fig. 17a, b)64. The results showed that the majority of monosynaptic inputs to both SST+-dLS and CB+-vLS neurons were from hippocampal and hypothalamic regions (Supplementary Fig. 17a, b). Notably, vCA1 contained a particularly high density of RV-labeled neurons (Supplementary Fig. 17a, b), drawing our attention due to its established role in regulating social memory9. Interestingly, the RV-labeled vCA1 input neurons to SST+-dLS and vLS-CB+ neurons showed very different distribution patterns along the dorsal-ventral axis of vCA1, with SST+-dLS neurons receiving more inputs from the dorsal part of vCA1 (vCA1d) and CB+-vLS neurons receiving more inputs from the ventral parts of vCA1 (vCA1v) (Fig. 5b-d), consistent with the finding that the soma locations of CA1 pyramidal neurons correlate with their axon tip locations in the LS (See Figure 8D in ref65). We also reanalyzed previously published single-neuron projectomes of mouse hippocampus65 and found that dLS-projecting vCA1 neurons are preferentially localized in the vCA1d region (Supplementary Fig. 18a-c), while vLS-projecting vCA1 neurons are preferentially localized in the vCA1v region (Supplementary Fig. 18d-f). These findings confirm the correlation between vCA1 soma locations and the intensity of axonal projections in the LS.

Since CA2 is also known to regulate social memory, we next investigated whether SST+-dLS neurons receive monosynaptic inputs from CA2 neurons. To do this, we performed additional RV tracing experiments combined with immunostaining for RGS14, a molecular marker of CA2 neurons, (Supplementary Fig. 19). We found that 10.64% ± 1.39% of RGS14+ CA2 neurons were double-labeled with GFP, indicating that a subset projects to SST+-dLS neurons. However, these neurons represented only 3.12% ± 0.17% of the total GFP+ input population in the hippocampus, suggesting that CA2 provides a relatively minor input compared to vCA1. Based on these findings, we focused subsequent experiments on the vCA1→LS circuit.

To assay functional synaptic connections between vCA1 and LS neurons, we injected AAV-CaMKII-ChR2-EYFP into the vCA1 of C57 mice and performed patch-clamp recordings in LS neurons. Dense EYFP+ axonal fibers were visible in the LS (Supplementary Fig. 17c), suggesting potential synaptic connections between the vCA1 and LS. Based on voltage-clamp recordings, almost all neurons exhibited both excitatory postsynaptic currents (EPSCs) (measured with membrane potential at −70 mV) and IPSCs (measured at 0 mV) in response to laser stimulation (Supplementary Fig. 17d). TTX/4-AP reduced EPSC amplitude, but CNQX eliminated the EPSCs, confirming mediation by monosynaptic glutamatergic inputs (Supplementary Fig. 17d, e). However, TTX/4-AP completely blocked the IPSCs, suggesting mediation by disynaptic inhibition from local GABAergic neurons (Supplementary Fig. 17d, f).

To determine whether vCA1d and vCA1v neurons differentially innervate SST+ and CB+ neurons, we injected AAV-CaMKII-ChR2-EYFP into the vCA1d or vCA1v, together with AAV-fDIO-H2B-GFP and AAV-DIO-H2B-mCherry into the dLS and vLS of CB-Cre/SST-Flp mice (Fig. 5e). We then performed dual whole-cell recordings of SST+-dLS and CB+-vLS neurons labeled with GFP and mCherry, respectively (Fig. 5f), while laser stimulation was applied to activate synaptic inputs from vCA1d (Fig. 5f, g) or vCA1v (Fig. 5f, h). We found that laser stimulation of vCA1d inputs evoked stronger EPSCs in SST+-dLS neurons than in CB+-vLS neurons (Fig. 5g). Conversely, laser stimulation of vCA1v inputs evoked stronger EPSCs in CB+-vLS neurons than in SST+-dLS neurons (Fig. 5h). Both results suggest that vCA1d and vCA1v pyramidal neurons preferentially provide stronger synaptic inputs to SST+-dLS neurons and CB+-vLS neurons, respectively. This is consistent with the observed gradient distribution of RV-labled vCA1 input neurons to SST+-dLS and CB+-vLS neurons (Fig. 5b-d).

vCA1d→dLS and vCA1v→vLS pathways bidirectionally regulate social memory acquisition

To test the role of vCA1d and vCA1v, we first investigated whether the vCA1d→dLS pathways regulate social memory. We bilaterally injected AAV2-retro-Syn-Cre-tdTomato into the dLS and AAV-DIO-EGFP-2A-TeNT into the vCA1d of C57 mice (Fig. 6a). TeNT silencing of dLS-projecting vCA1d neurons significantly reduced anxiety without affecting recognition (Supplementary Fig. 20b, c). Furthermore, inactivation of vCA1d→dLS pathway with TeNT impaired social memory at a 10-min interval (Fig. 6b) and blocked the enhanced theta oscillations during social interaction (Supplementary Fig. 20d), without altering baseline sociability (Supplementary Fig. 20a). Consistently, TeNT silencing of dLS-projecting vCA1d neurons also impaired social memory of the familiar mouse in the five-trial social memory assay (Fig. 6c), confirming the necessity of dLS-projecting vCA1d neurons for social memory.

Next, we explored whether vCA1d→dLS projections are essential for increased theta oscillations and social memory. To test this, we injected AAV2-retro-Syn-Cre-EGFP and AAV-DIO-ArchT-tdTomato into the dLS and vCA1d of C57 mice respectively, followed by optical fiber implantation above the dLS (Fig. 6d). To block this pathway, we delivered laser pulses to inhibit axonal terminals of vCA1d neurons in the dLS. This optogenetic silencing of vCA1d→dLS projections during memory acquisition blocked social memory at a 10-min interval, but did not affect baseline sociability (Fig. 6e; Supplementary Fig. 20f). In contrast, inhibiting the same projection during memory recall had no effect on social memory (Fig. 6f). To further explore the role of this pathway in theta activity, we injected AAV-CaMKII-eArchT3.0-EGFP into the vCA1d of C57 mice and implanted an LFP-recording optrode in the dLS (Supplementary Fig. 20e). Laser stimulation blocked the enhanced theta oscillations typically observed during social interaction (Supplementary Fig. 20e). These results suggest that vCA1d→dLS projections are necessary for both enhanced theta oscillations and social memory acquisition, consistent with the role of SST+-dLS neurons in regulating social memory acquisition.

We then examined whether the vCA1v→vLS pathways regulate social memory. We bilaterally injected AAV2-retro-Syn-Cre-EGFP and AAV-DIO-hM3Dq-mCherry into the vLS and vCA1v of C57 mice, respectively (Fig. 6g). Chemogenetic activation of vLS-projecting vCA1v neurons reduced anxiety without changing recognition (Supplementary Fig. 20h, i). Additionally, activation of vLS-projecting vCA1v neurons impaired social memory at a 10-min interval, without altering baseline sociability (Fig. 6h; Supplementary Fig. 20g). In the five-trial social memory assay, activation of vLS-projecting vCA1v neurons impaired social memory of the familiar mouse in the first four trials (Fig. 6i).

To determine whether vCA1v→vLS projections regulate social memory, we injected AAV2-retro-Syn-Cre-tdTomato and AAV-DIO-ChR2-EGFP into the vLS and vCA1v of C57 mice respectively, followed by optical fiber implantation above the vLS (Fig. 6j). Optogenetic activation of vCA1v→vLS projections during memory acquisition blocked social memory at a 10-min interval (Fig. 6k), whereas activation of these projections during memory recall did not affect social memory (Fig. 6l). These findings suggest that vCA1v→vLS projections inhibit social memory acquisition, correlating with the finding that activation of CB+-vLS neurons suppresses social memory acquisition.

Previous studies have shown that vCA1 region projects to both LS and NAc, including neurons that project exclusively to LS, exclusively to NAc, and a small subset that project to both regions21. To quantify the proportion of dual-projecting neurons, we performed retrograde tracing by injecting CTB-555 into the NAc and CTB-488 into the vLS, and analyzed labeled neurons in the vCA1. We found that 10.95% ± 1.19% of LS-projecting vCA1 neurons (green) also projected to the NAc, and 15.82% ± 1.24% of NAc-projecting vCA1 neurons (red) also projected to the LS (Supplementary Fig. 21a-d), suggesting that dual-projecting neurons comprise only a small fraction of the vCA1 neurons. Notably, global silencing of vCA1 neurons disrupts both social memory recall and acquisition (see Figure S8 in ref9), whereas selective inhibition of vCA1→NAc projections impairs recall alone9. Together with these findings, our data support a model in which vCA1→LS and vCA1→NAc pathways contribute to different phases of social memory: the vCA1→LS projection primarily supports memory acquisition, whereas the vCA1→NAc pathway is more important for memory recall.

To examine the function of vCA1 neurons that project specifically to the NAc, we bilaterally injected AAV2-retro-Syn-Cre-EGFP and AAV-Cre-off-eNpHR3.0-mCherry into the LS and vCA1 of C57 mice, respectively (Supplementary Fig. 21e), thereby restricting expression of eNpHR3.0 to vCA1 neurons that do not project to the LS. Optogenetic silencing of these non-LS projecting vCA1 neurons during memory acquisition did not affect social memory at a 10-min interval (Supplementary Fig. 21f), but silencing of these neurons during memory recall abolished social memory (Supplementary Fig. 21g). Similarly, inhibition of non-LS-projecting vCA1→NAc terminals selectively impaired memory recall without affecting acquisition (Supplementary Fig. 21h-j).

Collectively, these findings support a model in which vCA1→LS and vCA1→NAc projections form two parallel and functionally distinct circuits that regulate social memory acquisition and recall, respectively. Furthermore, within the vCA1→LS circuit, the vCA1d→dLS and vCA1v→vLS pathways appear to exert contrasting influences on social memory acquisition.

Presynaptic plasticity at vCA1d→dLS excitatory synapses to SST+ neurons

The above findings suggest that during social memory acquisition, vCA1d excitatory inputs may specifically regulate SST+-dLS neurons, whereas vCA1v excitatory inputs may specifically regulate CB+-vLS neurons. Therefore, we asked whether social memory acquisition affects synaptic strength at vCA1-LS excitatory synapses. To address this, we recorded spontaneous EPSCs (sEPSCs) in SST+-dLS and CB+-vLS neurons. To label SST+ or CB+ neurons, AAV-CAG-DIO-H2B-mCherry was injected into the dLS of SST-Cre or vLS of CB-Cre mice. Two weeks later, we subjected the mice to social memory acquisition paradigm (Fig. 7a, also see Methods) and prepared LS slices for sEPSC recordings. Interestingly, we found a significant increase in the frequency of sEPSCs in SST+-dLS neurons following social interaction compared to control mice (Fig. 7b-d), whereas sEPSCs in CB+-vLS neurons remained unchanged (Fig. 7e-g). To exclude potential confounds from motor activity, we recorded sEPSCs from SST+-dLS neurons in mice exposed to either a rotating (Running) or stationary (Control) rotarod (Supplementary Fig. 22a). No differences were observed in sEPSC frequency or amplitude between groups (Supplementary Fig. 22b-d), indicating that locomotion alone does not account for the synaptic changes. The social interaction-induced increase in sEPSC frequency in SST+-dLS neurons suggests an enhancement in either presynaptic release probability (Pr) or synapse number. To distinguish between these two probabilities, we measured the paired-pulse ratios (PPRs) of vCA1-LS EPSCs (Fig. 7h), as PPR is inversely related to Pr66. We observed a significant reduction in the PPRs of vCA1d→dLS EPSCs in SST+ neurons (Fig. 7i), but no change in the PPR of vCA1v→vLS EPSCs in CB+ neurons (Fig. 7j), suggesting that social interaction increased the Pr specifically at vCA1d→SST+-dLS synapses. Taken together, these results suggest that vCA1d excitatory synapses to SST+-dLS neurons undergo synaptic potentiation during social memory acquisition.

SST+-dLS→LHA and CB+-vLS→AHN pathways enhance and suppress social memory acquisition

Having demonstrated that SST+ and CB+ neurons exert bidirectional control over social memory, we next asked whether these divergent effects are mediated by distinct downstream projections. To map efferent pathways, we performed anterograde tracing by injecting AAV-DIO-EGFP into the LS of SST-Cre or CB-Cre mice (Supplementary Fig. 23a, b). Both SST+ and CB+ neurons project to multiple downstream targets, including BNST, NAc, and several hypothalamic subregions such as the preoptic area (POA), AHN, LHA, supramammillary nucleus (SUM), and posterior hypothalamic nucleus (PH)—regions known to contribute to diverse social behaviors67-69. Notably, SST+-dLS neurons sent more projections to the LHA, while CB+-vLS neurons projected comparably to both the AHN and LHA (Supplementary Fig. 23c, d). Moreover, the AHN contained a higher density of Gad1⁺ GABAergic neurons compared to Slc17a6⁺ glutamatergic neurons, while the LHA displayed the opposite pattern, with a greater density of Slc17a6⁺ glutamatergic neurons (Supplementary Fig. 25).

To determine whether above circuits are required for social memory, we injected AAV-DIO-ArchT-tdTomato into the dLS of SST-Cre mice, followed by optical fiber implantation above the ArchT-expressing axonal terminals in the AHN (Fig. 8a), LHA (Fig. 8d), and POA (Supplementary Fig. 23e). ArchT silencing of the SST+-dLS→AHN or SST+-dLS→POA pathways during the memory acquisition phase did not affect social memory (Fig. 8c; Supplementary Fig. 23g). In contrast, silencing the SST+-dLS→LHA pathway during memory acquisition blocked social memory without affecting novel object preference (Fig. 8f; Supplementary Fig. 24g). ArchT silencing of all three pathways did not change baseline sociability (Fig. 8b, e; Supplementary Fig. 23f). Moreover, silencing the SST+-dLS→LHA pathway significantly reduced anxiety levels (Supplementary Fig. 24e, f). To validate the SST+-dLS→LHA pathway, we injected AAV-DIO-ChR2-EYFP into the dLS of SST-Cre mice and performed slice physiology (Supplementary Fig. 24a, b). In acute LHA slices, we detected light-evoked IPSCs in 15 out of 17 LHA neurons, which were completely abrogated by PTX (Supplementary Fig. 24c, d), confirming that SST+-dLS neurons formed functional GABAergic synapses with LHA neurons. Together, these results show that GABAergic projections from SST+-dLS neurons to LHA neurons are necessary for social memory.

Considering the opposite effect of the SST+ and CB+ neurons on social memory, we next examined whether activation of vLS-CB+ circuits can impair social memory. AAV-DIO- ChR2-EYFP was injected into the vLS of CB-Cre mice, followed by optical fiber implantation above the ChR2+ axonal terminals in the AHN (Fig. 8g), LHA (Fig. 8j), and POA (Supplementary Fig. 23h), respectively. Light stimulation of the CB+-vLS→LHA or CB+-vLS→POA pathways had no effect on social memory or baseline sociability (Fig. 8k, l; Supplementary Fig. 23i, j). In contrast, activation of the CB+-vLS→AHN pathway during memory acquisition blocked social memory without altering baseline sociability (Fig. 8h, i). Moreover, activation of the CB+-vLS→AHN pathway did not change anxiety levels or the preference for the novel object (Supplementary Fig. 24l-n). To validate the CB+-vLS→AHN pathway, we injected AAV-DIO-ChR2-EYFP into the vLS of CB-Cre mice and performed slice physiology (Supplementary Fig. 24h, i). In acute AHN slices, we observed light-evoked IPSCs in 19 out of 20 AHN neurons, which were eliminated by PTX (Supplementary Fig. 24j, k), confirming functional GABAergic connections between CB+-vLS neurons and AHN neurons. Together, these findings demonstrate that the CB+-vLS→AHN pathway suppresses social memory.

Methods
Animals. All experimental procedures were performed following protocols approved by the Animal Care and Use Committee of Huazhong University of Science and Technology, China. The SST-ires-Cre (SST-Cre), SST-ires-Flp (SST-Flp), CB-ires-Cre (CB-Cre), Rosa26-LSL-tdTomato (Ai14), Esr1-2a-Cre (Esr1-Cre) and Rosa26-LSL-H2B-GFP (LSL-H2B-GFP) mouse lines were imported from the Jackson Laboratory (SST-Cre: #013044; SST-Flp: #028579; CB-Cre: #028532; Ai14: #007914; Esr1-Cre: #0017913; LSL-H2B-GFP: #036761; JAX Mice and Services, USA). The C57BL/6 mice were purchased from the Animal Center of Huazhong University of Science and Technology. Mice (3–5 per cage) were housed under a 12-h light/dark cycle at an ambient temperature of 20–24 °C and relative humidity of 30–70%, with food and water provided ad libitum. We have only used male mice in this study because the social behaviors of laboratory mice exhibit sex- and strain-dependent behavioral parameters90,91.

Single-nucleus RNA-seq (snRNA-seq)

Tissue collection and snRNA-seq. Single nuclei were isolated as described previously92. The LS was micro-dissected from six male C57BL/6 mice (2-month-old). Coronal LS sections (300-μm thick) spanning bregma +1.10 mm to −0.10 mm (Allen Brain Atlas, atlas.brain-map.org) were prepared with a vibratome, and four consecutive slices were collected. To minimize contamination from adjacent regions (e.g., MS, NAc, striatum, and corpus callosum), LS tissue was carefully isolated under a dissection microscope using a fine angled knife (#10056-12, FST) and fine forceps. Surrounding brain regions were removed, leaving only the LS (highlighted in purple in Supplementary Fig. 1a) for analysis. Tissues were rapidly frozen in liquid nitrogen and stored at −80 °C until processing.

For single-nuclear suspension, tissues were thawed and homogenized in homogenization buffer containing 250 mM sucrose, 25 mM KCl, 5 mM MgCl , 10 mM Tris, 0.1 mM dithiothreitol (DTT), mini protease 2 inhibitor cocktail (#11836153001; Roche, Switzerland), 0.4 U/μL RNase inhibitor, 1% BSA, and 0.1% NP40. Samples were centrifuged (500 g, 5 min, 4 ℃), washed with homogenization buffer, and repetitively pipetted to generate a nuclear suspension. The nuclear suspensions were again centrifuged (500 g, 5 min, 4 ℃) and resuspended in cold 1 × phosphate-buffered saline (PBS). After nucleus counting, the DNBSEQTM technology platform (BGI Genomics, China) and DNBelab C4 Single-Cell Library Prep Set (#1000021082; MGI, China) were used for snRNA-seq library preparation93. Briefly, the single-nucleus suspensions were converted to barcoded libraries using droplet generation, emulsion breakage, bead collection, reverse transcription, cDNA amplification, and purification. Indexed sequencing libraries were constructed according to the manufacturer’s protocols. Sequencing library quality was evaluated using a QubitTM ssDNA Assay Kit (#Q10212; Thermo Fisher Scientific, USA). Libraries were sequenced using an ultra-high-throughput DIPSEQ T1 sequencer with the following strategy: 30 bp for read 1, inclusive of 10 bp cell barcode 1, 10 bp cell barcode 2, and 10 bp unique molecular identifier (UMI), 100 bp of transcript sequence for read 2, and 10 bp for sample index.

SnRNA-seq data processing. Raw sequencing reads were filtered and demultiplexed using PISA (https://github.com/shiquan/PISA)94. Reads were aligned to the GRCm38 mouse genome using STAR (v2.7.4a) and sorted by Sambamba (v0.7.0).

Cell clustering and cell type identification. Cell clustering was performed using the Seurat (v4.1.0) R toolkit (https://github.com/satijalab/seurat). Qualified cells were filtered according to number of detected genes (between 500 and 6 500) and percentage of mitochondrial genes (< 0.1%). Genes expressed in < 3 cells were removed. The filtered dataset was log-normalized and scaled, and principal component analysis (PCA) was conducted. The first 18 PCs were used for graph-based clustering in Seurat using the Louvain algorithm. Non-neuronal clusters were identified by expression of Pdgfra, Oligo1, Mki67, Slc1a3, Mal, C1qa, Foxj1, and Cldn5 (Supplementary Fig. 1). A cluster with high mitochondrial gene expression and low detected genes was removed (data not shown). The remaining neuronal cells were then reclustered and processed using the same pipeline. Clusters were designated “non-LS” only if they expressed more than ten well-established markers for neighboring regions (e.g., MS, NAc) (Supplementary Fig. 2). Corresponding in-situ hybridization (ISH) images were adapted from Allen Mouse Brain Atlas, mouse.brain-map.org, and details are provided in Supplementary Table 3. Analysis of differentially expressed genes (DEGs) in all neuronal clusters was performed using the FindAllMarkers function in Seurat. Fold-changes and p-values of gene expression between Sst+ and Calb1+ clusters were calculated using the FindMarkers function with the MAST algorithm95.

Immunohistochemical (IHC) analysis. Mice were deeply anesthetized with isoflurane, then perfused with PBS followed by 4% paraformaldehyde (PFA). Brains were dissected and post-fixed in 4% PFA for 6 h at 4 °C, then immersed in 30% sucrose for 2 days before sectioning (30 μm) on a cryostat (Leica CM1050; Leica Biosystems, Germany). For IHC, slices were pre-incubated in blocking solution (10% normal goat serum with 0.3% Triton X-100 in PBS) for 1 h at room temperature (RT) and incubated overnight at 4 °C with primary antibodies, including rabbit anti-CB (1:500, #14479-1-AP; Proteintech, China), mouse anti-NeuN (1:1 000, #MAB377; Merck, Germany), guinea pig anti-c-fos (1:1 000, #226004; SYSY, Germany), rabbit anti-RGS14 (1:1 000, #16258-1-AP; Proteintech, China), rat anti-mCherry (1:1 000, #M11217; Thermo Fisher Scientific, USA), and rabbit anti-GFP (1:1 000, #A-11122; Thermo Fisher Scientific). The slices were washed in PBS (10 min, three times) and incubated with secondary antibodies (1:1 000, goat anti-rabbit Alexa Fluor 488, goat anti-rat Alexa Fluor 546, goat anti-guinea pig Alexa Fluor 633, and goat anti-mouse Alexa Fluor 647; Invitrogen, USA) for 2 h at RT. Next, the slices were mounted on positive-charged glass slides, coverslipped, and imaged using a confocal microscope (LSM 780, Carl Zeiss, Germany). The images were analyzed using Fiji ImageJ v1.52n.

c-fos labeling. Two-month-old male SST-Cre/Ai14 mice were singly housed in clean cages for 7 days before the experiment, then randomly divided into test and control groups. A test mouse was placed into a clean cage with a novel juvenile mouse. A control mouse was placed into an empty cage. After 10 min, mice from both groups were returned to their home cages for 1.5 h, then perfused with 4% PFA for IHC analysis (as above). All unbiased analyses were done manually from blinded groups.

Single-molecule fluorescent in-situ hybridization (smFISH). Two-month-old male mice were used for all experiments. Hybridization chain reaction (HCR) was used to detect mRNA expressions of Sst, Gad1 and Slc17a696. We designed probes targeting the coding and 3′UTR regions of Sst, Gad1 and Slc17a6 (Sangon Biotech, China). All solutions used for hybridization were prepared using RNase-free reagents and diethylpyrocarbonate (DEPC)-treated double deionized water (ddH O). After perfusion, brains were post-fixed in 4% PFA for 24 h, dehydrated in 20%–30% DEPC-treated sucrose for 24 h, cryosectioned (30 μm), and mounted onto SuperFrost glass slides. The sections were then immersed in 70% ethanol for 16 h at 4 °C, permeabilized by 0.5% Triton X-100 for 1 h at 37 °C, and treated with 10 µg/mL protease K to improve mRNA accessibility. After twice washing in 1 × PBS at RT, the brain sections were pre-hybridized in probe hybridization buffer for 10 min at 37 °C and further incubated with HCR probe (10 µM, Supplementary Table 1) at 37 °C for 3 h. After mRNA hybridization, washing and amplification procedures were conducted as described previously96.

RNAscope-FISH. Tissue preparation for RNAscope-FISH followed the same protocol as smFISH. Brains were cryosectioned into 20-μm sections and mounted onto SuperFrost glass slides. RNAscope-FISH was performed using the RNAscope v2 Assay kit (cat. #323100, Advanced Cell Diagnostics, USA), according to the manufacturer’s instructions. The following target probes were used: Sst (cat. #404631-C1), Calb1 (cat. #428431-C2), Nts (cat. #420441-C3), Prlr (cat. #430791-C3), Htr2c (cat. #401001-C3), and Glp1r (cat. #418851-C2). All probes were obtained from Advanced Cell Diagnostics (ACDBio, USA).

Virus preparation. Two AAV serotypes (AAV2/9 and AAV2-retro) were used. AAV2-retro was used to retrogradely label projection neurons in the vCA197. The plasmid for AAV-DIO-EGFP-2A-TeNT was a gift from Dr. Thomas C. Südhof (Stanford University). All AAVs (AAV-DIO-EGFP, AAV-DIO-tdTomato, AAV-DIO-mCherry, AAV-fDIO-H2B-mCherry, AAV-DIO-H2B-mCherry, AAV-DIO-EGFP-2A-TeNT, AAV-DIO-hM3Dq-mCherry, AAV-DIO-ArchT-tdTomato, AAV-DIO-ChR2(H134R)-EYFP, AAV-fDIO-ChR2(H134R)-EYFP, AAV-CaMKII-ChR2(H134R)-EYFP, AAV-Syn-Cre-off-eNpHR3.0-mCherry, AAV2-retro-Syn-Cre-EGFP, AAV2-retro-Syn-Cre-tdTomato, AAV-CaMKll-eArchT3.0-EGFP, AAV-Syn-DIO-TVA-2a-RG-2a-mCherry), and the SAD ΔG-GFP pseudotyped rabies virus were purchased from Shanghai Taitool Bioscience (China) or Brain Case (China). The final viral vector titers of AAVs ranged from 3 to 8 × 1012 particles/mL. The final titer of the SAD ΔG-GFP pseudotyped rabies virus was 108 infecting units/mL.

Stereotaxic injection. Mice were anesthetized with tribromoethanol (150–250 mg/kg, i.p.). Standard surgery was performed to expose the brain surface above the LS or ventral hippocampus. Coordinates for the LS injections in SST-Cre were: bregma 0.86 mm, lateral ±0.35 mm, and dura −2.5 mm. Coordinates for the LS injections in CB-Cre were: bregma 0.5 mm, lateral ±0.37 mm, and dura −3.0 mm. Coordinates for hippocampal vCA1d injection were: bregma −3.28 mm, lateral ±3.10 mm, dura −1.4 mm. Coordinates for hippocampal vCA1v injection were: bregma −3.28 mm, lateral ±3.10 mm, dura −3.4 mm. AAVs (200–400 nL) were stereotaxically injected using a glass pipette connected to a Nanoliter Injector MICRO-2T (World Precision Instruments, Inc., USA) at a slow flow rate of 0.12 μL/min. The pipette was withdrawn at least 10 min after the viral injection. AAV-DIO-EGFP, AAV-DIOS-tdTomato, or AAV-DIO-mCherry were bilaterally injected into the LS of SST-Cre or CB-Cre mice for control experiments. Experimental designs related to viral injection are summarized in Supplementary Table 2. Schematics of injection sites in the main and supplementary figures were adapted from reference brain images from Allen Mouse Brain Atlas, atlas.brain-map.org.

Optical fiber implantation. Three weeks after AAV injection, ceramic ferrules with an optical fiber (200-μm diameter, N.A. 0.37, Inper Inc., China) were bilaterally implanted with the fiber tips on the top of the dLS (bregma 0.86 mm, lateral ±1.10 mm, and dura −2.55 mm) at a 14° angle and the vLS (bregma 0.5 mm, lateral ±1.47 mm, and dura −3.0 mm) at a 14° angle, the vCA1 (bregma−3.28 mm, lateral ± 3.5 mm, and dura −2.65 mm), the NAc (bregma 1.42 mm, lateral ± 1.07 mm, and dura −3.46 mm) at a 8° angle, the POA (bregma −0.10 mm, lateral ± 1.3 mm, and dura −4.6 mm) at a 10° angle, the AHN (bregma −0.82 mm, lateral ± 1.25 mm, and dura −4.5 mm) at a 8° angle, and the LHA (bregma −2.06 mm, lateral ± 1.0 mm, and dura −5.0 mm). The ferrules were secured onto the skull with dental cement. Optogenetic experiments were performed at least 6 weeks after AAV injection. The tip of the optical fiber was usually located 100~500 μm above the AAV injection center. Only mice with a correct injection sites and optical fiber tracks above the target regions were included in the analyses. Animals with off-target injections or misplaced fibers were excluded, and the number of exclusions is reported in Supplementary Table 4. In very rare cases, control mice with abnormal brain structures (e.g., cerebral edema) were also excluded.

Optogenetic manipulation. The optical fiber cable was connected via patch cords and 1 × 2 Fiber-optic Rotary Joints (Doric Lenses, Canada) to a laser (Shanghai Dream Lasers Technology, China). For ChR2 activation, blue laser pulses (473 nm, 5, 10, or 20 Hz, 5 ms/pulse) were applied during certain behavioral stages. For ArchT silencing, a continuous green laser (532 nm) was applied. Laser power at the optical fiber tip was measured with a power meter (PM100D, Thorlabs, USA) and calibrated to 10 mW/mm2.

Chemogenetic manipulation. For chemogenetic manipulation of LS CB+ neurons, CB-Cre mice were injected with AAV-DIO-hM3D(Gq)-mCherry or AAV-DIO-mCherry (Control). Clozapine-N-oxide (CNO, 5 mg/kg dissolved in saline; #4936, Tocris Bioscience, UK) or saline was i.p. injected 30 min prior to behavioral tests.

Mouse behaviors

Preparation for behavioral tests. Behavioral tests were performed at least 3 weeks after AAV injection. All animals were handled daily for 3 days in advance and habituated for 3 h in the test room before behavioral tests. All apparatuses were cleaned with 75% ethanol to eliminate odors. All behavioral tests were conducted in the light phase (10:00–19:00). All experiments were video-recorded and analyzed using a tracking system (Biobserve, Germany).

Open field test (OFT). White-colored plastic boxes (40 × 40 × 40 cm) were used as the open field chambers. Mice were individually placed into the center of the box and allowed to freely explore for 10 min. Total distance travelled, time spent in center arena (20 × 20 cm), distance travelled in center, and number of visits to center were analyzed.

Elevated plus maze (EPM). The maze consisted of two open arms (35 × 6 cm), two closed arms (35 × 6 × 15 cm), and a central connecting region (6 × 6 cm), positioned 45 cm above the ground. Mice were individually placed in the central region with their head facing the open arm and allowed to freely explore for 5 min. Time spent and number of entries in the open arms vs. closed arms were recorded.

Novel object recognition test-1 (NORT-1). NORT was conducted to evaluate non-social recognition ability, as previously described98. For the training phase, two identical objects (blue cylindrical glass bottles) were symmetrically placed in the open field chamber. Each mouse was allowed to freely explore the objects for 10 min, then returned to its home cage. After 1 h, a novel object (gray cubic brick) was used to randomly replace one of the familiar objects. The test mouse was returned to the chamber and time spent interacting with the objects was recorded. We cumulatively counted the first 20 s that the mouse interacted with the two objects. The discrimination index was calculated by: (T – T ) / (T + T ), where T and T represent time spent exploring novel and familiar objects, respectively.

Novel object recognition test-2 (NORT-2). This test was adapted as previously described15. For the habituation phase, the subject mouse was introduced into the open field chamber for 5 min. Then two identical objects (blue cylindrical glass bottles) were symmetrically placed in opposite corners of the open field chamber. Each mouse was allowed to freely explore the objects for 10 min (learning phase), then returned to its home cage. After 30 min, a novel object (gray cubic brick) was used to randomly replace one of the familiar objects. The test mouse was returned to the chamber and were allowed to explore for 5 minutes. The discrimination index was calculated by: (T – T ) / (T + T ), where T and T represent time spent exploring novel and familiar objects, respectively, during the 5-min period.

Three-chamber social test. The classical three-chamber social test was performed as previously described2. The apparatus was divided into three chambers (30 × 30 × 30 cm), with connecting doors. Two cylinders (5-cm circular base radius and 15-cm height) were placed in the middle of the side chambers. The behavioral test consisted of three sessions, including habituation (10 min), sociability test (10 min), and social memory test (10 min). During habituation, the test mouse was allowed to freely explore the arena for 10 min. For the familiarization session, a novel stranger mouse (age and sex matched, stranger 1) was randomly placed in the left or right cylinder, with the other cylinder empty. The subject mouse was allowed to explore the two cylinders (with or without stranger 1) for 10 min. Interaction time was defined as the time in which the subject mouse spent investigating each cylinder (snout within 2 cm of the mesh barrier), as described previously2. The social index was calculated by: social index = (T – T ) / (T + T ), where T and T represent interaction time for the two cylinders, respectively. For the social memory test session, a novel stranger mouse (stranger 2) was randomly placed in the left or right cylinder, and the now familiar mouse (stranger 1) was placed in the other cylinder. The test mouse was allowed to explore the two cylinders (with novel or familiar stranger) for 10 min. Interaction time towards the familiar mouse (S1) and novel mouse (S2) was recorded. The social discrimination (SD) index was calculated by: SDI = (T – T ) / (T + T ). For most experiments, there was no interval between the familiarization and social memory test sessions. For the prolonged social memory test, the social memory session was performed after an interval of 10–60 min (Supplementary Fig. 11g) or 40 min (Fig. 2l and 4f).

For the social memory experiments related to vCA1 (Fig. 6; Supplementary Fig. 21), a novel stranger mouse (age- and sex-matched, stranger 1) and a novel object (blue brick, 4 × 4 × 6 cm) were randomly placed in the left or right cylinder during the familiarization session. The social memory test session was carried out after an interval of 10 min.

For the two-round social memory test (Supplementary Fig 12), we introduced a 10‑min interval between the first social memory recall (S1 vs. S2) and the subsequent social memory acquisition (S3).

5-trial social memory assay. This test was performed as previously described 2,15. The test mouse was placed in a clean cage for a 4-h habituation period. Subsequently, a novel mouse (5-6 weeks old) was introduced into the cage for four consecutive 1-min trials with a 10-min inter-trial interval. On the fifth trial, a second novel stimulus animal was presented. The direct interaction time was analyzed frame by frame from the video using a Matlab code as previously described53.

Real-time conditioned place preference (RT-CPP). The RT-CPP apparatus consisted of two adjacent chambers (20 × 30 × 30 cm), which were visually (black and white) and tactilely (smooth and rough) different. One chamber was randomly assigned as the initial photostimulated side (phase 1). After 10 min, the stimulated side was switched to the previously non-stimulated chamber (phase 2). In each session, a mouse with optical fibers was placed into the non-photostimulated side and allowed to freely explore the two side chambers. Each time the mouse entered the photostimulated side, green (532 nm) light was delivered until the mouse returned to the non-photostimulated side. There was no interruption between phase 1 and phase 2. Time spent in each chamber (stimulated vs. non-stimulated) was recorded, and preference for the photostimulated side was calculated by: preference = percentage of time spent in photostimulated side – percentage of time spent in non-photostimulated side.

Pseudotyped rabies virus-mediated retrograde tracing and AAV-mediated anterograde tracing. For retrograde tracing, we first unilaterally injected 80 nL of AAV-Syn-DIO-TVA-2a-RG-2a-mCherry into the dLS of SST-Cre or the vLS of CB-Cre mice, respectively. Three weeks later, 300 nL of RV-ΔG-GFP (glycoprotein deficient, GFP-expressing rabies virus) was injected into the same location under biosafety level 2 conditions as above. One week after RV -ΔG-GFP injection, mice were euthanized and their brains were collected. For anterograde tracing, AAV-DIO-EGFP (50 nL) were unilaterally injected into the dLS of SST-Cre or the vLS of CB-Cre mice, respectively. Coronal slices (40 μm) were cryosectioned as above, and every third section was collected for imaging analysis. Fluorescence images were acquired with a SV120 Olympus automatic slide scanner (10× objective, 0.4 NA, Japan).

To quantify rabies virus (RV) labeled neurons along the dorsal-to-ventral axis of vCA1, we adapted a previously described method99. Briefly, A spline curve was first drawn along the vCA1 pyramidal layer from its dorsal to ventral end and divided into 100 equal segments. RV-labeled neurons were then counted within each segment. Vertical boundaries for each segment were defined by the tangent to the spline at the corresponding point. In Fig. 5d, the X-axis (0–100) represents the relative position along the vCA1 dorsal–ventral axis, where 0 denotes the most dorsal region and 100 the most ventral region.

In-vivo electrophysiology

In-vivo single-unit recordings and data analysis. In-vivo electrophysiological recordings were performed in freely moving or head-fixed mice as per previous study53,59. Opto-electrodes (optrodes) consisted of a custom-designed miniature micro-drive containing 16 movable electrodes (25.4-μm nickel-chromium wire, #761500; A-M System, USA) and an optical fiber in the center. Final resistance of the electrodes was 700–800 kΩ. AAV-DIO-ArchT-tdTomato was bilaterally injected into the LS of 7–8-week-old SST-Cre or CB-Cre mice. Three weeks later, mice were anesthetized with tribromoethanol (150–250 mg/kg, i.p.) and placed in a stereotaxic frame. The mice were properly aligned and the optrodes were implanted into the LS. Dental cement was applied to fully cover the exposed skull and secure the implants. After surgery, mice were returned to their home cage and allowed to recover for at least 10 days before recording.

To record single-unit activity in freely moving mice (Supplementary Fig. 9b), we recorded neuronal activity during social interactions100. First, the experimental mouse was placed in the test arena (40 × 40 × 40 cm) for 5 min to record baseline activity. A novel stranger mouse was then introduced to the chamber. Both mice were separated by a plastic wall with small holes (7.5 mm) (Fig. 3b; Supplementary Fig. 9b), which allowed social interaction with each other. Neuronal activity was recorded for another 5 or 20 min during social interaction. Wide-band (WB) signals were recorded for offline sorting and mouse behaviors were videotaped simultaneously for further analysis.

To record single-unit activity in head-fixed mice (Supplementary Fig. 9j-m), we used a previously established recording setup53, in which mice were head-fixed using a 3D-printed head ring and allowed to run freely on a wheel. Each mouse was presented with either an anesthetized stranger mouse (male, 5-6 weeks old) or a novel object (3 × 3 × 3 cm) placed on a movable platform. Once positioned, the stimulus was approximately 0.5 cm from the nose of the recording mouse. For SST+ neuron recordings during social interactions, the stimulus was presented for 5 s with 25 s intervals, repeated for 20 trials.

To record mutual inhibition during social interactions in vivo (Supplementary Fig. 16), neuronal activity was recorded during a 10-min baseline period or a 10-min social interaction period, during which an anesthetized male mouse was continuously presented. Optogenetic stimulation (λ = 532 nm, 3 s pulses, 10 s inter-pulse interval, 20 trials) was delivered within 1 minute of each recording condition.

Single-unit sorting was performed manually by Offline Sorter v4.0 (Plexon, Inc., USA). Spiking activities were digitized at 40 kHz and stored for offline sorting. The WB signals were high-pass filtered at 250 Hz and waveform detection thresholds were placed at -4.0 to -4.5 times the standard error of digital signal range, depending on the signal-noise ratio. The detected waveforms were aligned at the valley point, and two-dimensional principal component analysis (PCA) was used for separation of single-unit spikes. The distribution of inter-spike intervals (ISIs) from all isolated single-unit spikes exhibited recognizable refractory periods (> 1 ms). Only well-isolated units (L ratio < 0.2, isolation distance > 15) were included for analyses.

In-vivo firing rate analysis. Single-unit responses were analyzed using NeuroExplorer v5.0 (Plexon, Inc.). Well-separated single-unit spikes were collected to analyze neuronal responses to social stimuli. During 20-min social interactions, the start and end time points of each social bout were manually labeled by examining behavioral videos frame by frame. The ISIs of single-unit spikes during baseline and social interaction were compared to evaluate significant firing rate differences (p < 0.05, two-tailed unpaired Student’s t-test). The mean and SD during the total recorded time were used for calculating firing rate Z-score. Neurons were considered as activated with a firing rate Z-score value > 2.0 during the 3 s of stimulus presentation101.

In-vivo cell type identification. To identify SST+ and CB+ single units, we utilized ArchT-mediated optic tagging102, whereby laser pulses (λ = 532 nm, 3 s long) were delivered via the optical fiber after each behavioral recording session (Supplementary Fig. 9).

In-vivo local field potential recording. Optrodes containing two-channel single electrodes (75-μm stainless steel wire, #793400; A-M System, USA) and an optical fiber were hand-made as described previously59. Local field potentials (LFPs) were sampled at 1 kHz with a low-pass filter at 250 Hz. The LFP power spectra across four frequency bands, including alpha (1–3 Hz), theta (4–12 Hz), beta (13–30 Hz), and gamma (31–80 Hz), were analyzed. Power spectrum density (PSD) was calculated using NeuroExplorer v5.0 (Plexon Inc.). For optogenetic manipulation during LFP recordings, 5-ms blue light pulses (5, 10, and 20 Hz, λ = 473 nm) were used to activate SST+ neurons, whereas continuous green light (λ = 532 nm) was delivered to inhibit SST+ neurons or the vCA1d→dLS pathway.

In-vivo phase locking analysis. Single units and LFP recorded by the 16-channel optrode were used for phase-lock analysis to evaluate the relationship between theta oscillations and timestamps in SST+ and CB+ neurons in the LS, as described previously58,59. The oscillatory activity phase was extracted using Hilvert’s transformation and converted into angle degrees. Rayleigh test was used for circular uniformity to identify significant correlations between the timing of spikes and specific phase of the theta cycle58,59.

Slice electrophysiology and optogenetics. Mice were euthanized with isoflurane and coronal LS, AHN, or LHA slices (300-μm thick) were sectioned with a vibratome (VT1200S; Leica Biosystems, Germany) in cutting solution containing (in mM): 228 sucrose, 2.5 KCI, 26 NaHCO , 1 NaH PO ·2H O, 11 D-Glucose, 0.5 CaCl , and 7 MgCl , then transferred to artificial cerebrospinal fluid (ACSF) containing (in mM): 119 NaCl, 2.5 KCI, 26 NaHCO , 1 NaH PO ·2H O, 11 D-Glucose, 2.5 CaCl , and 1.3 MgCl (pH = 7.4). Slices were incubated at 35 °C for 30 min and then at RT until use. Recordings were performed in a submerged-style chamber mounted under an infrared-differential interference contrast (IR-DIC) microscope (BX-51 WI; Olympus, Japan). Whole-cell recordings were performed using a MultiClamp 700B amplifier and Digidata 1550B4 (Molecular Devices, USA). Patch pipette resistance was 4–6 MΩ. Signals were sampled at 20 kHz, filtered at 10 kHz, and analyzed using Clampex v10.4 (Molecular Devices).

To analyze electrophysiological properties, SST+ and CB+ neurons were visualized by tdTomato expression in SST-Cre/Ai14 or CB-Cre/Ai14 mice, respectively. TdTomato+ neurons were recorded with a K-gluconate-based internal solution containing (in mM): 135 K-gluconate, 10 HEPES, 8 KCl, 0.25 EGTA, 0.3 Na GTP, 2 MgATP, 7 phospho-creatine, and 0.1 spermine (pH 7.25–7.3; osmolarity 294–298). To compare the neuronal excitability, the recorded neurons were subjected to step current injections with different amplitudes ranging from 20 to 160 pA, and the number of action potentials (APs) was counted accordingly. To record HCN-mediated sag amplitudes, the recorded neurons were subjected to step current injections with different amplitudes ranging from –80 pA to –20 pA, and the sag amplitudes were estimated by subtracting the values at the onset of hyperpolarizing voltages (peak amplitude) from those at the end (steady-state) as previously described52.

For recording IPSCs from SST+ neurons, AAV-DIO-ChR2-EYFP was bilaterally injected into the LS of SST-Cre/Ai14 mice at postnatal day 35–40 (P35–P40). After 6 weeks, tdTomato-/EYFP- neurons (presumably Cre- neurons) in the LS were recorded using a KCl-based internal solution containing (in mM): 71 KCl, 72 K-gluconate, 10 HEPES, 2 MgCl , 0.025 BAPTA, and 2 MgATP (pH 7.25–7.3; osmolarity 295–300). To study inhibitory synapses from CB+ to SST+ neurons, AAV-DIO-ChR2-EYFP and AAV-fDIO-H2B-mCherry were bilaterally injected into the LS of CB-Cre/SST-Flp mice at P35–P40. After 6 weeks, mCherry+ neurons (SST+ neurons) in the LS were recorded with the same KCl-based internal solution. Light (2 ms)-evoked IPSCs were recorded in the presence of 4-aminopyridine (4-AP, 50 μM; #0940, Tocris) and tetrodotoxin (TTX, 1 μM; #1078, Tocris). D-(-)-2-amino-5-phosphonopentanoic acid (D-AP5, 50 μM; #0106, Tocris) and 6-cyano-7-nitroquinoxaline-2,3-dione disodium (CNQX, 20 μM; #1045, Tocris) or picrotoxin (PTX, 50 μM; #1128, Tocris) were perfused with ACSF to examine the neurotransmitter type used by ChR2-EYFP-expressing neurons. The inhibitory synapses from SST+ to CB+ neurons were also studied by injecting AAV-fDIO-ChR2-EYFP and AAV-DIO-H2B-mCherry into the LS of CB-Cre/SST-Flp mice. The SST+-dLS→LHA and CB+-vLS→AHN pathways were also validated as mentioned above.

For dual patch-clamp recordings, AAV-CaMKII-ChR2-EYFP was bilaterally injected into the vCA1d or vCA1v of CB-Cre/SST-Flp mice at P35–P40. After 6 weeks, SST+ neurons in the dLS and CB+ neurons in the vLS were recorded using the K-gluconate-based internal solution. Light-induced excitatory postsynaptic currents (EPSCs) were recorded in SST+ and CB+ neurons simultaneously.

For sEPSC recordings, AAV-DIO-H2B-mCherry was bilaterally injected into the LS of SST-Cre or CB-Cre mice at P45–P50. After two weeks, SST+ neurons in the dLS and CB+ neurons in the vLS were recorded using a CsMeSO -based internal solution (in mM): 140 CsMeSO , 10 HEPES, 8 CsCl, 0.25 EGTA, 0.3 Na GTP, 2 MgATP, 7 phospho-creatine, and 0.1 spermine (pH 7.25–7.3; osmolarity 295–300). The sEPSCs were recorded with 50 μM PTX in ACSF.

For recording the PPRs of vCA1-LS EPSCs, AAV-CaMKII-ChR2-EYFP and AAV-DIO-H2B-mCherry were bilaterally injected into the vCA1 and LS of SST-Cre or CB-Cre mice at P45–P50, respectively. After 6 weeks, EPSCs evoked by two light (2 ms) pulses at 20 Hz were recorded in SST+-dLS or CB+-vLS neurons in the presence of 50 μM PTX.

Social memory acquisition protocol for slice physiology. sEPSCs were recorded 2 weeks after viral injection, while optogenetically evoked vCA1-LS EPSCs were recorded 6 weeks after viral injection. Briefly, subject mice were individually habituated in clean cages for 25 min per day for 3 consecutive days prior to the experiments. On the fourth day, following a 10-min of habituation, a novel juvenile mouse was introduced to the cage, and the subject mouse was allowed to freely interact with the stranger mouse for 10 min. A control mouse was placed in a similar but empty cage for 10 min. After 5 min, subject mice from the control and social groups were euthanized for slice physiology.

Rotarod running protocol for slice physiology. Two weeks after viral injection, all mice underwent training to run on a rotating rotarod (8r/min) for 10 min, followed by a 5-min stationary period. The training was conducted daily for three consecutive days. On the fourth day, after environmental adaptation, mice were assigned to either the running group (rotating rod, 8r/min) or the control group (stationary rod). Both groups remained on the rod for 10 min, followed by an additional 5-min stationary period. Mice that completed the full 15-min without dropping were euthanized for slice physiology.

Morphological reconstruction and analysis. For labeling the recorded neurons, we included biocytin (0.2%) in the K-gluconate-based internal solution. After recordings, slices with biocytin-labeled cells were post-fixed in 4% PFA overnight at 4 ℃. The slices were washed in 0.01 M PBS three times, permeabilized with 0.5% Triton X-100 for 1 h at RT, then incubated in Alexa Fluor 488-conjugated streptavidin (1:1 000, #S11223, Invitrogen) for 2 h at RT. For three-dimensional (3D) reconstruction of labeled cells, z-stack images (0.5 μm/image) were acquired with a confocal microscope and processed using Fiji ImageJ as described previously103.

Statistical analysis

All statistics were calculated using GraphPad Prism v8 or Matlab R2021. All values in the text and figure legends are presented as mean ± SEM. Data analysis was performed by experimenters blind to experimental conditions. Normality of data was assessed using the Shapiro-Wilk test, and equality of variances was checked using the Brown-Forsythe test. For unpaired non-parametric data, two-tailed Mann-Whitney test was used as indicated. For unpaired parametric data with unequal variance, two-tailed Welch's t-test was used to compare pairwise differences. For unpaired parametric data with equal variance, we applied two-tailed unpaired Student’s t-test or one-way Repeated measures (RM) analysis of variance (ANOVA) with Holm–Sidak post-hoc test to examine pairwise differences. For normalized data compared to baseline mean, the two-tailed one-sample t-test was used for parametric data, and one-sample Wilcoxon signed rank test for non-parametric data. In same-mouse or same-cell experiments, two-tailed paired Student’s t-test and two-tailed Wilcoxon signed rank test were used for parametric and non-parametric two-paired data, respectively. Two-way RM ANOVA with Holm–Sidak post-hoc test was used to compare multiple related samples. Two-tailed Chi-squared test was used for comparing multiple composition ratios. Rayleigh test was used to identify significant correlations between the timing of spikes and specific phase of the theta cycle. Two-tailed Kolmogorov-Smirnov test was used to analyze the statistical significance of the cumulative distribution of sEPSC amplitudes or inter-event intervals in slice electrophysiology. Detailed statistical analyses are provided in Supplementary Table 5. Significance notation: n.s., not significant; *p < 0.05, **p < 0.01, ***p < 0.001; #p < 0.05, ##p < 0.01, ###p < 0.001.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This study investigated the two parallel downstream circuits of ventral CA1, which has been shown to be the center of social memory, that are critical for social memory acquisition but not for social memory retrieval. The involvement of two circuits, vCA1d-SST+-dLS-lateral hypothalamic area and vCA1v-CB+-vLS-anterior hypothalamic nucleus, has been beautifully demonstrated using chemogenetic/optogenetic manipulation and electrophysiology. The results are very clear and strongly support the conclusions, so it is a study of exceptionally high scientific value to understand neural mechanisms underlying social memory. I have several concerns and suggestions to improve the paper.\n1. While there is no doubt that the brain region referred to as vCA1v is indeed vCA1, the region referred to as vCA1d is unclear from the coronal section whether it is CA1 or CA2. This is particularly important because dLS receives especially strong neural projections from the CA2 region, making it necessary to clarify this point. Therefore, in addition to the coronal sections, horizontal sections should be shown, and co-staining with CA2 marker genes such as RGS14 should be conducted.\n2. Some of the data in this paper are related to the following study recently published in eLife. It is necessary to clearly highlight the differences between the two in the discussion section and to cite the study appropriately.\n“A ventral hippocampal-lateral septum pathway regulates social novelty preference. Rashid et al., https://elifesciences.org/reviewed-preprints/97259”\n3. Regarding Figure 4 and Supplementary Figure 11, the SST+ neurons and CB+ neurons are shown to inhibit each other bilaterally. It is also suggested that they contribute to social memory performance as shown in Figure 8, partially supported by the SST+ (but not CB+) neurons contributing to enhanced theta oscillations (Figure 3) and presynaptic potentiation in vCA1d-SST+-dLS (but not in vCA1v-CB+-vLS) (Figure 6). This seems to indicate that positive regulation by SST+ neurons is stronger than negative regulation by CB+ neurons. Could the authors discuss these asymmetric results more, possibly from the viewpoint of the balance between bilateral inhibition? Furthermore, given the presynaptic potentiation in vCA1d-SST+-dLS, the results that vCA1-LS pathways are not important for social memory retrieval are counterintuitive. What could be the potential mechanism to explain this?\n4. The authors showed that the vCA1-LS circuit is important for social memory acquisition but not recall, and the vCA1-NAc circuit is important for social memory recall but not acquisition (Supplementary Figure 15). According to Gergues et al. (Nature Neuroscience 23:1444, 2020), it has been shown that there are many neurons projecting to both LS and NAc. Are these dual-projecting neurons involved in social memory regulation shown in this study? Or are the single-projecting neurons involved?", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "In this study, Zhang et al. investigated the role of two distinctive LS subpopulations- SST- and CB-expressing LS neurons- in bidirectional control of social memory acquisition. Using single nucleus RNA sequencing and immunostaining, they observed that SST- and CB-expressing LS neurons have molecularly and anatomically distinctive characteristics. The authors then demonstrated that each population positively and negatively regulates social memory acquisition, respectively. Optogenetic experiments further highlighted that this regulation is specifically engaged in social memory acquisition, but not social memory recall or sociability per se. Notably, SST LS neurons play a critical role in regulating socially relevant theta oscillations. At the circuit level, the dorsal and ventral LS (dLS, vLS) receive inputs from distinct parts of the hippocampus along its dorsal-ventral axis. Circuit-specific optogenetic manipulation revealed that vCA1d>dLS and vCA1v>vLS pathway can control social memory acquisition in a bidirectional way, similar to the effects observed after manipulating SST- and CB-expressing neurons, predominantly located in dorsal and ventral part of LS, respectively. The authors went one step further to demonstrate that the LHA and AHN are critical downstream targets of SST-and CB-expressing LS neurons to regulate social memory acquisition. Overall, this study provides valuable information into how specific neuronal circuits connecting the hippocampus to LS influence the social memory process. However, inconsistencies in data hinder in-dept interpretation, and generating superficial conclusions, primarily based on the results from artificial manipulation, is insufficient to support publication at this time. To further improve the paper, more clarifications listed below would be helpful.\nHere are some specific comments:\n1. In Figure 1, snRNA seq results show that SST- and CB-expressing LS neurons display distinct molecular profiles with different expression levels for Nts, Glp1r, Htr2c and Prlr. Has this result been confirmed using other methods, such as in situ hybridization and immunohistochemistry?\n2. The author claimed that previous studies demonstrated the ‘controversial’ role of the LS in social behaviors (line #55, 139), but it is unclear what it meant by ‘controversial’ in this context. Given the heterogeneity of LS cell types, several studies have been descriptive, focusing on different populations of LS and highlighting their functional relevance on different domains of social behaviors. These studies do not necessarily appear to be inconsistent or in disagreement (controversial) with each other. Please clarify this point.\n3. Figure 3 shows that theta oscillation power is increased during both social bouts and non-social intervals. Is this LS theta oscillation still sustained even after the social stimuli are removed, or is it specifically engaged during the social context? The same question would be related to SST LS neurons: Is the proportion of theta phase-locked SST LS neurons unique to social contexts?\n4. What is the explanation for using continuous social interaction tests for 20 min in Figure 3, instead of separate sessions of sociability vs. social novelty, as used throughout the rest of the paper? Figure 3e shows consistent enhancement of theta rhythm oscillations between P1 and P4 with no statistical difference as the familiarity is developed. More evidence is needed to substantiate their claim, this is a key neural mechanism for social memory acquisitions (line #220).\n5. What is the justification for the lack of changes in the power of theta rhythm oscillations in response to 20 Hz-ChR2 activation of SST LS neurons in Figure 3m?\n6. In Figure 5, TeNT silencing is applied to the vCA1d>dLS pathway using intersectional viral strategies. Given the collateral projections of vCA1 neurons, it is important to clarify whether the vCA1d>dLS pathway is a key participant for blocking the enhanced theta oscillations during social interaction in Supplementary Fig.14.\n7. In Figure 5d, it is unclear what numbers (0~100) on the X axis represent regarding the dorsal-ventral axis of vCA1.\n8. Supplementary Figure 6 shows that both SST- and CB-expressing LS neurons are activated by social stimuli, but this result is correlated with increased in vivo firing rate of SST LS neurons, but not with the one of CB LS neurons (Supplementary Fig. 7). Please discuss why.\n9. Based on supplementary Fig. 9e, the authors claimed that inhibition of SST LS neurons did not produce rewarding or aversive effects, though there is a lack of interpretation for many data indicating reduced anxiety level after inhibiting SST LS neurons or SST dLS> LH circuitry in supplementary Fig. 8, 17. It is unclear to understand the situation that poor social memory and low anxiety are related to each other, given that high anxiety typically causes memory loss in real world situations.\n10. The authors consistently claimed that SST LS and CB LS neuronal circuit exert ‘opposing’ effects on social memory, mainly based on results from artificial manipulation in Figures 2, 4 and 5. However, I’m unsure about the interpretation of ‘opposing role’, given that both SST- and CB-expressing LS neuronal populations are similarly activated by social stimuli (Supplementary Fig. 2). In addition, CB LS neuronal activity is not correlated with socially relevant theta oscillation (Supplementary Fig. 7), as well as frequency/amplitude of sEPSCs in CB LS neurons are not affected by social interaction (Figure 6), while SST LS neurons are largely engaged in both cases. Beyond the data from artificial manipulations, more physiological/endogenous evidence is needed to support the claim that SST LS and CB LS neuronal circuits oppose each other for regulating social memory acquisition.\n11. In Discussion, the authors claimed that the opposing effects of vCA1d>SST dLS>LHA and vCA1>CB vLS> AHA on social memory may be explained by the predominantly GABAergic nature of AHN neurons and the predominantly glutamatergic nature of LHA neurons (line #532~534). What is the justification for this claim? Given previous studies suggesting that both AHN and LHA contain a decent amount of intermingled GABAergic and glutamatergic neurons, the authors need to provide more evidence in depth to support their explanation.\n12. There are some misplaced figure annotations throughout which should be corrected.", "reviewer_4": "The authors present an interesting and important data set exploring the contributions of somatostatin (Sst) and calbindin 1 (Calb1)-expressing cells in the lateral septum (LS) to social behavior. The authors used single-nucleus RNA sequencing (snRNAseq) and histological preparations to show that Sst and Calb1 are largely nonoverlapping in the LS. The authors then use a variety of circuit manipulations to show that inhibition of Sst cells reduces social discrimination when performed at least during training; discrimination is increased with their stimulation. Inhibition of Sst cells appears to reduce theta power, while their activation increases it. Conversely, Calb1 manipulations show opposite effects. This may be due to inhibition of Sst cells by Calb1 neurons, as seen in their slice preparations. Additionally, Sst and Calb1 cells appear to have differential input from the hippocampus, based on rabies tracing and ex vivo electrophysiology. Inhibition of inputs from CA1d to the dLS during training reduced social discrimination, whereas social discrimination was disrupted by activation of CA1v inputs to the vLS, mirroring what was seen with Sst/Calb1 manipulations. Generally, the paper is well-written, the topic is interesting, and the cells and circuits involved are likely to be of high interest to many readers. The authors should be commended for their extensive dataset. However, my enthusiasm is deeply hindered by a surface-level discussion and analysis of the sequencing (there is little comparison of their findings with others who have previously sequenced the LS; some prior works are not cited) and of their other circuit mapping and behavioral experiments (others have also explored functions of Sst cells in the LS and little is discussed of this prior work). I expand on these concerns below:\nMAJOR ITEMS (in no particular order):\n---Theta power in the LS appears to similarly increase during both social and non-social events (Figure 3). While it appears Sst neurons phase lock to theta, it’s unclear then how Sst activity encodes social events. Did the authors observe single-unit activity of Sst cells during social bouts? Do they correlate with behavior? The authors also suggest that sociability itself was unaffected by the circuit manipulations, but is exploration of S1 higher in Sst-ArchT vs. controls (Supp. Figure 9)?\n---Related to the above, socially interacting mice may locomote more than a mouse in a familiar empty cage. Is there any concern that the data in Supplementary Figure 6 and Figure 6 reflect differences in locomotion, which may be independent of “social” experience per se? In other words, would a similar outcome occur if mice were wheel-running or given other novel stimuli?\n---Others have explored the function of Sst cells in the LS including in the OFT and EPM. For example, Besnard et al. 2019 did not find changes in OFT/EPM with optogenetic inhibition of Sst cells in the LS, however the authors here observed more time in the open arms with TeNT inactivation. Conversely, Besnard et al. 2019 observed more in time in the open arms of EPM with optogenetic stimulation, which may be in conflict with what the authors show here. These differences are not discussed/addressed.\n---It is unclear to me whether appropriate stats are used. For most of the memory recall tests, it appears the authors used one t-test for controls and a separate one for experimental groups (comparing S1 to S2), without reporting any sort of ANOVA/interaction that directly compares controls with experimental mice. The authors use t-tests for the discrimination ratio, but this ratio should mirror the interaction found in the investigation times. I suspect ANOVAs may yield significant interactions that would merit these comparisons (that should be followed by appropriate posthocs), but currently many of the statistics appear to lack rigor. Similarly, I am unsure why Figure 3e (and similar panels) makes use of multiple t-tests in the absence of an ANOVA.\n---This is not the first dataset to use snRNAseq to explore the diversity of LS cells. Surprisingly, the authors do not cite some of these prior works. This should be rectified. Moreover, very little effort is made to discuss how their data compare to these prior studies. Do the authors observe the same populations of cells in their dataset as others and in similar proportions? Why or why not?\n---I find the designation of “non-LS” to certain clusters in the sequencing data to be a bold claim. The authors largely rely on in situ images from the Allen Brain to help establish whether cells may be “LS” or “non-LS”. This approach is limited as the in situ data may not capture the dynamic expression of these genes or may not have the resolution to account for sparse labeling in the septum (or low levels), or may be expressed in other parts of the septum that are simply not shown in the in situ images. It is entirely possible for putative LS cells to be found within clusters that the authors designate as “non-LS”, and this caveat or possibility is not addressed or discussed in the manuscript. For example, Coro6 is shown, and this appears to have fairly specific labeling in the MS, but there are clearly many cells shown in the tSNE that fall within cells kept for “LS”. Similar things may be said about Col6a1 or Nrn1/etc. The converse is also true: based on the same Allen Brain in situ images, Sst and Calb1 are also expressed in the medial septum, so it is unclear if cells kept in the “LS” clusters would include those. Reporting additional top genes for the clusters may help the reader better determine the potential for non-LS cells to be represented in the tSNE. Right now, the most important aspect of these data to me are Figure 1C, but this depends on the relative inclusion/exclusion of cells as discussed above.\n---After excluding the “non-LS” cells in the tSNE, the authors then note what I assume are the top genes for each cluster. This strategy seems flawed to me because the clusters shown are formed relative to the expression of genes in the “non-LS” clusters when they were present. In other words, if the authors excluded the cells of the “non-LS” cells first then generated the tSNE (just as they did for transitioning from Supplemental 1 to Figure 1), do the authors think that the clustering for only “LS” cells would be similar? I suspect not, because these clusters already factor in the MS cells/etc.\n---Only in the methods do the authors note these data are acquired from male mice. It should be clearly stated in the title or abstract that all of the data were collected from male mice.\n---The authors state that the data shown only include animals with optical fibers above the target regions in the final analyses, but some of the current images make me uncertain about the accuracy of this (see Figure 5V). Similarly, it is unclear how much spread or specificity there may be in some of these injections/viruses. For example, there appears to be a lot of viral expression in the dorsal regions of the LS in CB-Cre mice. Are these terminals from ventral Calb1 cells? Are there more dorsally expressed Calb1 than is appreciated in the immunohistochemistry experiments? Also, several experiments use atlas schematics to represent the injections for the experiments, but no (or only partial) representative images are shown of injection sites. In Supplementary Figure 16e/h, there appears to be considerable expression of virus in regions above the POA, in what appears to be the BNST. The authors do not note the BNST in output terminals of the other figures. Are these from the LS? If not the LS, where are they from? My confidence may be bolstered by including more images of injections/placements (could be supplementary) and/or documenting viral spread/fiber placements. Perhaps the authors should note the number of exclusions based on hits/misses. Additionally, others have looked at outputs of Sst cells from the LS (Besnard et al. 2019), and there is no discussion of how their mapping compares (for example, no SUM is shown).\n---The authors state: “The opposing effects of these pathways on social memory may be explained by the predominately GABAergic nature of AHN neuorns and the predominately glutamateric nature of LHA neurons.” GABAergic neurons are widely expressed within the LHA. Moreover, the inputs/outputs of the AHN vs. LHA may be quite distinct. There are many citations that could potentially be included here. I recommend a more thorough discussion here.\n---Others have performed rabies tracing of Sst neurons of the LS (Besnard et al. 2019)—there is no discussion of how the authors’ findings compare with this work. This seems insufficient. Did the authors see the same inputs and at a similar level?\n---Do Calb1 neurons overlap with Esr1 neurons?\nMINOR ITEMS:\n---I believe the dissection of the LS for snRNAseq requires more details (rather than simply referring to a separate paper that sequenced a different structure). How much tissue was collected? Was an equivalent amount of tissue collected from each animal? The LS is a long, bilateral structure, how were the authors able to determine coverage or specificity to the LS?\n---It doesn’t bother me, as it is just a stylistic choice, but some of the legends are incredibly lengthy, perhaps they could be shortened by adding some of the information in the main text.\n---In general, the authors found the majority of their circuit manipulations to only have effects on social behavior when manipulated during training/encoding but not when manipulated at test. If the authors then added a new animal after the test, do they expect to eliminate secondary discrimination? If so, this may bolster the argument towards specificity to encoding.\n---I realize the authors report the number of cells, but can the authors report the number of mice from which the cells are derived in the slice electrophysiology experiments?\n---Have the authors tried using a reporter line (crossing CB-Cre with the reporter line) to match what was seen with the immunohistochemistry preparations?\n---Is there concern for ArchT being used in the terminal inhibition experiments? There is some evidence that sustained light activation of ArchT actually increases synaptic release at terminals: Mahn et al. 2016 Nature Neuroscience.\n---There may be some typos in the text for which figure is being referred to.\n---The authors state in the abstract: “While the hippocampus is crucial for social memory, the dynamic regulation of social memory, particularly the negative regulation, remains unclear.” I’m unsure what the authors mean by “negative” regulation, as this sounds like valence (especially since they do not see changes in RTRPP with Sst/CB). Can the authors clarify?"}, "author_response": "We sincerely thank the reviewers for their insightful and constructive comments. In response, we have performed additional experiments, re-analyzed data, and expanded our discussion to address the points raised. With their valuable input, the clarity and overall quality of our manuscript have been greatly improved.\nPoint-to-point responses:\n(Reviewers’ comments in Blue; Our responses in Black)\nPS: All changes in the revised manuscript are highlighted with yellow in the marked version.\nReviewer #1 (Remarks to the Author):\nThis study investigated the two parallel downstream circuits of ventral CA1, which has been shown to be the center of social memory, that are critical for social memory acquisition but not for social memory retrieval. The involvement of two circuits, vCA1d-SST+-dLS-lateral hypothalamic area and vCA1v-CB+-vLS-anterior hypothalamic nucleus, has been beautifully demonstrated using chemogenetic/optogenetic manipulation and electrophysiology. The results are very clear and strongly support the conclusions, so it is a study of exceptionally high scientific value to understand neural mechanisms underlying social memory. I have several concerns and suggestions to improve the paper.\nResponse: Thanks for your positive comments and insightful suggestions.\n1. While there is no doubt that the brain region referred to as vCA1v is indeed vCA1, the region referred to as vCA1d is unclear from the coronal section whether it is CA1 or CA2. This is particularly important because dLS receives especially strong neural projections from the CA2 region, making it necessary to clarify this point. Therefore, in addition to the coronal sections, horizontal sections should be shown, and co-staining with CA2 marker genes such as RGS14 should be conducted.\nResponse: We appreciate your constructive comment very much. To test whether SST+-dLS neurons receive monosynaptic inputs from CA2 neurons, we have conducted additional RV tracing experiments and performed immunostaining for RGS14, a molecular marker of CA2 neurons, in horizontal hippocampal slices (Supplementary Fig. 19, revised manuscript). We found that RGS14+/GFP+ neurons account for 10.64% ± 1.39% of RGS14+ CA2 neurons, indicating that a subset of CA2 neurons projects to SST+-dLS neurons. However, RGS14+/GFP+ neurons represent only 3.12% ± 0.17% of all GFP+ input neurons in the hippocampus, suggesting that CA2 provides a relatively minor contribution to the total excitatory input to SST+-dLS neurons. Given that vCA1 neurons receive direct inputs from dorsal CA2 region1, we speculate that SST+-dLS neurons might also receive indirect input from CA2 neurons through a dCA2→vCA1→LS pathway. We have updated this notion in the revised manuscript (Result section, lines 357-364; Discussion section, lines 608-611).\nSupplementary Fig. 19 in revised manuscript. Mapping of the monosynaptic inputs from CA2 to SST+-dLS neurons using pseudotyped rabies virus.\n(a) Schematic for rabies virus-based retrograde tracing strategy, as described in Fig. 5a. Starter cells were identified by co-expression of mCherry and GFP, whereas input neurons were labeled by GFP alone.\n(b) Diagram illustrating the locations of coronal LS section containing the injection site (position #1, shown in panel c) and horizontal hippocampal sections (positions #2–#4, shown in panel d).\n(c) Representative coronal section showing that SST+ starter cells are unilaterally confined to the dLS.\n(d) Representative horizontal sections showing RV-labeled input neurons co-labeled with the CA2 marker RGS14.\n(e) Magnified areas of the CA2 from panel (d). Yellow arrowheads indicate neurons co-expressing GFP and RGS14.\n(f) Left, proportion of RGS14⁺ neurons that were GFP⁺ (double-labeled) within CA2. Right, proportion of GFP⁺ input neurons across the hippocampus that were double-labeled in CA2.\n2. Some of the data in this paper are related to the following study recently published in eLife. It is necessary to clearly highlight the differences between the two in the discussion section and to cite the study appropriately.\n“A ventral hippocampal-lateral septum pathway regulates social novelty preference. Rashid et al., https://elifesciences.org/reviewed-preprints/97259”\nResponse: Thank you for your suggestion. Rashid et al. reported that inhibition of the vHPC→LS→ VTA pathway abolished social novelty preference2. In contrast, our study identified the vCA1d→ SST⁺–dLS→LHA and vCA1v→CB⁺–vLS→AHN pathways as two distinct hippocampal–septal– hypothalamic circuits that bidirectionally regulate social memory.\nIn our anterograde tracing experiments, we observed minimal GFP⁺ axonal projections from SST⁺ and CB⁺ LS neurons to the VTA (Supplementary Fig. 23a-c, revised manuscript), suggesting these populations do not significantly contribute to the vHPC→LS→VTA pathway. Furthermore, Rashid et al. demonstrated that VTA-projecting LS neurons receive inputs from both dCA1 and vCA12, whereas our data demonstrate that SST⁺–dLS and CB⁺–vLS neurons receive strong input primarily from vCA1, not from dCA1(see new Supplementary Fig. 17a-b, revised manuscript).\nPrevious studies have demonstrated that Esr1⁺ neurons in the LS send dense projections to the VTA and are implicated in reward seeking behaviors3. We therefore speculate that Esr1⁺ LS neurons may underlie the vHPC→LS→VTA circuit described by Rashid et al., whereas the SST⁺ and CB⁺ LS neurons characterized in our study form separate circuits that regulate social memory via hypothalamic targets. We have now incorporated this comparison and citation into the revised Discussion section (Discussion section, lines 622-628).\n3. Regarding Figure 4 and Supplementary Figure 11, the SST+ neurons and CB+ neurons are shown to inhibit each other bilaterally. It is also suggested that they contribute to social memory performance as shown in Figure 8, partially supported by the SST+ (but not CB+) neurons contributing to enhanced theta oscillations (Figure 3) and presynaptic potentiation in vCA1d-SST+-dLS (but not in vCA1v-CB+-vLS) (Figure 6). This seems to indicate that positive regulation by SST+ neurons is stronger than negative regulation by CB+ neurons. Could the authors discuss these asymmetric results more, possibly from the viewpoint of the balance between bilateral inhibition? Furthermore, given the presynaptic potentiation in vCA1d-SST+-dLS, the results that vCA1-LS pathways are not important for social memory retrieval are counterintuitive. What could be the potential mechanism to explain this?\nResponse: Thank you for your insightful comments. We agree that the asymmetric influence of SST⁺ and CB⁺ neurons is a compelling observation that warrants further discussion. Based on our current dataset (Fig. 6), the vCA1d→SST⁺–dLS circuit undergoes selective synaptic potentiation during social memory acquisition, whereas no significant changes are observed in the vCA1v→CB⁺–vLS pathway. This synaptic asymmetry likely increases the responsiveness of SST⁺–dLS neurons to vCA1 input, thereby enhancing their functional influence relative to other LS subpopulations. Furthermore, due to the observed mutual inhibition between SST⁺ and CB⁺ neurons (Fig. 4g-j; Supplementary Fig. 15, revised manuscript), increased activity of SST⁺ neurons may further suppress CB⁺ neuron firing via lateral inhibition, thus amplifying the functional impact of the SST⁺ population during the memory acquisition.\nWe propose that SST⁺ and CB⁺ neurons work in a dynamically balanced manner to stabilize social memory formation. Their mutual inhibition may serve as a homeostatic mechanism that prevents memory from becoming either excessively rigid or unstable. Conceptually, these two neuronal populations may act similarly to a gas and brake system in a vehicle—SST⁺ neurons acting as the accelerator to promote memory encoding, and CB⁺ neurons serving as the brake to regulate or constrain it. The relative strength of these pathways may shift dynamically depending on behavioral demands.\nRegarding the question of why the potentiated vCA1d→SST⁺–dLS pathway does not appear to contribute to social memory retrieval, we speculate that activation of SST⁺–dLS neurons and their downstream targets do not directly drive social exploration behavior (Supplementary Fig. 11c, revised manuscript). We hypothesize that social memory is a multi-phase process involving coordinated plasticity across distributed circuits, and further studies will be required to clarify the retrieval-specific plasticity mechanisms.\nWe have incorporated this interpretation into the revised manuscript (Discussion section, lines 576-583).\n4. The authors showed that the vCA1-LS circuit is important for social memory acquisition but not recall, and the vCA1-NAc circuit is important for social memory recall but not acquisition (Supplementary Figure 15). According to Gergues et al. (Nature Neuroscience 23:1444, 2020), it has been shown that there are many neurons projecting to both LS and NAc. Are these dual-projecting neurons involved in social memory regulation shown in this study? Or are the single-projecting neurons involved?\nResponse: Thank you for this insightful question. As reported by Gergues et al., vCA1 region projects to both LS and NAc, including neurons that project exclusively to LS, exclusively to NAc, and a small subset that project to both regions4. A previous study also showed that NAc-projecting neurons are mainly located in vCA1v (see Fig. S3 in Okuyama, T., et al., Science, 2016)5. To estimate the percentage of dual-projecting vCA1 neurons targeting both NAc and vLS, we performed retrograde tracing by injecting CTB-555 into the NAc and CTB-488 into the vLS, and examined retrogradely labeled neurons in the vCA1. Our results showed that 10.95%± 1.19% of LS-projecting vCA1 neurons (green) also send projections to NAc, and 15.82%± 1.24% of NAc-projecting vCA1 neurons (red) also send projections to LS (Supplementary Fig. 21a-d, revised manuscript), suggesting that only a small amount of vCA1 neurons simultaneously project to both brain regions. These findings suggest that dual-projecting neurons make up only a minor fraction of the total projection population.\nThese results, combined with previous findings, suggest that two largely non-overlapping groups of single-projecting vCA1 neurons form the vCA1→LS and vCA1→NAc pathways, which function in parallel to regulate social memory acquisition and recall, respectively. This interpretation has been incorporated into the revised manuscript (Result section, lines 424-435).\nSupplementary Fig. 21a-d in the revised manuscript. CTB-tracing the vCA1 neurons projecting to both vLS and NAc.\n(a-d) CTB tracing showed limited overlap between vCA1 neurons projecting to the vLS and NAc. (a) Schematic of unilateral CTB-488 and CTB-555 injections into the vLS and NAc, respectively. (b) Representative coronal section showing injection sites. (c) Retrogradely labeled vCA1 neurons (CTB-488, green; CTB-555, red); right, magnified view of the boxed area. (d) Quantification of double-labeled neurons among CTB-555⁺ and CTB-488⁺ vCA1 neurons.\nReviewer #2 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.\nReviewer #3 (Remarks to the Author):\n(Remarks to the Author):\nIn this study, Zhang et al. investigated the role of two distinctive LS subpopulations- SST- and CB-expressing LS neurons- in bidirectional control of social memory acquisition. Using single nucleus RNA sequencing and immunostaining, they observed that SST- and CB-expressing LS neurons have molecularly and anatomically distinctive characteristics. The authors then demonstrated that each population positively and negatively regulates social memory acquisition, respectively. Optogenetic experiments further highlighted that this regulation is specifically engaged in social memory acquisition, but not social memory recall or sociability per se. Notably, SST LS neurons play a critical role in regulating socially relevant theta oscillations. At the circuit level, the dorsal and ventral LS (dLS, vLS) receive inputs from distinct parts of the hippocampus along its dorsal-ventral axis. Circuit-specific optogenetic manipulation revealed that vCA1d>dLS and vCA1v>vLS pathway can control social memory acquisition in a bidirectional way, similar to the effects observed after manipulating SST- and CB-expressing neurons, predominantly located in dorsal and ventral part of LS, respectively. The authors went one step further to demonstrate that the LHA and AHN are critical downstream targets of SST-and CB-expressing LS neurons to regulate social memory acquisition. Overall, this study provides valuable information into how specific neuronal circuits connecting the hippocampus to LS influence the social memory process. However, inconsistencies in data hinder in-dept interpretation, and generating superficial conclusions, primarily based on the results from artificial manipulation, is insufficient to support publication at this time. To further improve the paper, more clarifications listed below would be helpful.\nResponse: Thanks for your positive comments and insightful suggestions.\nHere are some specific comments:\n1. In Figure 1, snRNA seq results show that SST- and CB-expressing LS neurons display distinct molecular profiles with different expression levels for Nts, Glp1r, Htr2c and Prlr. Has this result been confirmed using other methods, such as in situ hybridization and immunohistochemistry?\nResponse: Thank you for your advice. To validate the snRNA-seq findings, we performed RNAscope in situ hybridization to assess the expression levels of Glp1r, Nts, Htr2c, and Prlr in LS neurons. We found that Glp1r expression was primarily localized to the dLS, with 65.69% ± 0.92% of all Sst+ neurons co-expressing Glp1r and 73.96% ± 0.63% of all Glp1r + neurons co-expressing Sst, suggesting a high overlapping between Sst and Glp1r (Supplementary Fig. 3a, revised manuscript). Additonally, 52.55% ± 2.40% of all Sst+ neurons co-expressed Nts and 64.42% ± 1.93% of all Nts + neurons co-expressing Sst, suggesting a moderate but specific overlap between Sst and Nts (Supplementary Fig. 3b, revised manuscript). In contrast, 70.52% ± 1.37% of all Calb1+ neurons co-expressed Htr2c and 63.88% ± 1.22% of all Htr2c+ neurons co-expressing Calb1, with minimal colabeling observed in Sst⁺ neurons (Supplementary Fig. 3c, revised manuscript). Similarly, 81.53% ± 3.50% of all Calb1+ neurons co-expressed Prlr and 72.99% ± 3.40% of all Prlr + neurons co-expressing Calb1, further supporting a specific overlap between Calb1 and Prlr (Supplementary Fig. 3d, revised manuscript).\nThese findings are consistent with the snRNA seq data, which indicated that SST+ neurons exhibit higher expression levels of Glp1r and Nts, whereas Htr2c and Prlr are more highly expressed in CB+ neurons. We have added these findings to the revised manuscript (Result section, lines 110-115).\nSupplementary Fig. 3 in the revised manuscript. Distinct molecular profiles of SST+ and CB+ neurons in the LS.\n(a) Left, representative coronal section showing high co-expression of Sst and Glp1r mRNA, predominantly localized in the dLS; Middle, quantification of percentage of double-labeled neurons among Sst+ or Glp1r+ neurons in the LS; Right, quantification of Glp1r+ neuron density across dLS, iLS, and vLS (n = 3).\n(b) Left, representative coronal section showing robust co-expression of Sst and Nts mRNA; Middle, quantification of Nts co-expression across Sst+ or Calb1+ neurons in the LS; Right, quantification of Nts+ neurons density in the dLS, iLS, and vLS (n = 3).\n(c) Left, representative coronal section showing high co-expression of Calb1 and Htr2c mRNA; Middle, quantification of Htr2c co-expression across Sst+ or Calb1+ neurons in the LS; Right, quantification of Htr2c+ neurons density in the dLS, iLS, and vLS (n = 3).\n(d) Left, representative coronal section showing high co-expression of Calb1 and Prlr mRNA; Middle, quantification of Prlr co-expression across Sst+ or Calb1+ neurons in the LS; Right, quantification of Prlr+ neuron density in the dLS, iLS, and vLS (n = 3).\n2. The author claimed that previous studies demonstrated the ‘controversial’ role of the LS in social behaviors (line #55, 139), but it is unclear what it meant by ‘controversial’ in this context. Given the heterogeneity of LS cell types, several studies have been descriptive, focusing on different populations of LS and highlighting their functional relevance on different domains of social behaviors. These studies do not necessarily appear to be inconsistent or in disagreement (controversial) with each other. Please clarify this point.\nResponse: Thank you for pointing this out. We acknowledge that our use of the term “controversial” was imprecise. We agree that the LS are organized into different molecularly defined clusters, which differentially regulate different domains of social behaviors depending on the context. Rather than being contradictory, these studies collectively highlight the functional heterogeneity of the LS. We have updated this notion with more precise wording in the revised manuscript (Result section, lines 60-61).\n3. Figure 3 shows that theta oscillation power is increased during both social bouts and non-social intervals. Is this LS theta oscillation still sustained even after the social stimuli are removed, or is it specifically engaged during the social context? The same question would be related to SST LS neurons: Is the proportion of theta phase-locked SST LS neurons unique to social contexts?\nResponse: Thank you for this thoughtful comment. To address whether LS theta oscillations are sustained beyond social engagement, we performed additional control experiments measuring LFPs and single-unit activity from SST+ neurons in the LS across three conditions: 10‑min social interaction, 20-min exploration of empty chamber, and 10-min exploration of a novel object (Supplementary Fig. 13a, revised manuscript). Our data show that theta power increased significantly during social interactions but returned to baseline levels after the social stimulus (i.e., the unfamiliar mouse) was removed (Supplementary Fig. 13b, revised manuscript). Notably, exposure to a novel object did not produce a similar increase in theta power, indicating that the effect is specific to social stimuli. In contrast, the proportion of theta phase-locked SST+ neurons remained elevated even after the theta power declined, suggesting that while theta oscillations are specifically enhanced during social engagement, the phase-locking of SST+ neurons may persist beyond the immediate social context (Supplementary Fig. 13c, revised manuscript).\nWe have added these findings to the revised manuscript (Result section, lines 251-257; Discussion section, lines 588-591).\nSupplementary Fig. 13 in the revised manuscript. Enhanced theta oscillations in the LS are specific to social contexts.\n(a-b) Theta power increased specifically during social interaction but not in non-social contexts. (a) Experimental timeline showing sequential LFP recording during social interaction (SI), empty context (EC), and object (OB) sessions.\n(b) Normalized theta power relative to baseline (BSL) across conditions. The SI session was divided into five 2-min bins to examine temporal dynamics. Theta power increased significantly during SI (2– 10 min) but not during EC or OB sessions (Friedman test: p < 0.0001; Dunn’s post-hoc—vs. baseline: 0-2 min, p = 0.3569; 2-4 min, p = 0.0005; 4-6 min, p = 0.0030; 6-8 min, p = 0.0042; 8-10 min, p = 0.0015; EC-1, p > 0.9999; EC-2, p > 0.9999; OB, p = 0.2861; n = 8).\n(c) Proportion of significantly phase-locked SST+ neurons during baseline, SI (0–5 min and 5–10 min), EC-1 (0-5 min), EC-2 (10-15 min), and OB sessions. The proportion remained elevated even after the theta power returned to baseline (vs. baseline: 0-5 min, p = 0.0016; 5-10 min, p < 0.0001; EC-1, p = 0.0005; EC-2, p = 0.0001; OB, p = 0.0005; 14 SST+ neurons from 8 SST-Cre mice).\nStatistics: Friedman test followed by Dunn’s post-hoc test (b), and Chi-squared test (c).\n4. What is the explanation for using continuous social interaction tests for 20 min in Figure 3, instead of separate sessions of sociability vs. social novelty, as used throughout the rest of the paper? Figure 3e shows consistent enhancement of theta rhythm oscillations between P1 and P4 with no statistical difference as the familiarity is developed. More evidence is needed to substantiate their claim, this is a key neural mechanism for social memory acquisitions (line #220).\nResponse: Thank you for raising this important point.\nIn Fig. 3, we employed a continuous 20-min social interaction session with a single social stimulus to capture the cumulative neural response to repeated exposure to the same conspecific, analogous to the sequential 10-min sociability and 10-min social novelty phases used elsewhere in the study. Because theta oscillation power is increased during both social bouts and non-social intervals (Fig. 3d-e). Therefore, we excluded S2 to enable more precise analysis of how neural activity evolves over time in response to one social stimulus. This rationale has been added to the revised manuscript (Result section, lines 230-232).\nTo determine whether the enhanced theta oscillations are specifically engaged by social context, we recorded LFP activity during a 10-min social interaction session (social context), followed by a 20-min session without social stimuli (empty context), and a 10-min novel object session (Supplementary Fig. 13a, revised manuscript). Theta power increased rapidly during the social session—beginning in the second 2-minute bin— and remained elevated throughout. In contrast, theta power remained at baseline during the empty context and object sessions (Supplementary Fig. 13b, revised manuscript). Our results suggest that enhanced theta oscillations are specific to social context, and it may represent a key neural mechanism for social memory acquisition.\nWe have included these new data and interpretations in the revised manuscript (Result section, lines 251-257; Discussion section, lines 588-591).\n5. What is the justification for the lack of changes in the power of theta rhythm oscillations in response to 20 Hz-ChR2 activation of SST LS neurons in Figure 3m?\nResponse: Thank you for this important question. Previous work has shown that activation of fast-spiking GABAergic neurons at a given frequency can enhance the LFP power at the corresponding frequency (e.g., 40 Hz stimulation increases 40 Hz power; Cardin et al., 2009, see Figure 3)6. This indicates that the stimulation frequency strongly influences the resulting network oscillations.\nTo directly test this in the LS, we expressed ChR2 in SST+ neurons and applied photostimulation across a wide frequency range (5 to 160 Hz; see Revision Fig. 1a). Compared to baseline, stimulation between 10–80 Hz increased the normalized LFP power within ±2 Hz of the stimulation frequency (Revision Fig. 1a). Specifically, 10 Hz stimulation enhanced oscillations in the theta range (8–12 Hz), whereas 20 Hz stimulation increased power in the 18–22 Hz band (Revision Fig. 1b-c). These results show that 20 Hz activation does not enhance theta power but instead drives oscillations closer to its own stimulation frequency. Thus, the lack of theta enhancement during 20 Hz stimulation in Fig. 3m is consistent with this frequency-specific effect and highlights that 10 Hz SST⁺ activation is particularly effective in promoting theta oscillations.\nRevision Fig. 1. Stimulation frequency determines the frequency of induced oscillations in the LS.\n(a) Normalized LFP power within ± 2 Hz of the stimulation frequency during light activation of SST⁺ neurons (5–160 Hz). The dashed line indicates baseline power (ratio = 1). Power increased at 10 Hz (p = 0.0013), 20 Hz (p = 0.0066), 40 Hz (p = 0.0036), 60 Hz (p = 0.0156), and 80 Hz (p = 0.0225), but not at 5 Hz (p = 0.6647), 120 Hz (p = 0.0701), or 160 Hz (p = 0.3591); n = 7. (b) 10 Hz stimulation selectively enhanced theta-band (8–12 Hz) power (one-way RM ANOVA: p = 0.0511; Holm–Sidak post hoc—vs. baseline: 10 Hz, p = 0.0471; 20 Hz, p = 0.6812; n = 7). (c) 20 Hz stimulation selectively enhanced 18–22 Hz oscillations, whereas 10 Hz stimulation did not (one-way RM ANOVA: p = 0.0006; Holm–Sidak post-hoc—vs. Baseline: 10 Hz, p = 0.0738; 20 Hz, p = 0.0003; n = 7).\nStatistics: two-tailed one-sample t-test (a), one-sample Wilcoxon signed rank test (a), one-way RM ANOVA followed by Holm–Sidak post-hoc test (b, c).\n6. In Figure 5, TeNT silencing is applied to the vCA1d>dLS pathway using intersectional viral strategies. Given the collateral projections of vCA1 neurons, it is important to clarify whether the vCA1d>dLS pathway is a key participant for blocking the enhanced theta oscillations during social interaction in Supplementary Fig.14.\nResponse: Thank you for your suggestion. To address the role of the vCA1d→dLS pathway in regulating theta oscillations during social interaction, we injected AAV-CamKⅡ-eArchT3.0-EGFP into the vCA1d of C57 mice, and implanted an LFP-recording optrode in the dLS to enable pathway-specific silencing during social behavior. Compared to baseline recordings without light stimulation, optogenetic inhibition of vCA1d→dLS pathway abolished the enhanced theta oscillations typically observed during social interaction (Supplementary Fig. 20e, revised manuscript). These results confirm that the vCA1d→dLS projection is necessary for the social interaction-driven increase in theta power.\nWe have incorporated these findings into the revised manuscript (Result section, lines 404-407).\nSupplementary Fig. 20e in the revised manuscript. Optogenetic silencing the vCA1d→dLS pathway blocks the enhanced theta oscillations during social interaction.\nLeft, schematic of AAV-mCaMKⅡ-eArchT3.0-EGFP injection into the vCA1d of C57 mice, followed by optrode and optical fiber implantation in the dLS; middle, representative coronal section showing optrode and optical fiber track in the dLS of C57 mouse (green, eArchT3.0-EGFP; blue, DAPI); Right, normalized theta power (groups, p = 0.0046; time, p = 0.0102; Holm–Sidak post-hoc—light-off (vs. baseline): P1: p = 0.0009; P2: p < 0.0001; P3: p < 0.0001; P4: p = 0.0009; light-on (vs. baseline): P1: p = 0.9812; P2: p = 0.9812; P3: p = 0.9812; P4: p = 0.7950; n = 5).\n7. In Figure 5d, it is unclear what numbers (0~100) on the X axis represent regarding the dorsal-ventral axis of vCA1.\nResponse: Thank you for highlighting this point. We have revised the Methods section to clarify this quantification approach. In Fig. 5d, the X-axis (0–100) represents the normalized position along the dorsal–ventral extent of the vCA1 pyramidal cell layer, where 0 corresponds to the most dorsal point and 100 to the most ventral point.\nTo quantify RV-labeled neuron distribution, we fitted a spline curve along the vCA1 pyramidal layer from dorsal to ventral ends. This curve was then divided into 100 equal bins, and the number of labeled neurons within each bin was quantified. Bin boundaries were defined orthogonally to the tangent of the spline at each point, ensuring accurate segmentation along the curved structure of vCA1.\nWe have incorporated this clarification into the revised manuscript (Methods section, lines 851–856).\n8. Supplementary Figure 6 shows that both SST- and CB-expressing LS neurons are activated by social stimuli, but this result is correlated with increased in vivo firing rate of SST LS neurons, but not with the one of CB LS neurons (Supplementary Fig. 7). Please discuss why.\nResponse: Thank you for this thoughtful comment. Ideally, c-fos staining and in vivo electrophysiology would provide consistent evidence of CB+ neuron activation. However, in vivo electrophysiology has inherent limitations, including low throughput and dependence on the precise location of optrode implantation. In our dataset, approximately 20% of recorded CB+ neurons showed increased firing rates during social interaction (now Supplementary Fig. 9h-i, revised manuscript), suggesting that at least a subset of CB+ neurons were activated under these conditions.\nImportantly, c-fos expression reflects cumulative, context-specific neuronal activation and can be induced by subthreshold depolarization, synaptic inputs, or intracellular signaling cascades, without requiring large changes in firing rate. Previous studies have shown that membrane depolarization, BDNF signaling, or cAMP/PKA activation can drive c-fos transcription7. Thus, CB⁺ neurons may express c-fos despite modest firing rate changes. We believe both technical constraints of electrophysiological sampling and the integrative nature of c-fos activation explain this apparent discrepancy.\nWe have incorporated this discussion into the revised manuscript (Discussion section, lines 572-576).\n9. Based on supplementary Fig. 9e, the authors claimed that inhibition of SST LS neurons did not produce rewarding or aversive effects, though there is a lack of interpretation for many data indicating reduced anxiety level after inhibiting SST LS neurons or SST dLS> LH circuitry in supplementary Fig. 8, 17. It is unclear to understand the situation that poor social memory and low anxiety are related to each other, given that high anxiety typically causes memory loss in real world situations.\nResponse: Thank you for this thoughtful comment. While anxiety disorders are commonly related to impaired social behaviors in individuals with autism spectrum disorders (ASD)8, reduced anxiety levels have also been reported in ASD models. For example, male Mef2cL35P⁺/⁻ mice, a validated ASD model, exhibit impaired social memory alongside reduced anxiety-like behavior in the elevated plus maze9. These findings suggest that impaired social memory and low anxiety can coexist as independent phenotypes, although reduced anxiety is less frequently recognized clinically because it is often not considered pathological by patients or clinicians.\nIn our study, inhibition of SST+ neurons decreased anxiety-like behavior in the elevated plus maze, evidenced by increased time spent in the open arms located 45 cm above the ground (Supplementary Fig. 10c–d, revised manuscript). In contrast, the same manipulation did not alter anxiety-like behavior in the open field test, which is performed at ground level (Supplementary Fig. 10a–b, revised manuscript). Because anxiety levels significantly increase with elevation10, we speculate that anxiety and social memory are largely regulated by independent mechanisms. This is supported by evidence that height-induced fear responses are primarily driven by visual cues11, whereas social behaviors in mice are primarily evoked by olfactory cues12. As the social memory test is also performed at ground level, we infer that SST⁺ neurons regulate social memory and anxiety-like behavior in a context-dependent and largely independent manner.\nWe have added this clarification to the revised manuscript (Discussion section, lines 547-553).\n10. The authors consistently claimed that SST LS and CB LS neuronal circuit exert ‘opposing’ effects on social memory, mainly based on results from artificial manipulation in Figures 2, 4 and 5. However, I’m unsure about the interpretation of ‘opposing role’, given that both SST- and CB-expressing LS neuronal populations are similarly activated by social stimuli (Supplementary Fig. 2). In addition, CB LS neuronal activity is not correlated with socially relevant theta oscillation (Supplementary Fig. 7), as well as frequency/amplitude of sEPSCs in CB LS neurons are not affected by social interaction (Figure 6), while SST LS neurons are largely engaged in both cases. Beyond the data from artificial manipulations, more physiological/endogenous evidence is needed to support the claim that SST LS and CB LS neuronal circuits oppose each other for regulating social memory acquisition.\nResponse: Thank you for this insightful comment. We agree that the term “opposing” requires careful interpretation, and we appreciate the opportunity to clarify our conclusions. In the revised manuscript, we have replaced “opposing role” with “bidirectional regulation” to better reflect our findings.\nOur data suggest that SST⁺ and CB⁺ LS neurons contribute to the bidirectional regulation of social memory acquisition through lateral inhibition. SST⁺ neurons are strongly engaged during social interaction, modulate theta oscillations (Fig. 3), and show potentiated excitatory input from the vCA1→SST⁺ dLS pathway (Fig. 6). In contrast, CB⁺ neurons did not exhibit similar modulation of theta oscillations or sEPSCs but appear to provide inhibitory feedback that constrains memory strength, maintaining homeostatic balance (Fig. 4).\nTo assess whether these reciprocal interactions occur in vivo, we employed opto-tagging to isolate single units of SST⁺ and CB⁺ neurons. We injected AAV-DIO-ArchT-tdTomato unilaterally into the LS of SST-Cre and CB-Cre mice, and conducted optrode recording (Supplementary Fig. 16a, b, revised manuscript). Spike waveform analysis revealed that SST+ neurons have longer trough-to-peak durations, wider half-width, and larger peak-trough ratios than CB+ neurons (Supplementary Fig. 16c, d, revised manuscript). Using these features, we identified putative CB⁺ (pCB⁺) neurons in SST-ArchT mice and putative SST⁺ (pSST⁺) neurons in CB-ArchT mice.\nIn head-fixed mice presented with an anesthetized stranger (Supplementary Fig. 16b, revised manuscript), we identified 15 pCB⁺ and 14 pSST⁺ neurons (Supplementary Fig. 16c, d, revised manuscript) in SST-ArchT and CB-ArchT mice, respectively. Silencing SST⁺ neurons significantly increased the firing rate of pCB⁺ neurons, especially during social stimulus presentation (12/15 neurons), suggesting SST⁺-mediated inhibition of CB⁺ neurons is dynamically enhanced during social interaction (Supplementary Fig. 16e–g, revised manuscript). Conversely, silencing CB⁺ neurons produced a modest, context-independent increase in pSST⁺ firing (Supplementary Fig. 16h–j, revised manuscript). Together, these findings support the existence of context-dependent, asymmetric lateral inhibition between SST⁺ and CB⁺ LS neurons, supporting their contrasting roles in social memory regulation.\nWe have incorporated these findings into the revised manuscript (Result section, lines 321-336).\nSupplementary Fig. 16 in the revised manuscript. SST+ and CB+ neurons exhibit mutual inhibition during social interaction.\n(a-d) SST+ and CB+ single units display distinct spike waveform features. (a) Schematic of AAV-DIO-ArchT-tdTomato injection into LS of SST-Cre or CB-Cre mice, followed by optrode implantation in the LS. (b) Setup for social stimulation and simultaneous in-vivo optrode recording: head-fixed mice on a running wheel interacting with an anesthetized stranger mouse. (c) Representative waveforms of opto-tagged SST+ and CB+ neurons. (d) Quantification of waveform properties from opto-tagged (solid dots: 54 SST+ neurons from 30 mice; 20 CB+ neurons from 11 mice) and putative SST+(pSST+) and CB+(pCB+) neurons (open dots: 14 pSST+ neurons from 9 mice; 15 pCB+ neurons from 8 mice).\n(e-g) SST⁺ neurons exert stronger inhibitory control over pCB+ neurons during social interaction. (e) Schematic of optogenetic silencing of SST⁺ neurons (532-nm laser, 3 s, 10 mW) during recording of pCB+ single units. (f) Z-score heatmaps of pCB⁺ neuron firing following SST⁺ silencing during baseline and social interaction. (g) Proportions of pCB+ neurons showing increased firing (Z-score > 2) or no change in (|Z-score| < 2) under baseline and social stimulus conditions. SST⁺ neurons suppressed pCB⁺ neuron activity more strongly during social interaction (p = 0.0099).\n(h-j) CB⁺ neurons exert stable inhibition of pSST⁺ neurons regardless of behavioral state. (h) Optogenetic silencing of CB⁺ neurons during pSST+ recordings. (i) Z-score heatmaps of pSST⁺ neuron firing during baseline and social stimulus conditions. The proportion of pSST⁺ neurons showing increased firing was similar across both conditions. (j) Proportions of pSST+ neurons showing increased firing (Z-score > 2) or no change in (|Z-score| < 2) under baseline and social stimulus conditions. CB⁺ neuron inhibition of SST⁺ neurons remained stable (p > 0.9999).\nStatistics: Chi-squared test (g, j).\n11. In Discussion, the authors claimed that the opposing effects of vCA1d>SST dLS>LHA and vCA1>CB vLS> AHA on social memory may be explained by the predominately GABAergic nature of AHN neuorns and the predominately glutamatergic nature of LHA neurons (line #532~534). What is the justification for this claim? Given previous studies suggesting that both AHN and LHA contain a decent amount of intermingled GABAergic and glutamatergic neurons, the authors need to provide more evidence in depth to support their explanation.\nResponse: Thank you for your insightful comment. To reveal the cellular composition of AHN and LHA, we conducted additional smFISH experiments against Gad1(GABAergic marker) and Slc17a6 (glutamatergic marker) mRNAs. These analyses revealed that Gad1⁺ GABAergic neurons are significantly more abundant in the AHN, whereas Slc17a6⁺ glutamatergic neurons predominate in the LHA (Supplementary Fig. 25, revised manuscript).\nWe have added these findings to the revised manuscript (Result section, lines 481-483; Discussion section, lines 617-620).\nSupplementary Fig. 25 in the revised manuscript. Distinct distribution of GABAergic and glutamatergic neurons in the AHN and LHA.\n(a-c) smFISH labeling of Gad1 (marker for GABAergic neurons) and Slc17a6 (marker for glutamatergic neurons) mRNAs in C57 mice. (a) Representative coronal section showing the distribution of Gad1+ and Slc17a6+ neurons in the AHN and LHA. (b) Magnified views of AHN and LHA region from panel (a). (c) Quantification of cell density reveals a higher density of Gad1⁺ neurons in the AHN (p = 0.0058) and a higher density of Slc17a6⁺ neurons in the LHA (p = 0.0257, n = 3 mice).\nStatistics: two-tailed paired Student’s t-test (c).\n12. There are some misplaced figure annotations throughout which should be corrected.\nResponse: Thank you for pointing this out. We have carefully reviewed all figures and corrected the misplaced annotations.\nReviewer #4 (Remarks to the Author):\nThe authors present an interesting and important data set exploring the contributions of somatostatin (Sst) and calbindin 1 (Calb1)-expressing cells in the lateral septum (LS) to social behavior. The authors used single-nucleus RNA sequencing (snRNAseq) and histological preparations to show that Sst and Calb1 are largely nonoverlapping in the LS. The authors then use a variety of circuit manipulations to show that inhibition of Sst cells reduces social discrimination when performed at least during training; discrimination is increased with their stimulation. Inhibition of Sst cells appears to reduce theta power, while their activation increases it. Conversely, Calb1 manipulations show opposite effects. This may be due to inhibition of Sst cells by Calb1 neurons, as seen in their slice preparations. Additionally, Sst and Calb1 cells appear to have differential input from the hippocampus, based on rabies tracing and ex vivo electrophysiology. Inhibition of inputs from CA1d to the dLS during training reduced social discrimination, whereas social discrimination was disrupted by activation of CA1v inputs to the vLS, mirroring what was seen with Sst/Calb1 manipulations. Generally, the paper is well-written, the topic is interesting, and the cells and circuits involved are likely to be of high interest to many readers. The authors should be commended for their extensive dataset. However, my enthusiasm is deeply hindered by a surface-level discussion and analysis of the sequencing (there is little comparison of their findings with others who have previously sequenced the LS; some prior works are not cited) and of their other circuit mapping and behavioral experiments (others have also explored functions of Sst cells in the LS and little is discussed of this prior work). I expand on these concerns below:\nResponse: Thanks for your positive comments and insightful suggestions.\nMAJOR ITEMS (in no particular order):\n---Theta power in the LS appears to similarly increase during both social and non-social events (Fig. 3). While it appears Sst neurons phase lock to theta, it’s unclear then how Sst activity encodes social events. Did the authors observe single-unit activity of Sst cells during social bouts? Do they correlate with behavior? The authors also suggest that sociability itself was unaffected by the circuit manipulations, but is exploration of S1 higher in Sst-ArchT vs. controls (Supp. Figure 9)?\nResponse: We greatly appreciate your valuable question. To better characterize the temporal dynamics of SST+ neuron activity in a more controllable social context, we trained the head-fixed test mice which were allowed to run freely on a running wheel13, and represented them with an anesthetized stranger or a novel object (Supplementary Fig. 9j, revised manuscript). Most SST+ neurons (63.64%, 14/22) increased firing in response to the anesthetized stranger, whereas a smaller fraction (18.18%, 4/22) responded to the novel object (Supplementary Fig. 9j-k, revised manuscript). These results indicate that SST⁺ neurons are preferentially activated during social interaction.\nWe have incorporated these findings into the revised manuscript (Result section, lines 170-175).\nRegarding sociability in the Supp. Figure 9 (now Supplementary Fig. 11c, revised manuscript), we analyzed the time spent exploring S1 during the initial sociability phase and found no significant difference between SST-ArchT and control mice (two-way RM ANOVA: interaction, F = 2.459, p = 0.1342), indicating that 1, 18 circuit manipulations did not alter baseline sociability.\nSupplementary Fig. 9j-m in the revised manuscript. SST⁺ neurons are preferentially activated during social interaction.\n(j-m) SST+ neurons were activated by social stimulus but not an object. (j) Behavioral setup for head-fixed optrode recordings while an anesthetized stranger or an object was presented. (k) Z-score heatmap showed that SST+ single units were activated by anesthetized stranger but not an object. (l) Averaged Z-score traces aligned to stimulus onset. (m) Normalized firing rates were higher in response to the anesthetized stranger compared to the object (p < 0.0001, 22 SST+ neurons from 9 mice).\nStatistics: two-tailed Wilcoxon signed rank test (m).\n---Related to the above, socially interacting mice may locomote more than a mouse in a familiar empty cage. Is there any concern that the data in Supplementary Figure 6 and Figure 6 reflect differences in locomotion, which may be independent of “social” experience per se? In other words, would a similar outcome occur if mice were wheel-running or given other novel stimuli?\nResponse: Thank you for this important comment. To address whether the synaptic changes observed in Supplementary Fig. 6 and Fig. 6 were driven by locomotion rather than social experience, we performed additional control experiments. Specifically, we recorded sEPSCs from SST⁺ dLS neurons in mice exposed to either a rotating (Running) or stationary (Control) rotarod (Supplementary Fig. 22a, revised manuscript). We observed no significant differences in sEPSC frequency or amplitude between these groups (Supplementary Fig. 22b–d, revised manuscript), indicating that locomotor activity alone does not account for the synaptic changes seen following social interaction.\nWe have incorporated these new results into the revised manuscript (Method section, lines 974-979; Result section, lines 459-463).\nSupplementary Fig. 22 in the revised manuscript. Excitatory inputs to SST+-dLS neurons are unaffected by rotarod running.\n(a) Experimental timeline. Mice performed rotarod running (8 rpm, 10 min) before slice physiology; controls remained on a stationary rod.\n(b-d) Rotated running did not alter sEPSC frequency or amplitude in SST+-dLS neurons. (b) Representative sEPSC traces from control and running groups. (c) Cumulative distribution of inter-event interval and summary graphs of sEPSC frequency (inset) (p = 0.7204; SST-Control, 29 SST+ neurons from 3 mice; SST-Running, 27 SST+ neurons from 3 mice). (d) Cumulative distribution of sEPSC amplitude and summary of sEPSC amplitude (inset) (p = 0.0660; SST-Control, 29 SST+ neurons from 3 mice; SST-Running, 27 SST+ neurons from 3 mice).\nStatistics: Kolmogorov-Smirnov test for cumulative distributions (c, d), and two-tailed Mann-Whitney test for averaged frequency and amplitude (c, d).\n---Others have explored the function of Sst cells in the LS including in the OFT and EPM. For example, Besnard et al. 2019 did not find changes in OFT/EPM with optogenetic inhibition of Sst cells in the LS, however the authors here observed more time in the open arms with TeNT inactivation. Conversely, Besnard et al. 2019 observed more in time in the open arms of EPM with optogenetic stimulation, which may be in conflict with what the authors show here. These differences are not discussed/addressed.\nResponse: Thank you for the insightful comment. We acknowledge that our findings differ from those reported by Besnard et al.201914, who reported that optogenetic inhibition of dLS SST⁺ neurons did not alter anxiety-like behavior in the EPM, while ChR2 activation of these neurons at 15 Hz increased open arm exploration in the EPM. Several methodological differences may explain these discrepancies.\nFirst, Besnard et al. used longer EPM open arms (67 × 7 cm) positioned 100 cm above the ground, whereas we used shorter open arms (35 × 6 cm) at a height of 45 cm. Arm height are known to modulate anxiety levels and behavioral responses, with higher arms inducing stronger anxiogenic effects10. This is consistent with the lower baseline open arm exploration observed by Besnard et al. (~10%) compared to our study (~20%), suggesting our EPM represents a lower-stress environment.\nSecond, their optogenetic protocol included a 15-minute EPM session with alternating 5-minute laser OFF-ON-OFF epochs (see Fig. 4f, 5f in Besnard et al., 2019). The initial OFF period may serve as an adaptation phase, potentially influencing behavior during subsequent laser-on epochs. In contrast, our EPM sessions lasted 5 minutes, similar to their first epoch, reducing potential confounds from adaptation or habituation.\nTaken together, differences in task design, environmental stress levels, and temporal structure likely underlie the divergent results.\nWe have added this clarification to the revised manuscript (Discussion section, lines 545-553).\n---It is unclear to me whether appropriate stats are used. For most of the memory recall tests, it appears the authors used one t-test for controls and a separate one for experimental groups (comparing S1 to S2), without reporting any sort of ANOVA/interaction that directly compares controls with experimental mice. The authors use t-tests for the discrimination ratio, but this ratio should mirror the interaction found in the investigation times. I suspect ANOVAs may yield significant interactions that would merit these comparisons (that should be followed by appropriate posthocs), but currently many of the statistics appear to lack rigor. Similarly, I am unsure why Figure 3e (and similar panels) makes use of multiple t-tests in the absence of an ANOVA.\nResponse: We thank the reviewer for this insightful comment regarding our statistical approach. In the revised manuscript, we have reanalyzed the data from all sociability and social novelty preference tests using two-way ANOVA followed by Holm–Sidak post hoc tests, to allow for direct comparison between groups and to account for interaction effects. Likewise, we have updated the analyses for Fig. 3e and all similar panels by applying two-way ANOVA, thereby ensuring a more rigorous and appropriate statistical evaluation throughout the manuscript.\n---This is not the first dataset to use snRNAseq to explore the diversity of LS cells. Surprisingly, the authors do not cite some of these prior works. This should be rectified. Moreover, very little effort is made to discuss how their data compare to these prior studies. Do the authors observe the same populations of cells in their dataset as others and in similar proportions? Why or why not?\nResponse: Thank you for pointing this out. We have now incorporated a comparison between our snRNA-seq dataset and the previously published septal snRNA-seq dataset from Zhu lab3. Reanalysis of their data revealed a similar distribution of neuronal clusters when visualized using UMAP (Revision Fig. 2a). Pearson correlation analysis confirmed strong correspondence between LS clusters across the two datasets (Revision Fig. 2b). For example, the Pax6⁺ n6 cluster in our dataset corresponds to the Pax6⁺ #10 cluster in their dataset (also see Figure 1D in Chen et al., Neuron 2024)3; the Calb1⁺/Crfr2⁺ n7 cluster corresponds to the Crhr2⁺ #8 cluster; the Drd2⁺ n8 cluster corresponds to the Drd2⁺ #9 cluster; the Calb1⁺/Pde1c⁺ n9 cluster corresponds to the Rai14⁺ #6 cluster; the Slc18a2⁺ n13 cluster corresponds to the Ntf3⁺ #1 cluster; and the Sst⁺/Nts⁺ n14 cluster corresponds to the Nts⁺ #5 cluster. For n10, n11, and n12, each of our clusters mapped to more than one cluster in the Zhu dataset (Revision Fig. 2c). Overall, our snRNA-seq results are highly consistent with those from Zhu lab.\nThe Zhu study used laser-capture microdissection to isolate a broader septal area that included both LS and medial septum (MS), identifying 15 neuronal clusters (Chen et al., 2024, their Figure 1c)3. This broader sampling likely explains why they reported more clusters than we did.\nWe have added this clarification to the revised manuscript (Results section, lines 101-103; Discussion section, lines 527-528).\nRevision Fig. 2. Comparison of our snRNA-seq data with Zhu lab’s snRNA-seq dataset.\n(a) UMAP plot showing the mapping between neurons from Zhu lab’s dataset and those from our dataset. Dots, individual neurons. Tangerine clusters, neuron populations in our data; cyan clusters, septal neurons in Zhu_lab's data. (b) Heatmap of Pearson correlation coefficients (PCC) between cell clusters from the two datasets, showing the degree of transcriptional similarity. (c) Correspondence of neuronal populations identified in Zhu lab’s dataset mapped onto our neuronal clusters, illustrating cross-dataset cell type relationships.\n---I find the designation of “non-LS” to certain clusters in the sequencing data to be a bold claim. The authors largely rely on in situ images from the Allen Brain to help establish whether cells may be “LS” or “non-LS”. This approach is limited as the in situ data may not capture the dynamic expression of these genes or may not have the resolution to account for sparse labeling in the septum (or low levels), or may be expressed in other parts of the septum that are simply not shown in the in situ images. It is entirely possible for putative LS cells to be found within clusters that the authors designate as “non-LS”, and this caveat or possibility is not addressed or discussed in the manuscript. For example, Coro6 is shown, and this appears to have fairly specific labeling in the MS, but there are clearly many cells shown in the tSNE that fall within cells kept for “LS”. Similar things may be said about Col6a1 or Nrn1/etc. The converse is also true: based on the same Allen Brain in situ images, Sst and Calb1 are also expressed in the medial septum, so it is unclear if cells kept in the “LS” clusters would include those. Reporting additional top genes for the clusters may help the reader better determine the potential for non-LS cells to be represented in the tSNE. Right now, the most important aspect of these data to me are Figure 1C, but this depends on the relative inclusion/exclusion of cells as discussed above.\nResponse: Thank you for this constructive comment. We agree that the designation of certain clusters as “non-LS” requires careful justification and acknowledgment of its limitations.\nFirst, we apologize for not providing sufficient detail on tissue preparation. In our study, 300‑µm coronal sections were prepared, and the LS was microdissected under a dissection microscope using fine angled knives and forceps (Supplementary Fig. 1a-b, revised manuscript). Anatomical boundaries were defined based on the Allen Brain Atlas to minimize contamination from adjacent regions, including MS, NAc, striatum, and corpus callosum. While we are confident that most MS and neighboring regions were excluded, we cannot entirely rule out minimal contamination.\nWe agree that gene expression boundaries in the septum are not perfectly discrete. For example, markers enriched in non-LS clusters (e.g., Coro6, Col6a1, Nrn1) show sparse expression in LS clusters, and conversely, LS markers (e.g., Sst, Calb1) appear at low levels outside the LS. Such overlap likely reflects both biological gradients and technical limitations of snRNA-seq, which detects a limited number of transcripts per cell and lacks spatial context.\nTo reduce potential misclassification, clusters were designated “non-LS” only when they expressed more than ten well-established markers for neighboring regions (e.g., MS, NAc). This led to the exclusion of clusters 1, 2, 3, 4, 5, 15, 16, and 17, which showed expression profiles consistent with non-LS cell types (e.g., neuroblasts, MS neurons, and NAc subtypes).\nIn response to your helpful suggestion, we have now included additional top-ranked marker genes such as Crym, Slc5a7, Lhx6, Adarb2, Bmp7, Syt6, Npy1r, and Rarb in the revised Supplementary Fig. 2, enabling readers to independently assess potential regional overlap. We have also revised the manuscript to explicitly discuss these limitations and caveats (Methods, lines 648-654; Discussion sections, lines 528-534).\nSupplementary Fig. 1a-b in the revised manuscript. Isolation of LS tissue and snRNA-seq workflow.\n(a) Flow chart of snRNA-seq pipeline. Left, LS tissue was dissected manually from 300-µm thick coronal sections; middle, single nuclei were barcoded; right, RNA-seq analyses.\n(b) In total, 21 023 single nuclei were clustered into 16 clusters using t-SNE. Dots, individual cells.\nSupplementary Fig. 2 in the revised manuscript. Non-LS neurons identified by unique molecular profiles.\n(a) Visualization of eight major non-LS clusters using t-SNE. Colored dots, non-LS neurons; gray dots, major GABAergic neurons in LS analyzed in Fig. 1a-c.\n(b) Dot plot showing expression patterns of cluster-enriched markers (x-axis) for eight non-LS clusters (y-axis). Cluster 1, neuroblast; Clusters 2–5, from the medial septal nucleus (MS); Clusters 15–17, from the nucleus accumbens (NAc).\n(c-e) Expression pattern of cluster-enriched markers for non-LS clusters in septum and surrounding brain regions. Top, molecular markers in non-LS clusters. Dots, individual cells. Bottom, in-situ hybridization (ISH) images showing mRNA distribution of marker genes in distinct cell. ISH images are courtesy of Allen Brain Atlas.\n---After excluding the “non-LS” cells in the tSNE, the authors then note what I assume are the top genes for each cluster. This strategy seems flawed to me because the clusters shown are formed relative to the expression of genes in the “non-LS” clusters when they were present. In other words, if the authors excluded the cells of the “non-LS” cells first then generated the tSNE (just as they did for transitioning from Supplemental 1 to Figure 1), do the authors think that the clustering for only “LS” cells would be similar? I suspect not, because these clusters already factor in the MS cells/etc.\nResponse: Thank you for this thoughtful suggestion. To address this concern, we performed additional re-clustering analyses on the snRNA-seq dataset after excluding cells identified as “non-LS” in Supplementary Fig. 2. We found that the overall clustering structure remained largely consistent (Revision Fig. 3), supporting the robustness of our classification strategy.\nSpecifically, correlation analyses comparing the original clusters (“original-clusters”) derived from the full dataset with those obtained after excluding “non-LS” cells (“LS-only-clusters”) revealed high concordance. Most LS neuronal clusters retained their original identities, with only minor adjustments: original clusters #7 and #8 merged into LS-only cluster n7, and original cluster #10 separated into LS-only clusters n5 and n6 (Revision Fig. 3). Importantly, the distinction between Sst⁺ and Calb1⁺ neuronal populations remained robust in the LS-only dataset, further supporting our central conclusion that these represent molecularly and functionally distinct LS subpopulations.\nRevision Fig. 3. Re-analysis of“LS-only neurons” confirms similar neuron clusters in the LS.\n(a-b) Original snRNA-seq analysis revealed nine neuronal subpopulations in the LS (#6-14). (a) t-SNE visualization of LS GABAergic neurons. Dots, individual neurons. Colored clusters, GABAergic neuronal clusters within LS; Gray clusters, non-LS clusters from nearby MS and NAc (Supplementary Fig. 2a-d). (b) Molecular characterization of the nine LS neuronal clusters. Left, nine subclasses with typical molecular markers listed; middle, two histograms showing number of nuclei and average detected genes for every cluster, respectively; right, dot plot showing gene expression patterns of cluster-enriched markers (x-axis) for individual cell types (y-axis). Size of dot indicates percentage of cells expressing indicated gene. Color indicates average expression level.\n(c-d) Re-clustering of all LS neurons (clusters #6–14) again identified nine distinct subpopulations (n1–n9).\n(c) t-SNE visualization of “LS-only neurons”, showing nine distinct clusters. (d) Molecular profiles of the nine re-clustered LS clusters, presented as in panel (b).\n(e) Correlation analysis shows strong correspondence between the original clustering and LS-only re-analysis, confirming the robustness of the clustering strategy. PCC, Pearson correlation coefficient.\n---Only in the methods do the authors note these data are acquired from male mice. It should be clearly stated in the title or abstract that all of the data were collected from male mice.\nResponse: Thank you for the helpful suggestion. We have now clearly stated in the Abstract that all experiments and analyses were conducted in male mice to avoid any ambiguity regarding the study design.\n---The authors state that the data shown only include animals with optical fibers above the target regions in the final analyses, but some of the current images make me uncertain about the accuracy of this (see Figure 5V). Similarly, it is unclear how much spread or specificity there may be in some of these injections/viruses. For example, there appears to be a lot of viral expression in the dorsal regions of the LS in CB-Cre mice. Are these terminals from ventral Calb1 cells? Are there more dorsally expressed Calb1 than is appreciated in the immunohistochemistry experiments? Also, several experiments use atlas schematics to represent the injections for the experiments, but no (or only partial) representative images are shown of injection sites. In Supplementary Figure 16e/h, there appears to be considerable expression of virus in regions above the POA, in what appears to be the BNST. The authors do not note the BNST in output terminals of the other figures. Are these from the LS? If not the LS, where are they from? My confidence may be bolstered by including more images of injections/placements (could be supplementary) and/or documenting viral spread/fiber placements. Perhaps the authors should note the number of exclusions based on hits/misses. Additionally, others have looked at outputs of Sst cells from the LS (Besnard et al. 2019), and there is no discussion of how their mapping compares (for example, no SUM is shown).\nResponse: We greatly appreciate your thoughtful questions regarding our results. We have conducted additional experiments or analysis to address these issues:\nFirst, we apologize for the misleading representative image displayed in Fig. 5v, which resulted from insufficient exposure of the green fluorescence signal during imaging. To address this, we have re‑captured the image using optimized exposure parameters, revealing clear ChR2 expression covering the vLS (highlighted in the red box in Revision Fig. 4). In addition, we also provide all the images from the remaining 12 mice in the ChR2-EGFP group, showing viral expression patterns and fiber placements related to Fig.5v. To avoid potential misinterpretation, we have replaced the original representative image with the 6th image in the first row, which more accurately reflects the data, in the revised Fig. 5v.\nRevision Fig. 4 (Related to Fig. 5v). Coronal brain sections showing ChR2-EGFP expression in the vCA1v→vLS pathway from 13 mice.\nThe original representative image shown in Fig. 5v is highlighted within the red box.\nSecond, we agree that representative images of injection sites and optical fiber placements are important for clarity and reproducibility. In the revised manuscript, we have added such images for the relevant experiments (Fig.4d; Supplementary Fig. 14a; Supplementary Fig. 20d; Supplementary Fig. 21e).\nTo further address concerns regarding viral targeting and fiber placements, we have provided additional images documenting viral spread and implant locations. Specifically, we included representative images from 10 mice in the ArchT group showing AAV-DIO-ArchT-tdTomato expression in the dLS of SST-Cre mice and fiber placements in the LHA of the same animals (related to Fig. 7d, Revision Fig. 5). These data confirm the accuracy of our viral targeting and fiber implantation across experiments.\nIn addition, we have added detailed information on the number of animals excluded due to off-target injections or misplaced fibers to the revised manuscript (Supplementary Table 3). We have incorporated this clarification into the revised manuscript (Methods section, lines 757–760).\nRevision Fig. 5 (Related to Fig. 7d). Coronal brain sections showing ArchT-tdTomato expression in the SST+-dLS→LHA pathway. (a-b) AAV-DIO-ArchT-tdTomato was injected into the dLS of SST-Cre mice, and optical fiber was implanted above ArchT-tdTomato+ axonal terminals in LHA (n = 10 mice).\nIn each panel, top image showing the ArchT expression in the dLS; bottom image showing optical fiber track above ArchT-tdTomato+ axonal terminals in LHA.\nThird, regarding the fluorescent signals observed in the dorsal LS (dLS) when manipulating CB⁺ neurons, we believe these signals primarily reflect axonal projections originating from CB⁺ neurons in the ventral LS (vLS), rather than somatic expression of CB⁺ neurons within the dLS itself. Our immunohistochemistry analysis consistently showed that CB⁺ somas are highly enriched in the posterior part of iLS/vLS, with only sparse neuronal presence in the dLS (Revision Fig. 6a; Fig. 1d–i).\nTo further clarify the source of these dorsal signals, we employed a sparse labeling approach based on the leaky expression of the tTA/TRE positive-feedback system15, which enables high-intensity, cell-type-specific fluorescent labeling of axonal projections. Specifically, we injected AAV-TRE-DIO-Flpo (titer: 5.57*109 v.g./ml, volume: 100 nL) and AAV-TRE-fDIO-GFP-tTA (titer:4.54*1012 v.g./ml, volume: 100 nL) into the vLS of CB-Cre mice (Revision Fig. 6b), without administering doxycycline. Under these conditions, sparse but robust labeling of CB⁺ neurons and their projections was achieved. Using this method, we found that even a small number of CB⁺ neurons (~30 neurons at AP +0.38 mm) in the vLS sent extensive axonal projections to the dLS (Revision Fig. 6c). Therefore, the prominent fluorescence observed in the dLS of CB-Cre mice largely reflects axonal innervation originating from ventral CB⁺ neurons, rather than indicating an underestimated population of CB⁺ somas within the dLS.\nRevision Fig. 6 (Related to Fig. 4). Fluorescence observed in the dLS of CB-Cre mice primarily reflects axonal input from vLS CB⁺ neurons.\n(a) RNAscope images showing Sst and Calb1 mRNA distribution in the LS, confirming the low density of CB⁺ neurons within the dLS. (b) Schematic of AAV-TRE-DIO-Flpo and AAV-TRE-fDIO-GFP-tTA injections into the vLS of CB-Cre mice for selective labeling the output of CB⁺ neurons. (c) Left, representative coronal section of the LS showing GFP (green) and DAPI (blue); Right, a small number of vLS CB⁺ neurons send extensive axonal projections to the dLS. Note that both sections were obtained from the same mouse at different AP positions.\nFourth, regarding the projection patterns of LS SST⁺ neurons, we appreciate the reviewer highlighting this point and apologize for not discussing these aspects in sufficient detail in the original manuscript. Specifically, we acknowledge that the fluorescence signals in the BNST region were initially underappreciated, in part due to the anatomical proximity between the BNST and POA, which complicated clear delineation during our initial analysis. Upon re-examination of the brain sections, we confirmed that both SST⁺ dLS neurons and CB⁺ vLS neurons send axonal projections to SuM (Supplementary Fig. 23a-d, revised manuscript), consistent with prior work by Besnard et al. (2019)14. Moreover, our tracing results align with Besnard et al.'s report in showing that SST⁺ dLS neurons project to LHA, BNST, and SuM, but not to the PVN (Supplementary Fig. 23a-d). We have now included a discussion comparing our findings with those of Besnard et al. (2019) in the revised manuscript (Discussion section, line 621) to better contextualize the projection patterns of LS SST⁺ neurons.\nIn addition to these major target regions, we re-analysed seveal weak fluorescence signals outputs incluing ZI, RCH, DMHa, TU, PMv, PMd (Supplementary Fig. 23a-d, revised manuscript). And we also observed very weak fluorescence signals in several other brain areas, including MEAad, and LHb (data not shown). However, the signal intensity in these regions was substantially lower compared to the primary projection targets shown in Supplementary Fig. 23c, and thus, they were not included in our quantitative analysis.\nSupplementary Fig. 23a-d in the revised manuscript. Anterograde tracing of SST+ dLS neurons and CB+ vLS neurons.\n(a-d) Anterograde tracing of SST+ and CB+ neurons in LS. (a) Representative coronal section showing EGFP-labeled SST⁺ neurons in the dLS (left) and EGFP⁺ axons in ipsilateral output regions (right). Scale bar, 100 μm. (b) Same as panel (a) for EGFP-labeled CB⁺ neurons in the vLS. (c) Quantification of axonal fluorescence signals in ipsilateral output regions, normalized to MS (AHN: p = 0.0190; NAc: p = 0.0341; SST-Cre: n = 5; CB-Cre: n = 5). (d) Schematic summary of SST⁺ and CB⁺ LS neuron output patterns.\nStatistics: two-tailed unpaired Student’s t-test (c), two-tailed unpaired Welch’s t-test (c).\nAbbreviations: MS, medial septal nucleus; NDB, diagonal band nucleus; POA, preoptic area; AHN, anterior hypothalamic nucleus; LHA, lateral hypothalamic area; SUM, supramammillary nucleus; BNST, bed nucleus of the stria terminalis; NAc, nucleus accumbens; PH, posterior hypothalamic nucleus; ZI, zona incerta; RCH, retrochiasmatic area; DMHa: dorsomedial hypothalamic nucleus, anterior part; TU: tuberal nucleus; PMv: ventral premammillary nucleus; PMd: dorsal premammillary nucleus.\n---The authors state: “The opposing effects of these pathways on social memory may be explained by the predominately GABAergic nature of AHN neuorns and the predominately glutamateric nature of LHA neurons.” GABAergic neurons are widely expressed within the LHA. Moreover, the inputs/outputs of the AHN vs. LHA may be quite distinct. There are many citations that could potentially be included here. I recommend a more thorough discussion here.\nResponse: We greatly appreciate your thoughtful suggestion. In the revised manuscript, we performed additional smFISH experiments targeting Gad1 (GABAergic marker) and Slc17a6 (glutamatergic marker) mRNAs to directly examine the cellular composition of the AHN and LHA. Our data confirmed that the AHN predominantly contains Gad1⁺ GABAergic neurons, whereas the LHA predominantly contains Slc17a6⁺ glutamatergic neurons, with significantly higher densities compared to the opposite neuronal subtype (Supplementary Fig. 25, revised manuscript). These findings have been incorporated into the revised manuscript (Result section, lines 481-483; Discussion section, lines 617-620).\nWe agree that the distinction between AHN and LHA extends beyond neurochemical identity to circuit organization. Previous studies have demonstrated that AHN GABAergic neurons and LHA glutamatergic neurons exhibit distinct input–output patterns—for example, AHN GABAergic neurons project to the VMH and POA16, while LHA glutamatergic neurons project to the VTA, lateral habenula (LHb), and the pedunculopontine nucleus (PPN)17. We have incorporated this discussion into the revised manuscript (Discussion section, lines 617-620).\nSupplementary Fig. 25 in the revised manuscript. Distinct distribution of GABAergic and glutamatergic neurons in the AHN and LHA.\n(a-c) smFISH labeling of Gad1 (marker for GABAergic neurons) and Slc17a6 (marker for glutamatergic neurons) mRNAs in C57 mice. (a) Representative coronal section showing the distribution of Gad1+ and Slc17a6+ neurons in the AHN and LHA. (b) Magnified views of AHN and LHA region from panel (a). (c) Quantification of cell density reveals a higher density of Gad1⁺ neurons in the AHN (p = 0.0058) and a higher density of Slc17a6⁺ neurons in the LHA (p = 0.0257, n = 3 mice).\nStatistics: two-tailed paired Student’s t-test (c).\n---Others have performed rabies tracing of Sst neurons of the LS (Besnard et al. 2019)—there is no discussion of how the authors’ findings compare with this work. This seems insufficient. Did the authors see the same inputs and at a similar level?\nResponse: Thank you for this valuable suggestion. Besnard et al. (2019)14 reported that SST⁺ neurons in the dLS receive monosynaptic inputs predominantly from dSub, MS/DBN, dCA3 and dCA1. In our study, we observed dense inputs to SST⁺-dLS neurons from dCA3, vCA3, and vCA1, with relatively little input from dCA1, which partially overlaps with but also differs from the inputs reported by Besnard et al (2019)11. These discrepancies may stem from differences in tracing methodology. Specifically, Besnard et al. utilized SST-Cre/TVA transgenic mice for their rabies tracing experiments, whereas we injected AAV-Syn-DIO-TVA-2A-RG-2A-mCherry into the dLS of SST-Cre mice followed by RV-ΔG-GFP delivery, with a 21-day interval between helper virus and rabies injections. Variations in genetic strategies, viral vectors, and experimental timelines could influence tracing efficiency, neuronal labeling patterns, or detection sensitivity.\nWe have incorporated this comparison into the revised manuscript (Discussion section, lines 606-608).\n---Do Calb1 neurons overlap with Esr1 neurons?\nResponse: Thank you for this important suggestion. We performed additional IHC staining against Calbindin 1 (CB) in the LS using Esr1-Cre/Ai14 mice to assess the potential overlap between CB⁺ and Esr1⁺ neurons. Our results revealed that approximately 12.01% ± 3.35% of all CB⁺ neurons co-expressed Esr1, while 27.53% ± 1.68% of Esr1⁺ neurons also expressed CB (Supplementary Fig. 6, revised manuscript). These findings indicate a partial, but largely non-overlapping relationship between CB⁺ and Esr1⁺ neuronal populations within the LS.\nThese findings have been incorporated into the revised manuscript (Results section, lines 132-137; Discussion section, lines 555-556).\nSupplementary Fig. 6 in the revised manuscript. Characterization of Esr1+ and CB+ neurons in the LS.\n(a) Representative images of anti-CB protein staining of Esr1-Ai14 mice in LS. (b) Quantification of the percentage of double labeled neurons (n = 3).\nMINOR ITEMS:\n---I believe the dissection of the LS for snRNAseq requires more details (rather than simply referring to a separate paper that sequenced a different structure). How much tissue was collected? Was an equivalent amount of tissue collected from each animal? The LS is a long, bilateral structure, how were the authors able to determine coverage or specificity to the LS?\nResponse: Thank you for this helpful suggestion. For each mouse, we collected four consecutive 300-µm coronal brain sections encompassing the LS (bregma +1.10 mm to −0.10 mm, Allen Brain Atlas). Dissections were performed under a stereomicroscope using a fine-angled dissecting knife (#10056-12, FST) and fine forceps, carefully avoiding adjacent regions such as the MS, NAc, striatum, and corpus callosum. The LS borders were defined using established anatomical landmarks, and all dissections were performed by the same experimenter to ensure comparable tissue amounts across animals. The collected region is illustrated in Supplementary Fig. 1a (highlighted in deep purple).\nThese details have been added to the revised manuscript (Methods section, lines 648-654).\n---It doesn’t bother me, as it is just a stylistic choice, but some of the legends are incredibly lengthy, perhaps they could be shortened by adding some of the information in the main text.\nResponse: Thank you for this helpful suggestion. In the previous version, we provided detailed figure legends to ensure clarity in presenting complex datasets. We agree, however, that some information is better placed in the main text. In the revised manuscript, we have shortened and simplified the figure legends (now ~500 words total) and relocated explanatory details to the main text, in line with the journal’s guidelines.\n---In general, the authors found the majority of their circuit manipulations to only have effects on social behavior when manipulated during training/encoding but not when manipulated at test. If the authors then added a new animal after the test, do they expect to eliminate secondary discrimination? If so, this may bolster the argument towards specificity to encoding.\nResponse: We thank for your valuable question. To further confirm that SST+ neurons are specifically required during social memory acquisition, we repeated this experiment with two rounds of acquisition and recall. We found that optogenetic silencing of SST+ neurons during the first acquisition disrupted the mouse’s ability to distinguish between stranger 1(S1) and stranger 2 (S2). This disruption also extended to the next round, impairing discrimination between stranger 3 (S3) and stranger 4 (S4) (Supplementary Fig. 12, revised manuscript). These results further support that SST+ neuron activity is essential for the acquisition—but not the recall—of social memory.\nWe have incorporated these findings into the revised manuscript (Results section, lines 209-214).\nSupplementary Fig. 12 in the revised manuscript. Two rounds of acquisition and recall assay confirm that SST+ neurons are required for social memory acquisition.\n(a) Experimental timeline showing optogenetic silencing during acquisition phase 1 (Acq1) and acquisition phase 2 (Acq2). The cylinder containing S1 or S3 was randomly placed in the left or right chamber at the start of each round.\n(b) Silencing SST+ neurons during Acq1 did not affect sociability: interaction time (interaction, p = 0.9137; Holm–Sidak post-hoc—Control: p = 0.0047, n = 7; SST-ArchT: p = 0.0036, n = 10) and social index (p = 0.8079).\n(c) Silencing during Acq1 disrupted the preference for the novel mouse: interaction time (interaction, p = 0.0044; Holm–Sidak post-hoc—Control: p = 0.0005, n = 7; SST-ArchT: p = 0.6585, n = 10) and social discrimination index (p = 0.0030).\n(d) Silencing during Acq2 did not affect sociability: interaction time (interaction, p = 0.5276; Holm–Sidak post-hoc—Control: p = 0.0176, n = 7; SST-ArchT: p = 0.0016, n = 10) and social index (p = 0.5241).\n(e) Silencing during Acq2 disrupted the preference for the novel mouse: interaction time (interaction, p = 0.0003; Holm–Sidak post-hoc—Control: p = 0.0007, n = 7; SST-ArchT: p = 0.0832, n = 10) and social discrimination index (p = 0.0003).\nStatistics: two-way RM ANOVA followed by Holm–Sidak post-hoc test for interaction time (b-e), two-tailed unpaired Student’s t-test for index (b, c, e), and two-tailed unpaired Welch's t-test (d).\n---I realize the authors report the number of cells, but can the authors report the number of mice from which the cells are derived in the slice electrophysiology experiments?\nResponse: Thank you for the helpful suggestion. In the revised manuscript, we have now included both the number of recorded cells and the number of animals from which the cells were derived in the corresponding figure legends for all slice electrophysiology experiments.\n---Have the authors tried using a reporter line (crossing CB-Cre with the reporter line) to match what was seen with the immunohistochemistry preparations?\nResponse: Thank you for your suggestion. We performed immunohistochemical (IHC) in the LS using CB-Cre/Ai14 mice, staining for CB in tdTomato-expressing CB+ neurons, which confirmed the high specificity of the CB-Cre line (Supplementary Fig. 4c, d, revised manuscript). Due to the temporary unavailability of CB-Cre/Ai14 mice in our lab, we proceeded with the current dataset. Together with IHC results in Fig. 1d-i, our results indicate that CB+ neurons are mainly localized in iLS/vLS.\n---Is there concern for ArchT being used in the terminal inhibition experiments? There is some evidence that sustained light activation of ArchT actually increases synaptic release at terminals: Mahn et al. 2016 Nature Neuroscience.\nResponse: Thank you for raising this important point. Mahn et al. (2016) reported that sustained yellow light (590 nm) illumination of ArchT-expressing axon terminals increased presynaptic calcium transients and synaptic release in cultured rat hippocampal neurons18. In our study, we used green light (532 nm), which is closer to the excitation peak of ArchT19, to silence either somata or axon terminals of ArchT-expressing neurons.\nTo directly assess potential effects on terminal release, we injected AAV-CaMKII-eArchT3.0-EGFP into the vCA1d of C57BL/6J mice. Five weeks later, we performed whole-cell patch-clamp recordings of dLS neurons in acute slices while electrically evoking EPSCs near EGFP+ vCA1d axon terminals. Continuous 532 nm illumination (5 min) significantly reduced evoked EPSC amplitudes, which fully recovered after light cessation, without significantly altering EPSC paired‑pulse ratios (PPRs) (Revision Fig. 7).\nThese results indicate that, under our experimental conditions, ArchT reliably suppresses synaptic transmission at vCA1d→dLS terminals and does not produce the paradoxical facilitation observed by Mahn et al.18, likely due to differences in wavelength (532 nm vs. 590 nm) and experimental preparations (acute slices vs. dissociated cultures).\nRevision Fig. 7. Terminal silencing of the vCA1d→dLS pathway reduces synaptic transmission but does not alter short-term plasticity. (a) Top, schematic showing bilateral injection of AAV-CaMKII-eArchT3.0-EGFP into the vCA1d of C57 mice. Bottom, schematic of whole-cell patch-clamp recordings from dLS neurons in acute slices. PTX was included in the bath to block GABAergic transmission. (b) Representative evoked EPSCs from a recorded dLS neuron before, during, and after 532 nm green light illumination targeting ArchT-expressing axon terminals. (c) Group summary showing that the amplitude of evoked EPSCs decreased during ArchT-mediated terminal silencing and recovered following laser off (one-way RM ANOVA: p = 0.0011; Holm–Sidak post-hoc test—Before laser vs. During laser: p = 0.0059; During laser vs. After laser: p = 0.0019; Before laser vs. After laser: p = 0.3387; 6 neurons from 3 mice). (d) PPRs of evoked EPSCs were not significantly affected by terminal silencing (one-way RM ANOVA: p = 0.4106; Holm–Sidak post-hoc test—Before laser vs. During laser: p = 0.9508; During laser vs. After laser: p = 0.5095; Before laser vs. After laser: p = 0.4898; 6 neurons from 3 mice).\nStatistical comparisons were performed using one-way RM ANOVA followed by Holm–Sidak post-hoc test (c, d).\n---There may be some typos in the text for which figure is being referred to.\nResponse: Thank you for pointing this out. We carefully reviewed the manuscript and corrected all figure reference typos to ensure consistency between the text and figures.\n---The authors state in the abstract: “While the hippocampus is crucial for social memory, the dynamic regulation of social memory, particularly the negative regulation, remains unclear.” I’m unsure what the authors mean by “negative” regulation, as this sounds like valence (especially since they do not see changes in RTRPP with Sst/CB). Can the authors clarify?\nResponse: Thank you for this insightful comment. Our intention was to emphasize the bidirectional regulation of social memory by SST+ and CB+ neurons, which exhibit mutual inhibitory interactions to fine-tune social memory strength and prevent excessively weak or overly robust memory formation. We agree that the term \"negative regulation\" may cause confusion, as it could be misinterpreted as referring to emotional valence. To avoid ambiguity, we have revised the abstract and relevant sections of the manuscript to replace \"negative regulation\" with more precise and neutral language describing this bidirectional control.\nReferences\n1. Meira, T., et al. A hippocampal circuit linking dorsal CA2 to ventral CA1 critical for social memory dynamics. Nature communications 9, 4163 (2018).\n2. Rashid, M., et al. A ventral hippocampal-lateral septum pathway regulates social novelty preference. (eLife Sciences Publications, Ltd, 2024).\n3. Chen, G., et al. Cellular and circuit architecture of the lateral septum for reward processing. Neuron (2024).\n4. Gergues, M.M., et al. Circuit and molecular architecture of a ventral hippocampal network. Nature neuroscience 23, 1444-1452 (2020).\n5. Okuyama, T., Kitamura, T., Roy, D.S., Itohara, S. & Tonegawa, S. Ventral CA1 neurons store social memory. Science 353, 1536-1541 (2016).\n6. Cardin, J.A., et al. Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature 459, 663-667 (2009).\n7. Joo, J.Y., Schaukowitch, K., Farbiak, L., Kilaru, G. & Kim, T.K. Stimulus-specific combinatorial functionality of neuronal c-fos enhancers. Nature neuroscience 19, 75-83 (2016).\n8. van Steensel, F.J., Bogels, S.M. & Perrin, S. Anxiety disorders in children and adolescents with autistic spectrum disorders: a meta-analysis. Clin Child Fam Psychol Rev 14, 302-317 (2011).\n9. Li, W.K., et al. Whole-brain in vivo base editing reverses behavioral changes in Mef2c-mutant mice. Nature neuroscience 27, 116-128 (2024).\n10. Huppert, D., Wuehr, M. & Brandt, T. Acrophobia and visual height intolerance: advances in epidemiology and mechanisms. J Neurol 267, 231-240 (2020).\n11. Shang, W., et al. A non-image-forming visual circuit mediates the innate fear of heights in male mice. Nature communications 15, 3746 (2024).\n12. Kaur, A.W., et al. Murine pheromone proteins constitute a context-dependent combinatorial code governing multiple social behaviors. Cell 157, 676-688 (2014).\n13. Yin, L., et al. VMHvll(Cckar) cells dynamically control female sexual behaviors over the reproductive cycle. Neuron 110, 3000-3017 e3008 (2022).\n14. Besnard, A., et al. Dorsolateral septum somatostatin interneurons gate mobility to calibrate context-specific behavioral fear responses. Nature neuroscience 22, 436-446 (2019).\n15. Lin, R., et al. Cell-type-specific and projection-specific brain-wide reconstruction of single neurons. Nat Methods 15, 1033-1036 (2018).\n16. Xie, Z., et al. Mechanically evoked defensive attack is controlled by GABAergic neurons in the anterior hypothalamic nucleus. Nature neuroscience 25, 72-85 (2022).\n17. Krauth, N., Sach, L.K., Sitzia, G., Clemmensen, C. & Kiehn, O. A hypothalamus-brainstem circuit governs the prioritization of safety over essential needs. Nature neuroscience 28, 1473-1485 (2025).\n18. Mahn, M., Prigge, M., Ron, S., Levy, R. & Yizhar, O. Biophysical constraints of optogenetic inhibition at presynaptic terminals. Nature neuroscience 19, 554-556 (2016).\n19. Mattis, J., et al. Principles for applying optogenetic tools derived from direct comparative analysis of microbial opsins. Nat Methods 9, 159-172 (2011)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have conducted additional experiments and have provided appropriate responses to all of my scientific concerns. The current version of the manuscript has reached a level of quality that is fully sufficient for publication. I believe this work advances our understanding of the neural mechanisms underlying social memory and will be highly appealing to a broad readership. I would like to commend the authors for their dedicated efforts.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "The authors have done a thorough job in addressing the reviewer’s comments. However, in Supplementary Fig. 25, while the authors describe distinct distributions of GABAergic and glutamatergic neurons in the hypothalamus, I remain concerned that these distributions are presented as mutually exclusive based solely on Gad1 and Slc17a6, and described in a binary manner. Numerous previous studies have demonstrated mixed populations of GABAergic and glutamatergic neurons, particularly in the lateral hypothalamus, as well established using a variety of markers. If the authors could revise the relevant text (lines 619–620) with careful consideration of these prior findings, I would be supportive of its publication in Nature Communications.", "reviewer_4": "Overall, and after careful review of the revised manuscript, I believe the authors have done a great job of addressing my primary concerns with their edits and new data. The study is much improved and represents a great addition to the field. I have no significant lingering concerns—I really only have one relatively minor item that I believe the authors should address as they finalize:\n(1) While this is a minor concern, I believe it is still necessary: again, as I mentioned in my first review, this is not the first study to perform single-cell sequencing of septal/LS tissue, and in fact, neither is the Chen et al. 2024 paper. Prior sequencing studies include: Turrero Garcia et al. 2021 eLife; Rodriguez et al. 2024 Translational Psychiatry. There are others (not all noted here) that have since come out that could also be cited (including human LS sequencing): Phillips et al. 2025 iScience; Xie et al. 2025 Nature Neuroscience. While the new data and comparison with Zhu’s group is very helpful, I believe not citing other prior single cell sequencing studies of the LS is still insufficient, especially if the goal is to build consensus on the genetic identity of cells in the LS. These other studies have also gone to great lengths to characterize LS populations.\nMinor note: This is just a very, very minor comment for the authors for the new Supp Figure 25: This may not require any edits to the manuscript (at most just the addition of a relevant citation for other GABAergic populations in the LHA), but Gad1 ISH may undersample the amount of GABA cells in the LHA (and this may depend on where you look in the LHA)—for example, there is wide expression of Vgat in the LHA (and moderately Gad2). My initial comment in my first review was only because I felt the authors’ first version understated the heterogeneity of these structures. The new text and in situ data are helpful.\nBeyond that, I commend the authors for their extensive study."}, "author_response": "We sincerely thank the reviewers for their insightful and constructive comments. With their valuable input, the clarity and overall quality of our manuscript have been greatly improved.\nPoint-to-point responses:\n(Reviewers’ comments in Blue; Our responses in Black)\nPS: All changes in the revised manuscript text file are highlighted with yellow.\nReviewer #1 (Remarks to the Author):-\nThe authors have conducted additional experiments and have provided appropriate responses to all of my scientific concerns. The current version of the manuscript has reached a level of quality that is fully sufficient for publication. I believe this work advances our understanding of the neural mechanisms underlying social memory and will be highly appealing to a broad readership. I would like to commend the authors for their dedicated efforts.\nResponse: We sincerely appreciate your positive comments and constructive suggestions, which are very helpful for us to improve our manuscript. We are also grateful for the recognition of our efforts.\nReviewer #2 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.\nResponse: Thanks for your positive comments and insightful suggestions.\nReviewer #3 (Remarks to the Author):\nThe authors have done a thorough job in addressing the reviewer’s comments. However, in Supplementary Fig. 25, while the authors describe distinct distributions of GABAergic and glutamatergic neurons in the hypothalamus, I remain concerned that these distributions are presented as mutually exclusive based solely on Gad1 and Slc17a6, and described in a binary manner. Numerous previous studies have demonstrated mixed populations of GABAergic and glutamatergic neurons, particularly in the lateral hypothalamus, as well established using a variety of markers. If the authors could revise the relevant text (lines 619–620) with careful consideration of these prior findings, I would be supportive of its publication in Nature Communications.\nResponse: Thank you for raising this important point. We apologize for the potentially misleading description in the previous revision. We fully agree that the expression of GABAergic and glutamatergic markers is not mutually exclusive in the AHN and LHA, consistent with previous studies showing mixed neuronal populations, particularly in the lateral hypothalamus.\nIn our study, classification of GABAergic and glutamatergic neurons was based primarily on Gad1 and Slc17a6 (VGLUT2) expression. We did not examine subpopulations expressing other markers such as vGAT, Gad2 or Slc17a7 (VGLUT1). Additionally, while we quantified the density of Gad1 and Slc17a6 neurons, we did not determine the percentage of GABAergic and glutamatergic neurons. We acknowledge that our analyses may underestimate the full diversity of neuronal subtypes and simplify the neuronal composition in these regions.\nWe have revised the relevant text to reflect this nuance and better incorporate prior findings (Discussion section, lines 624-631).\nReviewer #4 (Remarks to the Author):\nOverall, and after careful review of the revised manuscript, I believe the authors have done a great job of addressing my primary concerns with their edits and new data. The study is much improved and represents a great addition to the field. I have no significant lingering concerns—I really only have one relatively minor item that I believe the authors should address as they finalize:\n(1) While this is a minor concern, I believe it is still necessary: again, as I mentioned in my first review, this is not the first study to perform single-cell sequencing of septal/LS tissue, and in fact, neither is the Chen et al. 2024 paper. Prior sequencing studies include: Turrero Garcia et al. 2021 eLife; Rodriguez et al. 2024 Translational Psychiatry. There are others (not all noted here) that have since come out that could also be cited (including human LS sequencing): Phillips et al. 2025 iScience; Xie et al. 2025 Nature Neuroscience. While the new data and comparison with Zhu’s group is very helpful, I believe not citing other prior single cell sequencing studies of the LS is still insufficient, especially if the goal is to build consensus on the genetic identity of cells in the LS. These other studies have also gone to great lengths to characterize LS populations.\nResponse: Thank you for this constructive comment. We apologize for the insufficient discussion and citation of prior single-cell sequencing studies of the LS. In the revised manuscript, we have incorporated additional comparisons with previous reports:\n Clusters #6, #7, #10, and #13 correspond to Pax6, Crhr2, Rnf207, Slc18a2 expression in LS neuron types reported by Rodriguez et al. (Translational Psychiatry 2024).\n Clusters #6, #7, #14 correspond to Pax6, Crhr2, Sst expression in LS neuronal clusters identified by Simon et al. (Neuron 2025).\n Cluster #6 aligns with Wnt5a-expressing neurons reported by Xie et al. (Nature Neuroscience 2025).\n Cluster #14 corresponds to Nts-expressing neurons identified by Turrero Garcia et al. (eLife 2021).\n Clusters #10 and #14 correspond to MYO5B and Hs3st2 expression reported by Phillips et al. (iScience 2025).\nThese additions highlight both the overlap and distinctions between our dataset and previous studies, helping to build a consensus on the genetic identity of LS neurons. The revised text is included in the Results (lines 100–105) and Discussion (lines 530–536) sections.\nMinor note: This is just a very, very minor comment for the authors for the new Supp Figure 25: This may not require any edits to the manuscript (at most just the addition of a relevant citation for other GABAergic populations in the LHA), but Gad1 ISH may undersample the amount of GABA cells in the LHA (and this may depend on where you look in the LHA)—for example, there is wide expression of Vgat in the LHA (and moderately Gad2). My initial comment in my first review was only because I felt the authors’ first version understated the heterogeneity of these structures. The new text and in situ data are helpful.\nResponse: Thank you for this insightful comment.\nIn our study, classification of GABAergic and glutamatergic neurons was based primarily on Gad1 and Slc17a6 (VGLUT2) expression. We did not examine subpopulations expressing other markers such as vGAT, Gad2 or Slc17a7 (VGLUT1). Furthermore, while we quantified the density of Gad1 and Slc17a6 neurons, we did not determine the overall percentage of GABAergic and glutamatergic neurons. We acknowledge that our analyses may underestimate the full diversity of neuronal subtypes and simplify the neuronal composition in these regions. We have revised the relevant text to reflect this nuance and better incorporate prior findings (Discussion section, lines 624-631)\nBeyond that, I commend the authors for their extensive study.\nResponse: We sincerely appreciate your recognition and encouragement regarding our work."}]

Decision letter