The role of amygdala GABA neurons in controlling stress and reproduction in female mice

Domain: biology
Published: 2026-03-10
Editorial outcome: major_revision

Abstract
Stress can disrupt menstrual cycles, impair fertility and cause reproductive disfunction. The posterodorsal medial amygdala (MePD) integrates stress signals and regulates the gonadotropin-releasing hormone (GnRH) pulse generator through a dense network of GABA and Urocortin-3 (UCN3) neurons, yet the mechanisms underlying the circuitry remain poorly understood. Here, we combine in vivo mini-endoscopic calcium imaging, optogenetics, clustering analysis, and computational modeling to investigate the MePD circuitry in female mice. We uncover two anti-correlated GABA subpopulations in the MePD that are involved in the response to restraint stress and UCN3 neuron stimulation. Computational modeling suggests that mutual inhibition between these GABA groups drives their anti-correlated activity and predicts how these interactions shape downstream responses to stimulation of GABA and UCN3 neurons. In vivo optogenetics confirms that GABA neurons are critical for transmitting UCN3 signals to regulate luteinizing hormone (LH) pulse frequency. Together, our findings reveal amygdala GABAergic circuit mechanisms that mediate stress effects on reproductive health, linking emotional processing and neuroendocrine control.

Introduction
Successful reproduction requires normal function of a neural oscillator, the gonadotropin-releasing hormone (GnRH) pulse generator, that drives the pulsatile release of gonadotropic hormones, luteinizing hormone (LH) and follicle stimulating hormone (FSH) to control ovulation and spermatogenesis. This oscillator comprises Kisspeptin neurons co-expressing Neurokinin-B (NKB) and Dynorphin A (acronym KNDy) in the hypothalamic arcuate nucleus (ARC). The KNDy neural network not only provides the essential episodic stimulatory kisspeptin signal to the GnRH neurons, but receives diverse afferent inputs and hence is a hub for integrating various internal and external cues that regulate reproductive function1,2. Despite the marked heterogeneity of the myriad stressors, including acute versus chronic experimental stress paradigms, the common denominator is suppression of GnRH pulse generator frequency, which is associated with stress-related reproductive disorders and infertility3–8.

The amygdala, a part of the limbic brain typically associated with emotions and anxiety, has strong projections to the KNDy system1,2. The medial amygdala, and more specifically its posterodorsal subnucleus (MePD), has been shown to be a robust upstream regulator of GnRH pulse generator frequency9–11, pubertal timing12,13, sociosexual behavior14,15, anxiety14 and psychological stress-induced suppression of pulsatile LH secretion16,17.

In the MePD, the majority of neurons are GABAergic, accounting for a substantial portion of its projections, many of which target important hypothalamic centers involved in reproduction18–20, including the KNDy neurons and optogenetic stimulation of the latter suppresses LH pulsatility17. Moreover, chemogenetic inhibition of GABA neurons in the MePD can reverse the inhibitory effect of psychogenic stress on LH pulsatility17, suggesting an involvement of GABA signaling in the stress-induced suppression of pulsatile LH secretion. Although the precise way in which the MePD GABA neurons influence LH pulsatility is not fully understood, it has been suggested that they interact with the stress neuropeptide urocortin-3 (UCN3) neurons to modulate or reinforce stress-induced suppression of LH pulse frequency16.

UCN3, part of the corticotropin-releasing factor (CRF) superfamily and selective for CRF type 2 receptors (CRFR2)21, is highly expressed in the MePD16,22. Furthermore, UCN3 neurons in the MePD mediate psychosocial stress-induced suppression of the GnRH pulse generator and corticosterone secretion, thus playing a central role in the interaction between the reproductive and stress axes16,23. Previously we have shown that intra-MePD GABA antagonism can reverse UCN3-induced LH pulse suppression23, suggesting that GABA acts downstream of UCN3 signaling within the MePD. However, the local neural circuitry within the MePD mediating stress related information to the GnRH pulse generator remains to be established.

Here, we employed GRadient INdex (GRIN) lens mini-endoscopy to monitor and compare the calcium activity of GABA neurons at single-cell resolution under acute psychological stress or optogenetic stimulation of UCN3 neurons. Clustering analysis of the observed calcium transients uncovered two distinct GABA subpopulations exhibiting anti-correlated activity. To explore the functional role of these two subpopulations and unpick the mechanisms driving their anti-correlated activity, we build upon our previously developed MePD circuitry mathematical modeling framework11. Our modeling reveals that mutual inhibitory interactions between the GABA populations are sufficient to drive anti-correlated activity and predicts a complementary inhibitory effect of GABA and UCN3 signaling on the frequency of the GnRH pulse generator, which we tested by applying Cre/Flp recombinase intersectional strategies to selectively target and manipulate heterogeneous MePD neuronal populations17. Hence, by uncovering precise interactions between distinct subpopulations of MePD GABA neurons and UCN3 neurons in transmitting stress signals to the GnRH pulse generator, we provide critical and previously unknown insights into the neural circuitry driving stress-induced reproductive dysfunction. This discovery significantly advances our understanding of how emotional stress directly impacts reproductive health and identifies potential neural targets for therapeutic intervention in stress-related reproductive disorders.

Results
Dynamic reconfiguration of MePD GABA neuronal networks during selective optogenetic stimulation of urocortin-3 (UCN3) neurons and restraint stress

To investigate how the posterodorsal subnucleus of the medial amygdala (MePD) processes stress signals and to understand the role of GABA and UCN3 neurons in this process, we employed in vivo calcium imaging using GRadient INdex (GRIN) mini-endoscopy. A cohort of six female UCN3Cre::VGAT-Flpo transgenic mice were injected with a viral mixture containing pAAV-Syn-Flexrc[Chrimson-tdTomato] and pAAV-EF1a-fDIO-GCaMP6s. This intersectional viral strategy enabled dual functionality: (i) optogenetically stimulating MePD UCN3 neurons via Chrimson; and (ii) detecting calcium activity in MePD GABA neurons using GCaMP6s (Fig. 1A). GRIN lenses were surgically implanted at the same location as the viral injection, enabling imaging of calcium activity with single-neuron resolution Fig. 1B-G). The specificity of the AAV-Syn-Flex-rc[Chrimson-tdTomato] expression in the MePD was quantified by overlapping analysis with the UCN3 immunohistochemical staining and revealed that 95.06 ± 2.24% of tdTomato-positive neurons co-localized with the UCN3 immunohistochemical positive neurons (Supplementary Figure 1). Further, 81.61 ± 6.03% of the total UCN3-immunoreactive neurons co-expressed Chrimson-tdTomato (Supplementary Figure 1).

Two series of experiments were conducted to assess GABAergic responses under distinct conditions. To assess the role of UCN3 neurons in recruiting GABAergic response, baseline calcium activity from MePD GABA neurons was recorded for 3 min, followed by 3 min of recording during optogenetic stimulation of UCN3 neurons (Fig. 1A). Optogenetic stimulation was delivered in a discontinuous pattern, 5 seconds on, 5 seconds off, with a light-pulse frequency of 10 Hz during the ‘on’ periods (10ms pulse width, 10 mW power, and 532 nm wavelength). GABA neurons with activity that mimics the pattern of optic stimulation, evidence that they are co-expressing UCN3, are removed from further analysis (see Methods and Supplementary Figure 2). To further characterize the GABAergic response to acute stressors, baseline calcium activity of GABA neurons was recorded for 2 min, followed by 2 min of recording while the animals were exposed to restraint stress (Fig. 1A). The dynamic GABAergic response to optogenetic stimulation of UCN3 neurons and restraint stress was summarized in functional terms using pairwise (neuron-neuron) association matrices, constructed from Pearson correlation coefficients between neuronal trace pairs (see Methods). These correlation matrices represent the MePD GABAergic response as a graph of interconnected nodes (neurons) with edge weights corresponding to the strength of their pairwise functional interactions (Fig. 1H&I)24. To quantify the effect of stress or UCN3 activation on functional connectivity we calculated the normalized Riemannian distance between the correlation matrices from baseline and stimulation/stress periods. Our analysis revealed significant alterations in the functional connectivity of the GABAergic network during both UCN3 stimulation and stress relative to control animals lacking channelrhodopsin expression (Fig. 1J). Furthermore, on average, stress induces a significantly higher population time-averaged calcium response than UCN3 stimulation; however, this effect diminishes over the 2-minute stress period (Fig. 1K). These results indicate that the GABA population in the MePD plays a pivotal role in processing stress signals, such as those induced by restraint stress. Furthermore, our findings suggest that UCN3 neurons may serve as a key relay, driving functional reorganization within the GABAergic population to support transmission of stress-related information.

Clustering analysis reveals two functionally distinct GABA subpopulations in the MePD

To better understand the functional organization of the GABA MePD network during optogenetic stimulation of UCN3 neurons and under restraint stress, we performed clustering analysis on the functional connectivity matrices we obtained from the calcium recordings of GABA neurons. Clustering results consistently revealed two functionally distinct cell populations both during optogenetic stimulation of UCN3 neurons and restraint stress (Fig. 2A&C). Under both conditions, activity between the two clusters appeared highly anti-correlated as illustrated by two representative examples depicted in Fig. 2B&D. Moreover, we find that clusters are significantly different on a population level in size, with the smallest cluster accounting on average for 35% of all cells (Fig 2E&F, Supplementary Figure 3). The robustness of the above finding was also verified using the K-means clustering algorithm and an alternative measure of association between neuronal traces that accounts for time-lag and sign in neuronal interactions (see Methods and Supplementary Figs. 4-6).

Varying the frequency of optogenetic stimulation of UCN3 neurons influenced the functional connectivity within the GABA network (Supplementary Figure 7). Stimulation at 5 Hz produced no significant change compared with controls, 10 Hz resulted in a statistically significant increase, while 20 Hz reduced the effect, which could possibly reflect a differential release of neurotransmitters/neuropeptides at higher frequencies25. In contrast, stimulation at 5, 10, or 20 Hz did not significantly affect the correlation between the average activity of the two GABA clusters (Supplementary Figure 8). Based on the functional role of the MePD in relaying stress signals to the hypothalamic arcuate nucleus (ARC), our results suggest that the identified GABA subpopulations (clusters) could correspond to distinct populations of GABA interneurons and GABA efferent neurons—defined as neurons that transmit signals from the MePD to downstream targets. Known efferent projections to the ARC play a role in regulating the gonadotropin-releasing hormone (GnRH) pulse generator, a key driver of reproductive function11,17.

Mutually inhibitory interactions between GABA populations drive anti-correlated activity

To explore the network mechanisms driving the anti-correlated activity of the GABA subpopulations, we build upon our previously developed MePD circuit model11. The model allows us to explore interactions between MePD neuronal populations and understand emergent patterns of dynamical activity. Specifically, the model describes the calcium dynamics of two interacting populations of GABA neurons, corresponding to interneurons and efferent projection neurons. Efferent neurons project their axons outside the MePD to downstream targets such as the KNDy network. Both GABA populations interact with a glutamatergic population (Fig. 3A). Experimental evidence shows that antagonizing glutamate signaling completely blocks the suppressive effect of MePD UCN3 activation on LH pulsatility23, highlighting a functional role of glutamatergic neurons in the circuit. Therefore, the activity of the glutamatergic population is also included in the MePD model alongside the two GABA populations. Model equations are provided in Supplementary Information, and the parameter values for the MePD model are in Supplementary Table 3.

To incorporate input from UCN3 neurons we include a non-autonomous term in the model informed by recordings of the activity of UCN3 neurons during optogenetic stimulation (see Fig. 3A and Methods). The recorded traces exhibit a periodic pattern driven by the experimental stimulation protocol with 5 seconds on, 5 seconds off (see Methods). In the model, we approximated this UCN3 input using a constant drive along with a sinusoidal function with roughly 5 seconds on, 5 seconds off pattern, driving the populations GABA interneurons and the glutamatergic neurons. To simulate the anti-correlated activity between the two GABA neuronal subpopulations while also reproducing previously published results on the effects of neuropharmacological perturbations in the MePD on LH pulsatility23, we find that we need to include bi-directional (i.e. mutually inhibitory) GABA interaction in the circuit as well as GABA interneurons self-inhibition (Fig. 3A).

Next, we validate our model by simulating the effects of stress on the MePD circuit. UCN3 neurons in the MePD have also been shown to mediate psychosocial stress-induced suppression of the GnRH pulse generator16. Experimentally recorded calcium activity of UCN3 neurons during stress intervention is characterized by a fast rise followed by a slow decay (Fig. 3B), which we model by taking the difference between two exponential functions, with one fast and one slow time constant (see Methods). Using this input, our mathematical model confirms the emergence of anti-correlated behavior between the GABA subpopulation whereby the activity of GABA interneurons decreases over the stress period, while the activity of the GABA efferent neuron population increases (Fig. 3B), supporting the proposed MePD circuit structure (Fig. 3A).

In silico modeling reveals complementary relationship between MePD GABA and UCN3 populations

Having shown that the model of the MePD circuitry reproduces the observed anti-correlated dynamics, we next couple it to our network model of the KNDy population11,26. KNDy model details are in Supplementary Information, and the model parameter values can be found in Supplementary Table 4. Since KNDy neuronal activity serves as a well-established proxy for LH secretion, we use the dynamics of the KNDy network model to infer changes in LH pulsatility in response to MePD circuit manipulations. Our previous in silico findings11 show that MePD signal integration is predominately mediated by GABA projections. The effects of MePD GABA and glutamate antagonism alone and together with UCN3 stimulation on LH pulsatility have been previously investigated23, and we use these experimental findings to calibrate our coupled model parameters by reproducing these effects accordingly (see Supplementary Figure 9).

Next, using the calibrated model, we predict that providing a periodic excitatory input (see Supplementary Figure 10A), that mimics the effects of optogenetic stimulation of UCN3, leads to the increase in the KNDy inter-pulse interval (IPI) from 15.18 min to 23.97 min due to increased activity in the inhibitory GABAergic input to the KNDy network (Fig. 4A).

Since MePD has an overwhelming number of GABAergic outputs and interneurons, we are interested in their role in information processing of stress signaling. To this end we provide periodic excitatory input directly to both populations of GABA neurons (see Methods and Supplementary Information). This is different to the indirect activation through UCN3 stimulation, as it leads to the increased activity in both GABA subpopulations (Supplementary Figure 10B). The resulting effect on the KNDy IPI is an increase from 15.18 min to 42.65 min (Fig. 4B).

In the model we hypothesize that UCN3 signaling to the KNDy is operating through the GABAergic pathway, hence disrupting GABAergic interactions will suppress UCN3’s effects on KNDy. To investigate it we suppress the strength of the GABAergic interactions by 50% and mimic UCN3 stimulation by providing excitatory input to the circuit. The model shows that this intervention does not have a significant effect on KNDy IPI, apart from slightly increasing it from 15.18 min to 17.31 min (Fig. 4C & Supplementary Figure 10C).

Taken together the above could be summarized as the following set of model predictions along with suggested ways to test them experimentally:

• Optogenetic stimulation modelled via excitation of the MePD UCN3 increases the KNDy IPI 15.18 min to 23.97 min. This could be tested experimentally via in vivo optogenetic activation of the MePD UCN3 neuronal population and simultaneous measurement of LH pulsatility.

• Stimulation of the MePD GABA populations increases the KNDy IPI 15.18 min to 42.65 min. Such a substantial change underscores the critical role of GABAergic signaling in modulating KNDy pulsatility. Experimental confirmation could involve in vivo optogenetic activation of the entire MePD GABA population accompanied by LH pulsatility measurement.

• Stimulation of the MePD UCN3 with simultaneous suppression of the GABAergic interactions in the MePD does not significantly affect KNDy IPI, changing it from 15.18 min to 17.31 min. This finding suggests that UCN3 effects on the KNDy network are primarily dependent on its interactions with GABA populations. A strategy to verify this hypothesis experimentally could be to stimulate UCN3 non-GABA-expressing neurons in vivo while simultaneously inhibiting non-UCN3 GABA neurons and measure LH pulsatility.

• Finally, we investigate in silico the effects of stress on LH pulse dynamics mediated via the MePD. In the restraint-stress experiment it was shown that one GABA cluster was active, while the other one was inactive (Fig. 2D). By simulating these dynamics (Supplementary Figure 9D) in the coupled MePD - KNDy network model we are able to demonstrate that pulses in the KNDy network ceased (Fig. 4D). These modeling findings align with published experimental evidence indicating that restraint stress suppresses LH pulsatility16.

Selective optogenetic stimulation of UCN3 non-GABA neurons inhibits pulsatile LH secretion in female mice.

We now test experimentally our modeling predictions detailed in the previous section regarding the inhibitory effect of MePD UCN3 activation on LH pulsatility in vivo in freely behaving mice. To this end a cohort of UCN3-Cre::VGAT-Flpo transgenic female mice was injected with an AAV-nEF-Con/Foff 2.0-ChRmine-oScarlet viral construct. This intersectional approach enabled conditional expression of channelrhodopsin (ChRmine) in UCN3 neurons not expressing GABA (UCN3 non-GABA) (Con/Foff group). Following the viral injection, a unilateral fiber-optic cannula was implanted into the MePD, above the injection site, to facilitate selective activation of the targeted neuronal population. The specificity of the AAV-nEF-Con/Foff 2.0-ChRmine-oScarlet expression in the MePD was quantified by overlapping analysis with the UCN3 immunohistochemical staining and revealed that 98.92 ± 1.08% of the oScarlet-positive neurons co-localized with the UCN3 immunohistochemical positive neurons (Supplementary Figure 11). Further, 54.18 ± 5.04% of the total UCN3-positive neurons coexpressed ChRmine-oScarlet (Supplementary Figure 11).

The stimulation protocol consisted of a 60-min control period, followed by 60 min of optogenetic stimulation. Stimulation was delivered, as above, in a pulsed pattern (5 seconds on, 5 seconds off) with a pulse frequency of 10 Hz during the on period (10-ms pulse width, 10 mW power, 532 nm wavelength). Blood samples (5 µL) were collected every 5 min throughout the protocol and used to measure LH levels. Statistical analysis indicated post-stimulation LH inter-pulse intervals differed across the two groups (F(2, 15) = 19.51, p = 0.67*10-4, partial η² = 0.72; two-way ANOVA). In the Con/Foff group, the LH inter-pulse interval significantly increased after optogenetic stimulation compared to the control period (15.47 ± 0.91 min vs. 23.75 ± 1.07 min, mean ± SEM, n = 6, Mean difference (During−Before) = +8.28, t(5) = 6.19, adjusted p = 0.0016, Cohen’s dz = 2.53, 95% CI [4.84, 11.72] ; Fig. 5A&D), validating a prediction emerging from our model. In contrast, the no-stimulation group, which received the Con/Foff viral construct without optogenetic stimulation, showed no significant changes in LH inter-pulse interval (15.84 ± 0.37 min vs. 16.68 ± 0.86 min, n = 6, Mean difference (During−Before) = −0.84, t(5) = 0.76, adjusted p = 0.48, dz = 0.31, 95% CI [-2.02, 3.72]; Fig. 5B&D). Similarly, in a separate cohort of mice injected with a control virus (DIO-EYFP), optogenetic stimulation resulted in no significant differences in LH inter-pulse intervals before and after stimulation (19.02 ± 1.02 min vs. 17.78 ± 0.93 min, n = 6, Mean difference (During−Before) = +1.25, t(5) = -1.38, adjusted p = 0.23, dz = -0.56, 95% CI [-3.58, 1.08]; Fig. 5C&D). The LH pulse amplitude and mean LH levels were quantified, and data are provided in Supplementary Table 5.

Selective optogenetic stimulation of UCN3-expressing GABA neurons fails to affect pulsatile LH secretion in female mice.

To further test the functional interactions between the UCN3 and GABA populations, a separate cohort of UCN3-Cre::VGAT-Flpo transgenic female mice was injected with an AAV-nEF-Con/Fon 2.0ChRmine-oScarlet viral construct, which allows optogenetic stimulation of UCN3 neurons coexpressing GABA (UCN3-expressing GABA) (Con/Fon group). The specificity of the AAV-nEFCon/Fon 2.0-ChRmine-oScarlet expression in the MePD was quantified by overlapping analysis with the UCN3 immunohistochemical staining and revealed that 98.77 ± 1.24% of the oScarlet-positive neurons co-localized with the UCN3 immunohistochemical positive neurons co-expressing GABA (Supplementary Figure 12). Further, 32.73± 2.60% of the total UCN3-positive neurons co-expressed ChRmine-oScarlet (Supplementary Figure 12).

Statistical analysis showed no significant interaction effect of group and optogenetic stimulation on LH inter-pulse intervals (F (1, 9) = 0.29, p = 0.6, partial η² = 0.03; two-way ANOVA). That is, LH inter-pulse intervals in the Con/Fon group, showed no change following optogenetic stimulation compared to the control period (17.92 ± 0.80 min vs. 16.60 ± 0.88 min, mean ± SEM, n = 6, Mean difference (During−Before) = −1.32, t(5) = −0.83, adjusted p = 0.45, dz = −0.34, 95% CI [−5.40, 2.77]; Fig. 5H&J). Similarly, in the no-stimulation control experiment for this cohort, which did not receive optogenetic stimulation, there was no significant difference in LH inter-pulse intervals (16.08 ± 1.45 min vs. 15.83 ± 0.95 min, n = 5, Mean difference (During−Before) = −0.25, t(4) = −0.25, adjusted p = 0.82, dz = −0.11, 95% CI [−3.03, 2.53] ; Fig. 5I&J). The LH pulse amplitude and mean LH levels were quantified, and data are provided in Supplementary Table 5.

Taken together, our results suggest that although UCN3 and GABAergic neuronal populations overlap, they serve distinct functional roles within the MePD circuit, with both being critical for relaying inhibitory signals to the hypothalamic GnRH pulse generator. While independent activation of either population inhibits the GnRH pulse generator, activation of UCN3 neurons that co-express GABA is insufficient to elicit this effect.

The MePD GABA neurons relay information from UCN3 neurons and inhibit the GnRH pulse generator.

To test our remaining model predictions and establish the functional role of GABA neurons in the MePD in transmitting inhibitory signals to the hypothalamic GnRH pulse generator, we injected the AAV-EF1a-DIO-ChR2-EYFP viral construct into VGAT-Cre transgenic mice, targeting the entire MePD GABA neuron population for expressing ChR2 and used the optogenetic stimulation protocol described above (60 min control period followed by 60 min stimulation ) to stimulate the entire MePD GABA population. In the VGAT-Cre-tdtomato mice, we observed that 93.27 ± 2.99% of the EYFP positive neurons were tdtomato-positive and 87.01± 5.21% of the tdTomato-positive neurons were EYFP-positive. This indicates a high degree of co-expression consistency between the viral and transgenic reporters. Statistical analysis showed a significant interaction effect of our genetic intervention and stimulation period on LH pulsatility (F (2, 12) = 9.68, p = 0.003, partial η² = 0.62; two-way ANOVA). Stimulation of the GABA population markedly increased the LH inter-pulse interval compared to the pre-stimulation control period (18.5 ± 2.03 min vs 49.5 ± 8.46 min, mean ± SEM, n = 5, mean difference (During−Before) = 31; t(4) = 3.51, adjusted p = 0.025, dz = 1.57, 95% CI [6.50, 55.50] ; Tukey’s post-hoc; Fig. 6A&D), validating modeling prediction 2. In contrast, mice that did not receive optogenetic stimulation showed no change in LH inter-pulse interval (21.25 ± 3.79 min vs 19.33 ± 1.52 min, n = 5, mean difference (During−Before) = -1.92; t(4) = -0.40, adjusted p = 0.71, dz = -0.18, 95% CI [-15.22, 11.38] ; Tukey’s post-hoc; Fig. 6B&D). Similarly, control virus (AAV-EF1a-DIO-EYFP) injections did not result in any significant difference in LH inter-pulse interval before and during stimulation (16.50 ± 0.67 min vs 18.00 ± 0.62 min, n = 5, mean difference (After−Before) = 1.50; t(4) = 1.77, adjusted p = 0.15, dz = 0.79, 95% CI [-0.85, 3.85]; Tukey’s post-hoc; Fig. 6C&D). The LH pulse amplitude and mean LH levels were quantified, and data are provided in Supplementary Table 6.

Next, UCN3-Cre::VGAT-Flpo transgenic females were injected with an intersectional viral mixture containing AAV-nEF-Con/Foff 2.0-ChRmine-oScarlet and pAAV-nEF-Coff/Fon-NpHR3.3-EYFP , enabling simultaneous excitation of UCN3 non-GABA neurons and inhibition of non-UCN3 GABA neurons. Statistical analysis showed no significant interaction effect of genetic manipulation and stimulation period on LH pulsatility (F (1,9) = 0.11, p = 0.75, partial η² = 0.01; one-way ANOVA). Moreover, optogenetic stimulation resulted in no significant change in the LH inter-pulse interval relative to the control period (16.67 ± 1.31 min vs 18.61 ± 1.58 min, mean ± SEM, n = 6, mean difference (After−Before) = 1.95; t(5) = 0.88, adjusted p = 0.42, dz = 0.36, 95% CI [-3.77, 7.66] ; Fig. 6H&J), which aligns with our modeling prediction 3. Similarly, in mice injected with the same viral mixture but without receiving optogenetic stimulation, no significant change in LH inter-pulse interval was detected (16.33 ± 1.19 min vs 17.33 ± 0.81 min, n = 5, mean difference (After−Before) = 1; t(4) = 0.61, adjusted p = 0.57, dz = 0.27, 95% CI [-3.55, 5.55] ; Fig. 6I&J). The LH pulse amplitude and mean LH levels were quantified, and data are provided in Supplementary Table 5.

Collectively, these findings suggest that MePD GABA neurons are integral to regulating LH pulse frequency. The inhibitory effect on LH pulses observed upon UCN3 neuron activation is attenuated when GABA neuron activity is optogenetically suppressed, implying that GABA signaling acts downstream of UCN3 neurons, relaying the inhibitory signal to the hypothalamic GnRH pulse generator.

Methods
Animal

VGAT-Cre-tdTomato mice were generated by crossbreeding Vgat-cre homozygous mice (Jax stock #028862, B6J.129S6(FVB)-Slc32a1tm2(cre)lowl/MwarJ; Jackson Laboratory, Bar Harbor, ME, USA) with adult homozygous tdTomato mice (Jax stock #007909, B6.Cg-Gt(ROSA)26Sortm9(CAGtdTomato)Hze/J, Jackson Laboratory). VGAT-Cre-tdTomato mice were genotyped using PCR to determine heterozygosity for VGAT-Cre (primers 5′-3′: common, 12785—CTTCGTCATCGGCGGCATCTG, Sigma-Aldrich; wild-type reverse 12786—CAGGGCGATGTGGAATAGAAA, Sigma-Aldrich; mutant reverse oIMR8292—CCAAAAGACGGCAATATGGT, Sigma-Aldrich) and tdtomato (primers 5′-3′: wild-type forward oIMR9020—AAGGGAGCTGCAGTGGAGTA, Sigma-Aldrich; wild-type reverse oIMR9021—CCGAAAATCTGTGGGAAGTC, Sigma-Aldrich; mutant reverse WPRE oIMR9103—GGCATTAAAGCAGCGTATCC, Sigma-Aldrich; mutant forward tdTomato oIMR9105—CTGTTCCTGTACGGCATGG, Sigma-Aldrich). UCN3-Cre heterozygous mice (strain Tg(Ucn3-cre)KF43Gsat/ Mmucd, MMRRC GENSAT) were crossbred with VGAT-Flpo heterozygous mice (Jax stock #007909,B6.Cg-Slc32a1 2A-Flpo-D:Het) to obtain female double heterozygous UCN3-Cre::VGATFlpo mice (Slc32a1 2A-Flpo-D:Het|Ucn3-Cre:Het|Rosa26<tomato>WT); genotyped using PCR for the detection of heterozygosity (primers 5′- 3′: UCN3 Forward: CGAAGTCCCTCTCACACCTGGTT, Sigma-Aldrich; Cre Reverse: CGGCAAACGGAC-AGAAGCATT, Sigma-Aldrich; Slc32a1 Mutant Forward: TGC ATC GCA TTG TCT GAG TAG, Sigma-Aldrich; Slc32a1 Mutant Reverse: GAC AGC CGT GAA CAG AAG G, Sigma-Aldrich). Female mice, aged 8 to 10 weeks, weighing between 20 g and 25 g, were individually housed in ventilated cages sealed with a HEPA-filter at 25 ± 1°C, relative humidity at 55% ± 10%, in a 12:12-hour light/dark cycle, lights on at 07:00 h. Vaginal smears were performed when mice are 6 weeks old between 10:00 - 12:00 h daily. Only mice showing regular estrous cycles were included. All animal procedures performed were approved by the King’s College London Animal Welfare and Ethical Review Body. Procedures were in accordance with UK Home Office regulations, under Project Licence Number PP4067293. Sex was not considered in the study, and only ovariectomized mice were used for controlling the variables of the experiments.

Stereotaxic injection of adeno-associated virus construct and fiber-optic or mini-endoscope GRIN lens implantation

All surgical procedures were carried out under general anesthesia using ketamine (Vetalar, 100 mg/kg, i.p.; Pfizer, Sandwich, UK) and xylazine (Rompun, 10 mg/kg, i.p.; Bayer, Leverkusen, Germany) under aseptic conditions. Animals were secured in a David Kopf stereotaxic frame (Model 900, Kopf Instruments, CA, USA). Following bilateral ovariectomy, a midline incision was made in the scalp to reveal the skull. Two small bone screws were inserted into the skull. A small hole was drilled above the position of the MePD. The MePD coordinate (2.29 mm lateral, 1.60 mm posterior from bregma, at a depth of 5.33 mm below the skull surface) was determined according to the mouse brain atlas of Paxinos and Franklin33. A unilateral stereotaxic viral injection was performed to target opsin or fluorescent protein expression in the MePD neurons, using a robot stereotaxic system (Neurostar, Tubingen, Germany), with a 5-μL Hamilton microsyringe (Esslab, Essex, UK), at the speed of 25 nl/min for 10 min.

Two transgenic animal models were used for LH blood sampling under optogenetic stimulation: UCN3Cre::VGAT-Flpo and VGAT-Cre-tdTomato. The following types of viral constructs were used in separated cohorts of UCN3-Cre::VGAT-Flpo mice: (i) AAV-nEF-Con/Foff 2.0-ChRmine-oScarlet (250 nl, 2.1×1012 gc/mL, Serotype:8, #137161, Addgene, Massachusetts, USA); (ii) AAV-nEF-Con/Fon 2.0ChRmine-oScarlet (250 nl, 1.9×1012 gc/mL, Serotype:8, # 137159, Addgene, Massachusetts, USA); (iii) a mixture of AAV-nEF-Con/Foff 2.0-ChRmine-oScarlet (2.1×1012 gc/mL, #137161) and pAAV-nEF-Coff/Fon-NpHR3.3-EYFP (1.9×1012 gc/mL; #137159, final volume 300 nl); (iv) control virus AAV-Ef1a-DIO-EYFP (250 nl, 4.4 × 1012 gc/mL, Serotype:9, #27056, Addgene, Massachusetts, USA). VGATCre-tdTomato mice received unilateral injections of (i) channelrhodopsin (ChR2) viral construct, (250 nl, 1.8 × 1012 gc/mL; Serotype:9; Addgene, #20298, Massachusetts, USA) or (ii) control virus, AAVEf1a-DIO-EYFP (250 nl, 4.4 × 1012 gc/mL, Serotype:9; Addgene, # 27056, Massachusetts, USA) into the MePD. All adeno-associated virus constructs used in this study were purchased as ready-to-use viral particles from Addgene (Massachusetts, USA). No in-house plasmid packaging was used.

Following injection, the needle was kept in position for 10 min before going up slowly over 1 min. A unilateral fiber optic cannula (200 µm, 0.39 NA, 1.25 mm ceramic ferrule; Doric Lenses, Quebec, Canada) was inserted into the right MePD 0.15 mm above the injection site. After reaching the target, the fiber optic cannula was secured on the skull using dental cement (Super-Bond Universal Kit, Prestige Dental, UK), bonded to the screws and skull. Finally, the incision in the scalp was closed with suture. Animals were given 1 week to recover, after which they were handled 20 min daily to acclimate to experimental procedures for a further 2 weeks.

For mini-endoscope in vivo calcium imaging, only UCN3-Cre::VGAT-Flpo transgenic animals were used. Separate mice cohorts received the following viral injection into the MePD: (i) a mixture of pAAV-Syn-Flex-rc[Chrimson-tdTomato] (2.0×1012 gc/mL, Serotype:5, #62723, Addgene, Massachusetts, USA) + pAAV-EF1a-fDIO-GCaMP6s (2.3×1012 gc/mL; Serotype:8; #105715, Addgene, Massachusetts, USA; final volume 400 nl); (ii) a mixture of pAAV-Syn-Flex-rc[ChrimsontdTomato] (2.0×1012 gc/mL, Serotype:5, #62723, Addgene, Massachusetts, USA) + pAAV.CAG.Flex.GCaMP6s.WPRE.SV40 (4.3×1012 gc/mL; Serotype:9; # 100842, Addgene, Massachusetts, USA; final volume 400 nL); (iii) a mixture of control virus pAAV-hSyn-DIO-mCherry (2.3×1012 gc/mL, Serotype:9, #504S59) + pAAV-EF1a-fDIO-GCaMP6s (2.3×1012 gc/mL, Serotype:8, #105715, final volume 400nl) . One week after administering the virus, a 600-µm diameter, 7.2-mm long gradient index (GRIN) ProView™ Integrated Lens (Inscopix, PN:100-004554) was implanted at the same location as the viral injection. The surface of the skull was scored, using the tip of a surgical scalpel, and four screws were inserted into the skull. This was done to enhance the adhesion of dental cement to the skull, thereby reducing the interference of movement on in vivo recording. Before insertion of the GRIN lens, a 23 G needle was slowly lowered at a speed of 5.0 mm/min into the brain (2.42 mm lateral, 1.52 mm posterior from bregma, depth of 5.05 mm below the skull surface) to make a needle track to facilitate the insertion of the GRIN lens without causing brain distortion along its route. The GRIN lens was then inserted into the brain at a rate of 0.6 mm/min, using the same coordinates as the needle precutting. To secure the GRIN lens with integrated baseplate in position, we used a light curing adhesive (iBond Universal, Kulzer GmbH, Leipziger, Germany) along with a cured radiopaque hybrid dental cement (Gradia Direct Flo, GC corporation, Tokyo, Japan), bonding it to the head screws and skull. A GRIN lens baseplate dust cover (Inscopix) was rescued in place to protect the lens. After 4 weeks the mice were re-anaesthetized as described above and underwent bilateral ovariectomy.

Serial blood sampling for LH measurement

The mouse’s tail-tip was excised using a sterile scalpel. Then the chronically unilaterally implanted fiber optic cannula was connected to a multimode fiber optic rotary joint patch cables (Thorlabs Ltd, Ely, UK) via a ceramic mating sleeve to allow the animal freedom of movement. Mice were left for 1 h to habituate. A Grass SD9B stimulator-controlled DPSS laser (Laserglow Technologies, Toronto, Canada) was utilized to deliver either green light (532 nm wavelength, 10 Hz, 5 seconds on 5 seconds off, 10 mW, 10-ms pulse width,) or blue light (473 nm wavelength, 5 Hz, 5 seconds on 5 seconds off, 5 mW, 10-ms pulse width,). The light pattern was controlled using software designed in house. After 1 h of acclimatization, serial blood samples (5 µL) for LH pulse measurement were collected every 5 min for 2 h between 10:00 - 12:00 h: 0-60 min for control blood sampling period, and 60-120 min under stimulation or equivalent no-stimulation control period. Blood samples were diluted in 45 μL of Phosphate-Buffered Saline (PBS) containing 0.2% Bovine Serum Albumin (BSA) and 0.05% Tween20 (PBST) and immediately placed on dry ice and stored at −80°C until later analysis.

LH assay

LH measurement was performed using an LH ELISA assay as reported previously34. A mouse LH standard (mLH; AFP-5306A, NIDDK-NHPP, USA) was used to establish a standard curve for the quantitative measurement. The following antibodies were used in the assay: (i) coating antibody (RRID: AB_2665514, monoclonal antibovine LH beta subunit antiserum, 518B7, University of California, CA, USA; Lot No. 13; dilution 1:10,000); (ii) anti-LH antibody (polyclonal rabbit LH antiserum, AFP240580Rb, RRID: AB_2665533; National Hormone & Peptide Program, CA, USA; dilution 1:40) (iii) HRP-linked donkey anti-rabbit IgG, (Cat. No. NA934, RRID: AB_772206, VWR International/GE Healthcare, UK ). The LH ELISA antibodies (518B7 and AFP240580Rb) were validated by Steyn and colleagues34. The inter-assay and intra-assay variations were 10.53% and 5.74%, respectively. The assay sensitivity was 0.023 ng/mL.

LH pulse statistical analysis

LH pulses were determined using the Dynpeak algorithm in Scilab 5.5.2 programme35 with the settings adjusted to accommodate for the high LH pulse frequency in OVX mice as previously oulined by Breen and colleagues36. These include using the programs’ default parameters, except the global threshold that was increased to 35%, the nominal peak threshold was reduced to 20 minutes and the point 3-point peak threshold was removed. The average LH inter-pulse interval was calculated for the 1-h control period and the 1-h stimulation period in both experimental and control mice. Statistical significance was assessed using a 2-way ANOVA unless otherwise stated. Data were represented as mean ± SEM and p<0.05 was considered significant.

Mini-endoscope-based Calcium imaging

Optogenetic stimulation of MePD UCN3 neurons

Prior to recording, animals were handled daily for 5 to 6 weeks to get accustomed to the experimental setup. The Data Acquisition (DAQ) box (Inscopix, PN:100-005904) was turned on and connected to the computer wirelessly. The Data Acquisition Software (IDPAS; Inscopix, Inc.) was accessed through the Chrome web browser on the computer communicating with the DAQ box. Adequate DAQ box storage capacity was checked routinely before Calcium imaging. The GRIN lens baseplate dust cover was gently removed from the mouse’s head, after which the minscope camera was secured to the baseplate platform. Equipped with the head-mount miniscope (nVoke2, Inscopix, SN: BB-11238601), the mouse was then placed back into its home cage. The optimal focal plane was chosen by adjusting the lens focus to achieve clear cell morphology. The exposure time was fixed at 50 ms. The frame rate was set to 20 Hz. Subsequently, gain, and LED power were optimized based on image histograms before initiating recording. Two types of LED were used during the recording: (i) EX-LED (0.2-0.4 mW, 435-460 nm excitation filter) for GCaMP6s signal detection in the GABA or UCN3 neurons; (ii) OG-LED (10 mW, 590-650 nm excitation filter) for Chrimson optogenetic stimulation of the UCN3 neurons. After the mice were attached to the miniscope, they were given 1-2 h for adaptation. For stimulation of the UCN3 neurons, the OG-LED was set to 10 Hz, 5 sec on 5 sec off, and a 10-ms pulse width. Once the animals had acclimatized, the GCaMP6s recording of the GABA neurons or UCN3 neurons was started with a protocol of 2 min baseline before stimulation for 2 min. Optogenetic stimulation was randomized for the 10 Hz, with a 5-min interval between each to prevent photobleaching of GCaMP6s. Once the experiment was concluded, the miniscope was gently detached, and the baseplate cover was reattached and secured with its screw. The recordings were performed between 9:00 h and 15:00 h. Three groups of animals were included in this experiment: (i) mice with UCN3 neurons expressing opsin and GABA neurons expressing GCaMP (n = 6); (ii) mice with UCN3 neurons expressing both opsin and GCaMP, serving as a positive control (n = 2); (iii) mice with UCN3 neurons expressing mCherry and GABA neurons expressing GCaMP (n = 4), serving as a negative control. To quantify intra-animal variability at least two independent stimulation trials were conducted with each animal, with a maximum of four trials per animal (see Supplementary Table 1).

Restraint stress

The system was set up and the mouse was connected to the miniscope as described above but with the OG-LED turned off. Once the mouse had settled, the experiment started with a 3 min baseline recording, followed by 3 min of recording under hand-held restraint. Finally, the miniscope was detached and the baseplate cover was reattached. The experiments were performed between 9:00 h and 15:00 h. The animals in this experiment were the same as those used in the optogenetic stimulation protocol described above but were divided into two groups depending on whether GCaMP was expressed in the UCN3 or GABA neurons, regardless of whether opsin or mCherry was expressed in the UCN3 cells. A single trial per animal was performed to minimize unnecessary distress, in accordance with the 3Rs principle, apart from one animal in which the restraint stress experiment was performed twice to ensure this does not result in habituation (see Supplementary Table 1). In vivo calcium imaging recording processing

The video data, with a resolution of 1280 pixels x 800 pixels, was exported from the DAQ box through the file manager to a desktop computer and processed with the Inscopix Data Processing Software (IDPS). Within the IDPS, there are six essential steps for extracting single-cell calcium transient data from the recorded video: down-sampling, cropping, spatial filtering, motion correction, trace normalization (ΔF/F0), and cell identification. The video underwent both spatial down-sampling and temporal down-sampling by a factor of 2 and was cropped to enhance processing speed, focusing on the region of interest where the GCaMP signal was observed. Spatial filtering, with a threshold ranging between 0.005 (low) and 0.5 (high) was used to distinguish individual pixels in the video image, creating a high-contrast image. A mean intensity projection image was generated. Motion correction was subsequently conducted, using the mean intensity projection image as a reference. Motion correction was applied again using one of the frames affected by movement while simultaneously drawing a region of interest (ROI) where UCN3 accumulates to enhance the effectiveness of motion correction. For the recordings with GCaMP signals from GABA neurons, we did not use the built-in motion correction function of IDPS. Instead, we used the MATLAB (version R2022a) implementation of the open-source algorithm NoRMCorre37 with default parameters for both rigid and non-rigid (patch size 64 pixels and overlap 32) motion correction as long as a minimum correlation of the frames with the mean frame above 0.8 is achieved. This was performed by doubling the patch size and their overlap to 128 and 64, respectively. Corrected videos were saved in TIFF format for further analysis via IDPS. Following motion correction, pixel intensity, 𝐹(𝑥,𝑦), in each frame of the movie was normalized using the following formula (𝐹(𝑥,𝑦) − 𝐹𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒(𝑥,𝑦)) / 𝐹𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒(𝑥,𝑦), where 𝐹𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒(𝑥,𝑦) is the baseline pixel intensity calculated by taking the mean value of the pixel across the entire movie. Finally, regions of interest were identified automatically using the cell identification algorithm provided by IDPS, based on principal component and independent component analysis (PCA-ICA algorithm).

Validation of virus injection, fiber optic cannula and GRIN lens implantation

Once the experimental procedures were completed, a lethal dose of ketamine was used to humanely euthanize the mice. The mice were perfused transcardially with heparinized saline (5 U/ml) for 5 min, followed by ice-cold 4% paraformaldehyde (PFA) for 15 min using a pump (Minipuls,156 Gilson, Villiers Le Bel, France). The brains were collected and post-fixed sequentially at 4°C in a solution of 15% sucrose in 4% PFA and later in a solution of 30% sucrose in phosphate buffer until they sank. They were then snap frozen on dry ice and stored in -80°C until processing. The brains were coronally sectioned (30 μm) between +0.5 mm and -2.7 mm from the bregma using a cryostat (Bright Instrument Co., Huntingdon, UK), and sections were mounted on microscope slides, air-dried, and covered with slips using Prolonged Antifade mounting medium (Molecular Probes, Inc. OR, USA). The accuracy of injection sites, fiber optic cannula and GRIN lens implantation were confirmed by Axioskop 2 Plus microscope equipped with AXIOVISION 4.7 (Zeiss). Images were captured using Axioskop 2 Plus microscope (Carl Zeiss). The data analysis was performed in a blinded manner to minimise bias. The data of the animals were excluded from the final analysis only if post-hoc histological verification revealed (1) incorrect anatomical targeting of viral vectors to the MePD or (2) misplaced optical fibers or GRIN lenses. In total, 6 mice were excluded based on these criteria. All other data were included in the statistical analysis.

No statistical method was used to predetermine animal sample size. The experiments were conducted using a randomized design. The mice of the same genotype and age were randomly assigned to either the experimental group (receiving the active viral vector) or the control group (receiving a control virus). This randomization was performed within each animal cage to ensure that environmental factors were balanced across groups. Animals were randomly assigned to treatment and control groups using a random draw to minimize selection bias.

Immunohistochemistry

To assess the targeting of viral labeling to UCN3 neurons in the MePD, we used the indirect immunofluorescence technique to localize UCN3 neurons. Every 4th section from each brain was washed in potassium phosphate-buffered saline (KPBS) and incubated in blocking solution (KPBS containing 1% BSA, 0.03% Triton X-100 and 5 mg/mL heparin) at room temperature for 1 hour followed by incubated in a rabbit polyclonal anti-UCN3 antibody (1:2000 dilution)38 in the blocking solution (Code: PBL 7218, kindly provided by J. Vaughan, Salk Institute, La Jolla, CA, USA, Lot No. 01/12/11) for 48 hours at 4°C. This UCN3 antibody was validated by Shemesh and colleagues22. The brain sections were then processed with goat anti-rabbit IgG (H + L), a biotinylated secondary antibody (1:1000 dilution; Cat. No. BA-1000, Vector Laboratories, Burlingame, CA, USA) overnight at 4°C. After rinses in KPBS, visualization of UCN3 immunoactivity was achieved using Streptavidin, Alexa Fluor 405 conjugate (1:200 dilution; Cat. No. S 32351, Thermo Fisher Scientific, Waltham, MA, USA) for 2 hours at room temperature. The sections were finally washed, mounted onto slides and cover slipped. Omission of the UCN primary antibody and its pre-incubation resulted in the absence of specific staining, confirming specificity through negative controls. Brain sections from each experimental group were processed on the same day to control for inter-batch variability. To preserve the fluorescence of the virally expressed proteins, all subsequent steps were performed in a dark box. Semiquantitative analysis of immunostaining data was carried out on AxioVision microscope image system. UCN3-positive neurons were identified by Alexa Fluor 405 fluorescence, while native fluorescence (e.g. tdTomato or oScarlet) was used for virus-transduced neurons identification. The number of virus-labeled, UCN3-immunoreactive cells and co-localized cells in the MePD were quantified on 4 sections from each mouse brain. Targeting efficiency was defined as the percentage of virus-labeled cells that were also positive for UCN3.

Data analysis

The data processing protocol we employ in this study was performed in two phases: pre-intervention and intervention (either via optogenetic stimulation or restraint stress). For our analysis, we use the smoothed deconvolved traces generated by the OASIS method39, which improves the signal-to-noise ratio (SNR) and mitigates noise interference. All traces are rescaled between 0 and 1 (min-max normalization). The analysis process is divided into three key steps: i) identification of GABA cells co-expressing UCN3 and removing them from further analysis; ii) estimating and comparing functional connectivity before and during intervention; iii) clustering analysis based on pairwise association-derived dissimilarity scores. In step (i), we use power spectral density (PSD) analysis and K-means clustering (using Euclidean distance) to identify GABA neurons with activity that mimics the pattern of optic stimulation, evidence that they are co-expressing UCN3.

PSD filtering

For each trace, we compute the PSD during the stimulation phase. Cells with PSD values at 0.1 Hz (the frequency of the stimulus 5 sec and 5 sec off cycle) above 0.37 Hz-1 are labelled as co-expressing UCN3. This threshold is determined from recordings of UCN3 cells under optic stimulation, by calculating the median of the minimum PSD values at 0.1 Hz from each dataset (see Supplementary Figure 2B).

K-means clustering

Using the Euclidean distance metric, we cluster the traces during the stimulation phase into two groups, aiming to separate neurons into GABA-only neurons and neurons co-expressing UCN3 and GABA. Clustering separated a small group of neurons with activity mimicking the optic stimulation oscillatory pattern (see Supplementary Figure 2C). Recordings of MePD UCN3 neurons shows that under optogenetic stimulation their activity rises and declines in phase with on and off periods of stimulation (shown in Fig. 3A); therefore, this small number of cells was labeled as co-expressing UCN3.

The union of neurons identified by either method as co-expressing UCN3 and GABA are excluded from further analysis. By applying both filters, we aim to robustly identify purely GABA-expressing neurons. We acknowledge the possibility that some cells may pass through the filters or that a few purely GABA-expressing neurons may be inadvertently excluded. However, our dual approach of employing PSD analysis and K-means clustering minimizes this possibility and is essential to ensure our analysis remains focused exclusively on GABA-expressing neurons. Nevertheless, we take a further step and visually inspect the calcium recording traces for any potential anomalies such as regular oscillations in-phase with the stimulation and/or massive increase in calcium level during the intervention period. Any identified anomalies of this sort are also dropped from datasets.

Comparing pre-intervention and intervention cell-cell interaction strength

Following step (i), the remaining dataset contains only traces associated with GABA neurons, which are not directly activated by our optic stimulation protocol. In step (ii), we assess the functional defined in Equation (1) as

𝑅(𝑥,𝑦) (1)
𝑐𝑜𝑟𝑟(𝑥,𝑦) = ,
√𝑅(𝑥,𝑥)𝑅(𝑦,𝑦)

where 𝑅(𝑥,𝑦) = ∑𝑁 (𝑥 −𝑥̅)(𝑦 −𝑦̅) represents cross-correlation with 𝑁 as the length of 𝑥 and𝑦.
𝑖=1 𝑖 𝑖

Using the above measure in Equation (1), we construct the corresponding cross-correlation matrices (see for an example Fig. 1H&I).

To evaluate changes in pairwise cell interactions between the pre-intervention and intervention phases, we compute the pairwise Riemannian distance41 between correlation matrices from pre-intervention and intervention episodes. The Riemannian distance here is defined as

𝑑(𝐴,𝐵) = (∑ 𝑙𝑛 (𝜆 )2) 1/2 , (2)
𝑖 𝑖

where 𝑙𝑛 is the natural logarithm and 𝜆 indicates the joint eigenvalues of symmetric positive definite (SPD) cross-correlation matrices 𝐴 and 𝐵. In Equation (2) the size of the matrices directly affects the Riemannian distance, therefore, we normalize each Riemannian distance by the average Riemannian distance computed from 100 pairs of randomly generated SPD matrices of the same size. To make sure that random generation is uniform in the space of SPD matrices, we employ the Metropolis-Hasting method introduced in42. Normalizing the Riemannian distances guarantees that the distance is not influenced by matrix size. To assess the effect of experimental conditions on Riemannian distances while accounting for the hierarchical structure of the data, we employed a linear mixed-effects model43. The model was fitted using maximum likelihood estimation.

Clustering analysis

In step (iii), we apply agglomerative hierarchical clustering (using the average linkage criterion; package in scikit-learn Python™) to classify cells based on the dissimilarity of their calcium activity, given in Equation (4) as

𝐷(𝑥,𝑦) = 1−𝑐𝑜𝑟𝑟(𝑥,𝑦). (3)

To determine the optimal number of clusters and robustness of clustering, we employed a bootstrapping technique. This involved resampling (without replacement) 75% of the cells and clustering the resulting dataset with different numbers of clusters (2, 3, and 4) using hierarchical or K-means clustering with either the covariance or correlation as the dissimilarity measure. This resampling process was repeated 100 times.

For each resample dataset, we evaluate the clustering performance, using the Silhouette Coefficient (SC)42 which measures the cohesion within clusters and their separation, with values ranging from -1 (poor performance) to 1 (good performance). Results of the evaluation are given in Supplementary Figs. 4-6, showing that the SC is significantly higher for 2 clusters compared to 3 or 4 clusters in the case of both hierarchical and K-means clustering. The cluster sizes then were compared using linear mixed-effect model43 for all animals, including stress and stimulation, and for stimulation and stress separately.

Modeling

We build on our previously published modeling framework of MePD circuit11 by incorporating dynamic stimulation by UCN3 neurons as observed experimentally (as shown in Fig. 3). To this end we define input from UCN3 neurons into the populations of glutamatergic neurons and GABA interneurons with a strength given by the parameter 𝛾. The activity of UCN3 neurons during stimulation is approximated by a sinusoidal function:

𝑈 (𝑡) = 𝛾𝐵+𝐴𝑠𝑖𝑛(2𝜋𝑓𝑡), (4)
𝑠𝑡𝑖𝑚

where the parameter 𝑓 is the frequency of the wave. In Equation (5) parameter 𝐵 represents the constant excitatory drive, potentially mediated by slow neuropeptide action, while the term 𝐴𝑠𝑖𝑛(2𝜋𝑓𝑡) describes faster neurotransmitter-driven-driven input aligned with optogenetic stimulation frequency. UCN3 neuron activity during restraint stress is approximated as the sum of two exponential components as shown in Equation (6)

𝑈 (𝑡) = 𝛾(𝑎𝑡𝑒𝑥𝑝(−𝑟 𝑡)+𝑏(1−𝑒𝑥𝑝(−𝑟 𝑡))), (5)
𝑠𝑡𝑟𝑒𝑠𝑠 2 1

where 𝑎𝑡𝑒𝑥𝑝(−𝑟 𝑡) represents a transient increase in activity that rises shortly after stress onset and then decays, while the second term 𝑏(1−𝑒𝑥𝑝(−𝑟 𝑡)) describes a slower component that gradually accumulates and approaches a sustained plateau. In Equation (6) the parameters 𝑟 and 𝑟 are responsible for the rate of increase of the former term and rate of decrease to a plateau, while 𝑎 and 𝑏 determine their relative magnitudes.

Briefly, the model captures the dynamics of the MePD intracellular calcium activity of three populations: glutamatergic neuronal population (excitatory) and the populations of GABA interneurons and GABA efferent neurons (inhibitory). We build on our previous work11 by assuming that excitatory (UCN3) input is provided to the populations of GABA interneurons and glutamate (Fig 3). Previous analysis of the model indicated that negative feedback between GABA and glutamatergic neuronal populations as well as glutamatergic self-excitation are critical mechanisms for inducing oscillatory dynamics11. However, providing glutamatergic inputs to both populations of GABA neurons results in a null phase difference between the populations. Therefore, we opted to provide glutamatergic input only to the population of GABA efferent neurons.

To investigate how the amygdala modulates the activity in the GnRH pulse generator, we couple the above-described MePD model to our KNDy network model, where the oscillatory dynamics of the KNDy acts as a proxy of LH pulsatility26. Here we couple the model via providing only inhibitory output from MePD GABA efferent neurons population to KNDy, as it was previously shown that glutamate plays a modulatory role to the MePD output rather than directly affecting the KNDy network11. We then calibrate the coupled model by reproducing the experimental results from Ivanova et al.23 (Supplementary Figure 8). Further modeling details, such as equations governing model dynamics and model parameter values, can be found in Supplementary Information. The simulations have been done in MATLAB (version R2023b).

Statistics & Reproducibility

Optogenetic stimulation at 10 Hz was randomized across trials, with a 5 min interval between stimulation epochs to limit photobleaching of GCaMP6s. No statistical method was used to predetermine sample size. Experiments were conducted using a randomized design, with mice of the same genotype and age randomly assigned to experimental (active viral vector) or control (control virus) groups. Randomization was performed within each cage to balance environmental factors across groups, and assignment to treatment and control conditions was carried out using a random draw to minimize selection bias.

Data were excluded from the final analysis only if post hoc histological verification revealed incorrect anatomical targeting of viral vectors to the MePD or misplaced optical fibres or GRIN lenses. Based on these predefined criteria, a total of six mice were excluded. All remaining data were included in the statistical analyses. The investigators were not blinded to allocation during experiments or outcome assessment.

Statistical analyses were performed using the methods specified in the figure legends, with exact P values reported. Experiments were repeated across independent animals with similar results, and sufficient methodological detail is provided to allow assessment of reproducibility.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Review of Yu et al., Amygdala GABA Neurons: Gatekeepers of Stress and Reproduction\nThe manuscript by Yu et al investigates the involvement of different populations of posterodorsal medial amygdala (MePD) neurons on luteinizing hormone (LH) pulse frequency. The authors use an impressive array of tools including in vivo Ca2+ imaging, optogenetics and modelling. The authors conclude that there are two anti-correlated GABAergic sub-populations in the MePD that dictate responses to both UCN3 neuron stimulation and restraint stress.\nThis study provides additional insight into how neural circuits in the MePD regulate LH pulse frequency and hence fertility. As such, this is important work. However, I have a few concerns, which are noted below.\nPrevious work from several of the authors from this group have suggested a different connectively pattern than that currently proposed (see Ivanova et al Endocrinology 2023). In that paper, the UNC3 neurons are proposed to be glutamatergic. However, in this paper, they are proposed to be GABAergic. Because of the complexity of the proposed circuit under study, it is not possible to delineate the connectively with in vivo optogenetics. As such, it is essential in my opinion that the authors conduct additional in vitro channelrhodopsin-assisted circuit mapping with patch clamp electrophysiology to conclusively show the true connectivity. In addition, these in vitro experiments would reveal 1) whether UNC3 neurons release GABA, glutamate or both and 2) the effect of endogenous UNC3 release on MePD GABA neuron excitability.\nIt wasn’t until I read the supplementary Fig 8 that I appreciated how the miniscope imaging needed to be processed in order to exclude UNC3 expressing GABA neurons. While I am sure that this process does exclude a large number of these neurons, how can the authors be sure that all are excluded? In the UNC3 GABA neurons that remain, do these contribute to one of the clusters observed in Fig 2? At the very least, the data for these cells should be analysed and reported in Fig 2. Secondly, are the UNC3 cells excluded from the optogenetic stimulation data set also excluded from the stress data set? If they are, then also please show the response of the UNC3 neurons to stress.\nI notice that the baseline activity of GABA neurons prior to optogenetic stimulation (Fig 1A) is much higher than the baseline activity of the neurons prior to stress. Why is that? It would be useful to determine if the response of these neurons in the optogenetic stimulation experiment can predict how these neurons respond to stress.\nMany of the experiments in this manuscript rely on the targeting of specific neural populations with intersectional strategies. However, there is no quantification of the targeting of any of the viruses used (i.e. % coexpression). This quantification is required so that the reader can see how specific the virus expression is.\nIn addition to reporting effects on LH pulse frequency, it is also important to report how LH pulse height and mean LH levels are affected by the experimental manipulations.", "reviewer_2": "The authors employ an elegant combination of in vivo optical methods, computational modelling, and hormone measurements to dissect the circuit mechanisms underlying the impact of stress on the MePD and downstream KNDy network. The study is timely and compelling, integrating multiple levels of analysis to provide insight into how stress modulates reproductive function. However, several key concerns related to specificity, controls, and interpretation must be addressed to ensure a robust and well-supported conclusion. I encourage the authors to consider these points carefully to strengthen their findings.\nMAJOR POINTS\nThe authors should provide direct evidence confirming the specificity of their intersectional strategy. In Figure 1B-F, the fluorescence panels are labelled as UCN3 and VGAT, yet these signals merely represent red and green fluorescence, which may not necessarily correspond to the expected cell types. To support specificity, quantitative validation is needed, such as an overlap analysis of UCN3 immunohistochemical staining with red fluorescence to confirm accurate targeting.\nThe manuscript suggests that both optogenetic UCN3 stimulation and restraint stress induce similar functional connectivity changes and clustering patterns in MePD GABAergic populations. However, stress appears to drive a much stronger excitation of GABA neurons than UCN3 stimulation. Have the authors quantified the effects of stress and UCN3 stimulation on ΔF/F changes compared to baseline? A direct statistical comparison would clarify the relative strength of these manipulations. A more definitive test would be to silence UCN3 neurons during stress to assess whether the activation of GABAergic neurons and clustering patterns are abolished. While this may be beyond the scope of the current study, it should at least be discussed as a necessary future experiment.\nHave the authors done sufficient controls to ensure that 1-photon light excitation of the calcium indicator does not also activate the opsin? Similarly, have they conducted control experiments to verify that their observed effects are due to activation of inhibitory neurons rather than simply light delivery? These controls are well-documented for Figures 5-6 but are missing for Figures 1-2.\nUnless I am misunderstanding this, it seems that SLxCorr analysis allows for lag values spanning nearly the entire recording: τ∈{−N+1,...,−1,0,1,...,N−1}. Given that neuronal interactions typically occur on much shorter timescales, could the authors justify this choice?\nHave they tested whether restricting τ to a smaller, physiologically relevant window alters their clustering results?\nAdditionally, to confirm that anticorrelated ensembles exist independently of the clustering approach, could the authors provide a standard correlation matrix (e.g., using Pearson correlation) computed over a biologically relevant lag window? This would help verify that clear anticorrelated subgroups are present in the raw data, strengthening confidence in the reported clustering results.\nGiven this, how can the authors be sure that a mutually inhibitory interaction in the model is a correct implementation? The anticorrelated activity may occur at a very long timescale that is not related to biologically plausible interactions between neurons. Further explanations and/or controls to justify this choice are needed.\nThe modelling approach assumes mutual inhibition between the two GABAergic populations, yet this is not independently validated, and given the long time lags in SLxCorr, the presence of direct monosynaptic inhibition is unclear. Is anticorrelation an emergent property of the model or an inevitable built-in feature given the model architecture (i.e., simply enforced by the mutual inhibition, which may be unwarranted)? Could the authors clarify how they validated the presence of mutual inhibition and whether alternative model architectures would result or not in anticorrelated activity?\nThe intersectional approaches to restrict expression to individual populations or mixed populations are elegant and strengthen the paper. However, more thorough controls are required to ensure the expression patterns in the expected neuron types are present. Fluorescence micrographs are often not sufficiently zoomed in or clear, and are not corroborated by additional controls (e.g., immunohistochemical staining to verify expression in the appropriate cell types).\nThe authors write: “We test these predictions using optogenetics and confirm that GABAergic neurons operate downstream of the UCN3 population, playing a crucial role in transmitting UCN3 signals to regulate luteinizing hormone (LH) pulse frequency.” However, I do not see an unequivocal experimental demonstration of UCN3 neurons acting upstream of GABA neurons. The paper would benefit from either stronger circuit mapping evidence or a fairer description of the findings.\nThe title could better reflect the actual findings of the paper.\nMINOR POINTS\nInstead of performing KS tests on individual mice and combining p-values with Fisher’s method for functional connectivity changes, a more straightforward approach would be to compare baseline vs. stress/stimulation using mice as samples (e.g., paired t-test or Wilcoxon signed-rank test). This would directly assess whether functional connectivity changes at the group level. Have the authors considered this approach?\nThe study uses hand-held restraint as a stressor, but this method can introduce variability due to experimenter handling differences and potential habituation effects. Could the authors clarify the choice of this model (e.g., they used predator odour in Ivanova et al. 2021)?\nThe paper would benefit from a better introduction and discussion (with references) about previous work supporting the link between stress and infertility. Clarifying whether this happens with chronic or acute stress and how this relates to the current study (acute stress) would be useful.\nDo the authors have any information on the behaviour of the mouse during calcium imaging baseline recordings? i.e., were they mostly still, moving, etc.?\nRemove “opsin stimulation” in Figure 4 and replace it with “stimulation” and a different symbol. It is confusing given that this is a model.\nLine 289: “Opposite” is probably a more appropriate word than “orthogonal.”", "reviewer_3": "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_4": "In this manuscript, Yu et al. explore the role of UCN3 and GABAergic neurons in the medial amygdala posterodorsal subdivision (MePD) in regulating gonadotropin-releasing hormone (GnRH) pulse frequency, combining optogenetics, calcium imaging, and computational modeling to unravel how these neurons encode stress signals and modulate luteinizing hormone (LH) pulsatility. The study identifies complementary roles for two distinct GABAergic sub-populations and highlights the function between UCN3 and GABA signaling in the MePD. These findings provide new insights into the neural circuits underlying stress-induced reproductive suppression and have important scientific implications.\nA key question is how the activation strength of UCN3 neurons regulates the mutual inhibition between the two distinct GABAergic subpopulations. This issue could be addressed experimentally.\nMinor comments:\n1.Fig. 1J should be clearly explained.\n2.P5, line 105: no reference(s) is/are given for this statement, i.e. neurons response as a set of interconnected nodes (neurons) with connections can weighted by their functional interactions\n3.P7, line 139:“Fig2D&E”# “Fig2E&F”\n4.P7, line 119-120 pAAV-Syn- Flex-rc # pAAV-Syn- Flex - Chrimson - tdTomato?\n5.P9, line 158: Please provide a brief introduction to the purpose and principles of the mathematical modeling framework for MePD circuitry.\n6.Some paragraphs could be further streamlined to avoid lengthy descriptions. For example, P9 and P11, the description of the computational model could more clearly highlight its relationship to experimental data.\n7.P17, line 312 AAV-EF1a-ChR2 # AAV-EF1a-DIO-ChR2\n8.The fluorescent brain tissue images in Fig 5 E-F and K-M should display the optical fiber sites.\n9.All optogenetic viruses used in the manuscript should provide evidence of their effectiveness.\n10.Definitions or explanations of key terms (e.g., \"GABAergic efferent neurons\") could be included for non-specialist readers.\n11.For critical experiments (e.g., optogenetic activation of GABAergic neurons leading to LH pulse suppression), increasing control group sample size could improve statistical power.\n12.Some conclusions (e.g., identifying GABAergic neurons as downstream targets of UCN3 signaling) could be further discussed in the context of physiological and pathological conditions.\n13.The classification of GABAergic neurons (e.g., efferent vs. interneurons) within the MePD could be discussed further for its broader applicability to other brain regions.\n14.Additional discussion on the practical implications of these findings for reproductive health (e.g., stress-related infertility) could strengthen the manuscript."}, "author_response": "Response to the reviewers\nWe would like to thank the reviewers for their constructive feedback. Below, we address each\nof their comments point by point\nReviewer #1\n1. Previous work from several of the authors from this group have suggested a different\nconnectivity pattern than that currently proposed (see Ivanova et al Endocrinology 2023). In\nthat paper, the UNC3 neurons are proposed to be glutamatergic. However, in this paper, they\nare proposed to be GABAergic. Because of the complexity of the proposed circuit under study,\nit is not possible to delineate the connectively with in vivo optogenetics. As such, it is essential\nin my opinion that the authors conduct additional in vitro channelrhodopsin-assisted circuit\nmapping with patch clamp electrophysiology to conclusively show the true connectivity.\nIn addition, these in vitro experiments would reveal 1) whether UNC3 neurons release GABA,\nglutamate or both and 2) the effect of endogenous UNC3 release on MePD GABA neuron\nexcitability.\nThe challenging in-vivo study by Ivanova et al. 2023, utilised optogenetic activation of\nUCN3 neurons with intra-nuclear neuropharmacological antagonism of GABAergic or\nglutamatergic signalling. Both were affective at blocking the inhibitory effects of optical\nstimulation on UCN3 neurons on LH pulse frequency. The schematic circuitry referred\nto by the reviewer explained our novel neuropharmacological observations and the\nproposed potential glutamatergic nature of the UCN3 neurones was congruent with this\nneurochemical phenotype of UCN3 neurones in other brain regions, including the\nhypothalamic perifornical area. The cutting-edge GRIN-lens miniendoscopic\ntechnology used in the present study allows us to selectively visualise the actual\nactivity of individual GABA neurones in the amygdala, the neurones of interest, and\nrecord their response to stress or optogenetic stimulation of the stress-related UCN3\nneurones, placing us in a unique position to interrogate the circuitry. We examined the\nresponse of GABA neurones to optical stimulation of UCN3 neurons and found that\nsome GABA neurons may co-express UCN3 (see response to 2nd comment) As the\nreviewer clearly recognises co-release of GABA and glutamate is prevalent (eg.\nCeballos etal 2024; doi:10.1101/2024.03.27.587069) in the CNS. Naturally, we cannot rule\nout the possibility that UCN3 neurons co-express both neurotransmitters. Although in\nvitro electrophysiological patch-clamp experiments would indeed be valuable in\nelucidating the circuit, regrettably we are not in a position to perform them at this stage.\nWe would therefore kindly ask the reviewer to consider our suggestion that such\nexperiments may be beyond the scope of the present study, which is focused primarily\non the activity of GABA neurons in the amygdala.\n1\n2. It wasn’t until I read the supplementary Fig 8 that I appreciated how the miniscope imaging\nneeded to be processed in order to exclude UNC3 expressing GABA neurons. While I am sure\nthat this process does exclude a large number of these neurons, how can the authors be sure\nthat all are excluded? In the UNC3 GABA neurons that remain, do these contribute to one of\nthe clusters observed in Fig 2? At the very least, the data for these cells should be analysed\nand reported in Fig 2. Secondly, are the UNC3 cells excluded from the optogenetic stimulation\ndata set also excluded from the stress data set? If they are, then also please show the\nresponse of the UNC3 neurons to stress.\nTo ensure the exclusion of as many UNC-3 neurons expressing GABA as possible from\nour analysis, we applied two independent filtering approaches. The first filter involved\ncalculating the power spectral density of individual neurons and excluding those that\nshowed significant power around the frequency of our stimulation protocol (5-second\non/off intervals; 0.1 Hz). The second filter used unsupervised clustering, which\nidentified a distinct population of neurons exhibiting clear oscillatory activity in phase\nwith the stimulation. Neurons identified by either filter were excluded from all\nsubsequent analyses. This filtering pipeline is now clearly described in the Methods\nsection. For added clarity and conciseness, we also provide an illustrative figure\nshowing the activity of these neurons in the Supplementary Information\n(Supplementary Fig. 2), which is referenced in the caption of Figure 1 and in line 130-\n131.\nRegarding the reviewer’s second comment, UCN3-expressing GABAergic neurons\ncannot be directly identified in recordings from acutely stressed animals. These\nneurons may therefore contribute to the observed clusters. Nonetheless, the presence\nof two distinct clusters aligned with the stimulation protocol suggests that the\nfunctional role of UCN3 GABAergic neurons during acute stress is limited. This\ninterpretation is further supported by our functional intersectional study (Fig. 5H–J).\n3. I notice that the baseline activity of GABA neurons prior to optogenetic stimulation (Fig 1A)\nis much higher than the baseline activity of the neurons prior to stress. Why is that? It would\nbe useful to determine if the response of these neurons in the optogenetic stimulation\nexperiment can predict how these neurons respond to stress.\nIn Figure 1, we present scaled ΔF/F₀ traces normalized to the 0–1 range using the\nminimum and maximum values from the entire duration of the experiment. While this\napproach allows for visual comparison between baseline and intervention periods, it\nrenders comparisons across different experiments invalid. In this example, the\nresponse to stress greatly exceeds baseline activity, making the baseline activity\nappear dwarfed after normalization. In contrast, during UCN3 stimulation, activity\nduring the intervention looks more comparable to baseline levels. We have quantified\nthe effects of stress and UCN3 stimulation on ΔF/ F₀ changes compared to baseline and\nour results are now presented in Fig 1K.\n2\n4. Many of the experiments in this manuscript rely on the targeting of specific neural\npopulations with intersectional strategies. However, there is no quantification of the targeting\nof any of the viruses used (i.e. % coexpression). This quantification is required so that the\nreader can see how specific the virus expression is. In addition to reporting effects on LH pulse\nfrequency, it is also important to report how LH pulse height and mean LH levels are affected\nby the experimental manipulations.\nWe have now included the quantification of the % co-expression of the viruses used in\nthe revised manuscript. Lines 94-98, 278-283 and 305-310. See Supplemental Fig. 1, 11\nand 12 for the supportive histology. We have also added the data relating to LH pulse\namplitude and mean LH levels. See Supplementary Tables 3 and 4.\nReviewer #2\n1. The authors should provide direct evidence confirming the specificity of their intersectional\nstrategy. In Figure 1B-F, the fluorescence panels are labelled as UCN3 and VGAT, yet these\nsignals merely represent red and green fluorescence, which may not necessarily correspond\nto the expected cell types. To support specificity, quantitative validation is needed, such as an\noverlap analysis of UCN3 immunohistochemical staining with red fluorescence to confirm\naccurate targeting.\nIn the revised manuscript we have provided the overlapping analysis of the UCN3\nimmunohistochemical staining with the red fluorescence to confirm accurate targeting.\nSee Supplementary Fig. 1. The appropriate methodology is outlined in lines 677-698.\n2. The manuscript suggests that both optogenetic UCN3 stimulation and restraint stress induce\nsimilar functional connectivity changes and clustering patterns in MePD GABAergic\npopulations. However, stress appears to drive a much stronger excitation of GABA neurons\nthan UCN3 stimulation. Have the authors quantified the effects of stress and UCN3 stimulation\non ΔF/F changes compared to baseline? A direct statistical comparison would clarify the\nrelative strength of these manipulations. A more definitive test would be to silence UCN3\nneurons during stress to assess whether the activation of GABAergic neurons and clustering\npatterns are abolished. While this may be beyond the scope of the current study, it should at\nleast be discussed as a necessary future experiment.\nWe thank the reviewer for their constructive comment. Following up on this comment,\nwe calculated the change of the time-averaged ΔF/F₀ relative to baseline under\nconditions of stress and UCN3 stimulation. Our results indicate a significant difference\nbetween the two manipulations at short timescales (<90 seconds), which diminishes by\n120 seconds. Results of the analysis can be found in Fig. 1K.\n3. Have the authors done sufficient controls to ensure that 1-photon light excitation of the\ncalcium indicator does not also activate the opsin? Similarly, have they conducted control\nexperiments to verify that their observed effects are due to activation of inhibitory neurons\nrather than simply light delivery? These controls are well-documented for Figures 5-6 but are\nmissing for Figures 1-2.\nactivation the reviewer refers to, providing of course that one uses the appropriate AAV\nconstructs. Indeed, note that one-photon GECI excitation is typically achieved with light\npowers that are approximately an order of magnitude lower than opsin excitation, which\nallows for simultaneous use of GCaMP6 and Chrimson with minimal cross-talk. We\nhave ensured that our experimental design minimises the risk of cross-activation, and\nwe can confirm the following:\n1. Wavelength Separation: As mentioned, the excitation light for GCaMP6s (~480\nnm) and Chrimson-tdTomato (~590 nm) are well-separated, ensuring\nminimaloverlap in their activation spectra (Siciliano and Tye 2018,\nhttps://doi.org/10.1016/j.alcohol.2018.05.013). The excitation light for GCaMP6s\ndoes not activate Chrimson-tdTomato, and we have used nVoke Optics, which\noptimises this separation further, with the 455 ± 8 nm excitation for GCaMP6s\nand 620 ± 30 nm for Chrimson. This setup is also supported by previous\nstudies (Jimenez et al. 2020, https://www.nature.com/articles/s41467-020-17270-\nw; Stamatakis et al. 2018, https://doi.org/10.3389/fnins.2018.00496; Vidal-Ortiz\net al. 2024, https://doi.org/10.1093/sleep/zsad217)\n2. Optogenetic activation of inhibitory neurons is not purely due to light delivery.\nFigures 5-6 already include light-only control experiments where no response\nis observed with the control virus, showing that light delivery itself does not\ncause neuronal responses. Therefore, the light delivery controls in Figures 5-6\nserve as evidence that light alone is not driving the effects observed in Figures\n1-2, ie., GABA neuronal activity that correlates with LH pulse dynamics.\n3. Irradiance Differences: The irradiance for the GCaMP6s imaging system (0-2\nmW) is much lower than that for Chrimson-tdTomato, further reducing the\npossibility of cross-activation during imaging. This significant difference in\nirradiance between the two light sources ensures that GCaMP6s excitation\ndoes not inadvertently activate Chrimson-tdTomato.\n4. Additionally, one can see from Figure 1 A&J, that the behaviour of the\nGABAergic neurons significantly changes from the baseline period and\nsubsequent optical stimulation.\n5. With respect to the control experiments to verify that our observed effects are\ndue to activation of the inhibitory neurons rather than simply light delivery, we\nhad carried out those experiments using the appropriate control viruses and\nthey are now included in figure 1J.\n4\n4. Unless I am misunderstanding this, it seems that SLxCorr analysis allows for lag values\nspanning nearly the entire recording: τ∈{−N+1,...,−1,0,1,...,N−1}. Given that neuronal\ninteractions typically occur on much shorter timescales, could the authors justify this choice?\nHave they tested whether restricting τ to a smaller, physiologically relevant window alters their\nclustering results? Additionally, to confirm that anticorrelated ensembles exist independently\nof the clustering approach, could the authors provide a standard correlation matrix (e.g., using\nPearson correlation) computed over a biologically relevant lag window? This would help verify\nthat clear anticorrelated subgroups are present in the raw data, strengthening confidence in\nthe reported clustering results\nWe thank the reviewer for their comment. Using Pearson correlation (zero-lag) to assess\nfunctional connectivity reveals two anticorrelated clusters, consistent with the results\nobtained using SLxCorr. This confirms the presence of clearly anticorrelated groups\nwithin the GABAergic population. To simplify the presentation of our results (see also\ncomment 5), we have revised our analysis pipeline to use Pearson correlation matrices\nfor assessing the network’s functional connectivity and identifying functional clusters,\nwhile retaining the SLxCorr analysis in the Supplementary Information. Our results and\nconclusions remain unchanged.\n5. Given this, how can the authors be sure that a mutually inhibitory interaction in the model is\na correct implementation? The anticorrelated activity may occur at a very long timescale that\nis not related to biologically plausible interactions between neurons. Further explanations\nand/or controls to justify this choice are needed.\nThe modelling approach assumes mutual inhibition between the two GABAergic populations,\nyet this is not independently validated, and given the long time lags in SLxCorr, the presence\nof direct monosynaptic inhibition is unclear. Is anticorrelation an emergent property of the\nmodel or an inevitable built-in feature given the model architecture (i.e., simply enforced by\nthe mutual inhibition, which may be unwarranted)? Could the authors clarify how they validated\nthe presence of mutual inhibition and whether alternative model architectures would result or\nnot in anticorrelated activity?\nAs we discussed in the point above, our analysis results reveal two anticorrelated\nneuronal clusters regardless of whether we use lagged cross-correlation or Pearson\ncorrelation (zero-lag). Given the GABAergic identity of these neurons, mutual inhibitory\ninteractions between the two clusters are expected and represent a justifiable\nexplanation for the anticorrelated activity. We used our model to investigate whether\nunidirectional inhibition might give rise to anticorrelated activity, but our results\nindicate that this mechanism alone is insufficient.\n6. The intersectional approaches to restrict expression to individual populations or mixed\npopulations are elegant and strengthen the paper. However, more thorough controls are\nrequired to ensure the expression patterns in the expected neuron types are present.\nFluorescence micrographs are often not sufficiently zoomed in or clear, and are not\ncorroborated by additional controls (e.g., immunohistochemical staining to verify expression in\nthe appropriate cell types).\nPlease see response to point 1 above. The new figure includes immunohistochemical\nstaining and has higher magnification images.\n7. The authors write: “We test these predictions using optogenetics and confirm that\nGABAergic neurons operate downstream of the UCN3 population, playing a crucial role in\ntransmitting UCN3 signals to regulate luteinizing hormone (LH) pulse frequency.” However, I\ndo not see an unequivocal experimental demonstration of UCN3 neurons acting upstream of\nGABA neurons. The paper would benefit from either stronger circuit mapping evidence or a\nfairer description of the findings.\nWe appreciate the reviewer’s comments and have revised the manuscript to reflect a\nfairer description of the aims and findings. See abstract and lines 480-489 (discussion).\n5\n8. The title could better reflect the actual findings of the paper.\nWe have changed the title of the manuscript in accordance with the reviewer’s\nrecommendation, thank you.\nMinor comments:\n9. Instead of performing KS tests on individual mice and combining p-values with Fisher’s\nmethod for functional connectivity changes, a more straightforward approach would be to\ncompare baseline vs. stress/stimulation using mice as samples (e.g., paired t-test or Wilcoxon\nsigned-rank test). This would directly assess whether functional connectivity changes at the\ngroup level. Have the authors considered this approach?\nWe thank the reviewer for their suggestion. Following the revision of our pipeline to\nquantify functional connectivity using Pearson correlation, we have also updated our\nstatistical analysis to compare baseline and intervention periods across control, UCN3-\nstimulated, and stressed animals. The results are presented in Figure 1, and the\nmethodology is detailed in the Methods section.\n11. The study uses hand-held restraint as a stressor, but this method can introduce variability\ndue to experimenter handling differences and potential habituation effects. Could the authors\nclarify the choice of this model (e.g., they used predator odour in Ivanova et al. 2021)?\nWe appreciate the concerns of the reviewer. However, we know from our experience\nthat hand-held restraint does decrease hypothalamic arcuate multi-unit activity volleys,\nan electrophysiological correlate of GnRH pulse generator activity and LH pulsatility in\nmice. All the in-vivo mini-endoscopic experiments were carried out by one individual\nwhich will have minimised experimenter handling differences, and we know from our\nconsiderable experience that mice do not readily habituate to this type of restraint in\ncomparison to normal gentle handling associated with attaching and detaching the\nmini-endoscope camera. Ideally, we would have liked to have used predator odour, but\nthe size of the Inscopix system is not compatible with a fume cupboard that is essential\nfor this stressor as used by Ivanova et al 2021.\n12. The paper would benefit from a better introduction and discussion (with references) about\nprevious work supporting the link between stress and infertility. Clarifying whether this happens\nwith chronic or acute stress and how this relates to the current study (acute stress) would be\nuseful.\nIn line with the reviewer’s recommendation, we have revised the manuscript\naccordingly. See lines, 41-44 and 494-498.\n13. Do the authors have any information on the behaviour of the mouse during calcium imaging\nbaseline recordings? i.e., were they mostly still, moving, etc.?\nThe mice are extensively habituated to the Inscopix system, so the vast majority of the\ntime they are still. We have never observed any difference in baseline neuronal activity,\nwhether the animal is still, moving or indeed sleeping.\n6\n14. Remove “opsin stimulation” in Figure 4 and replace it with “stimulation” and a different\nsymbol. It is confusing given that this is a model.\nWe have revised Figures 3 and 4 and replaced the term “opsin stimulation” with\n“stimulation” and used a different symbol to minimise confusion.\n15. Line 289: “Opposite” is probably a more appropriate word than “orthogonal.”\nWe have reworded the text to avoid using the term ‘orthogonal’. The revised sentence\nnow reads: “our results suggest that although UCN3 and GABAergic neuronal\npopulations overlap, they serve distinct functional roles within the MePD circuit, with\nboth being critical for relaying inhibitory signals to the hypothalamic GnRH pulse\ngenerator. While independent activation of either population inhibits the GnRH pulse\ngenerator, activation of UCN3 neurons that co-express GABA is insufficient to elicit this\neffect.”. See lines 319-323.\nReviewer #4\n1. A key question is how the activation strength of UCN3 neurons regulates the mutual\ninhibition between the two distinct GABAergic subpopulations. This issue could be addressed\nexperimentally.\nWe thank the reviewer for their constructive suggestion. We used varying frequencies\nof optogenetic stimulation of UCN3 neurons to examine how activation strength\ninfluences GABA neuron activity. Our data show that stimulation at 5, 10, or 20 Hz does\nnot significantly alter the correlation between the average activity of the two GABA\nclusters (Supplementary Fig. 8). However, stimulation frequency does affect overall\nfunctional connectivity within the GABA network (Supplementary Fig. 7). Specifically, 5\nHz stimulation produces no significant change relative to control animals, while 10 Hz\nstimulation leads to a measurable alteration in functional connectivity. Further\nincreasing the frequency to 20 Hz reduces the effect on the functional connectivity,\nconsistent with a depolarization block effect.\nMinor comments:\n2. Fig. 1J should be clearly explained.\nOur revised statistical analysis is now clearly explained in the caption and methodology\nsection.\n3. P5, line 105: no reference(s) is/are given for this statement, i.e. neurons response as a set\nof interconnected nodes (neurons) with connections can weighted by their functional interactions\nensembles: Building blocks of neural circuits.\" Neuron 112.6 (2024): 860-861.\n4. P7, line 139:“Fig2D&E”# “Fig2E&F”\nCorrection made\n5. P7, line 119-120 pAAV-Syn- Flex-rc # pAAV-Syn- Flex - Chrimson - tdTomato?\nCorrection made\n6. P9, line 158: Please provide a brief introduction to the purpose and principles of the\nmathematical modeling framework for MePD circuitry.\nWe updated the first paragraph of the section “Mutually inhibitory interactions between\nGABA populations drive anti-correlated activity” to clarify the purpose of the\nmathematical model. We emphasise that the model is used to explore the mechanisms\nunderlying the observed data. We also reference our previous work, in which we\nintroduce the MePD model and provide further technical details.\n7. Some paragraphs could be further streamlined to avoid lengthy descriptions. For example,\nP9 and P11, the description of the computational model could more clearly highlight its\nrelationship to experimental data.\nWe would like to thank the reviewer for their helpful suggestion. We have updated P9\nto provide a more precise introduction to the model and clarify the purpose of our in-\nsilico investigations. Also, on P11, we explicitly emphasize that KNDy activity is a\nreliable proxy for LH pulsatility, reinforcing how our model is firmly grounded in and\nsupported by experimental evidence.\n8. P17, line 312 AAV-EF1a-ChR2 # AAV-EF1a-DIO-ChR2\nCorrection made\n9. The fluorescent brain tissue images in Fig 5 E-F and K-M should display the optical fiber\nsites.\nCorrection made, see revised figures.\n10. All optogenetic viruses used in the manuscript should provide evidence of their\neffectiveness.\nWe have now included the effectiveness of the optogenetic viruses as % co-expression\nof the viruses used in the revised manuscript in lines 94-98, 278-283 and 305-310 and\nSupplementary Fig. 1, 11, 12 for the supportive histology.\n11. Definitions or explanations of key terms (e.g., \"GABAergic efferent neurons\") could be\nincluded for non-specialist readers.\nsignal to other regions of the brain, such as hypothalamic KNDy, as GABA efferent\nneurons. For clarity we have described these as efferent projection neurons in the\nrevised manuscript. See revised lines 161-162 and 175-178.\n12. For critical experiments (e.g., optogenetic activation of GABAergic neurons leading to LH\npulse suppression), increasing control group sample size could improve statistical power.\nAs suggested by the reviewer, additional experiments have been conducted to improve\nstatistical power. See revised Figures 5 and 6.\n13. Some conclusions (e.g., identifying GABAergic neurons as downstream targets of UCN3\nsignaling) could be further discussed in the context of physiological and pathological\nconditions.\nWe appreciate the reviewer’s recommendation and have added the appropriate text.\nSee lines 480-484.\n14. The classification of GABAergic neurons (e.g., efferent vs. interneurons) within the MePD\ncould be discussed further for its broader applicability to other brain regions.\nWe discuss the diversity of GABA neurons within the MePD and the relevance of our\nfindings and modelling work to other brain regions (see lines 445–450).\n15. Additional discussion on the practical implications of these findings for reproductive health\n(e.g., stress-related infertility) could strengthen the manuscript.\nWe appreciate the reviewer’s recommendation and have added the appropriate text.\nSee lines 494-498.\nWe would like to thank the reviewers for their further comments on our manuscript. We have\ncarefully considered all the feedback and have provided point-by-point responses below in\nbold text. Where appropriate, we have revised the manuscript accordingly to address the\nreviewers’ suggestions.\nReviewer 1 (Remarks to the Author):\nThe revised manuscript by Yu and colleagues addresses several of my points raised in the\nfirst round of review. However, I still have some concerns which are noted below.\nAs noted in the first round of review, circuit mapping experiments are essential to define the\nconnectivity between MePD neurons. I appreciate that this cannot be achieved for this\ncurrent paper. However, if the arrangement MePD circuit cannot be confirmed by circuit\nmapping, this limits the conclusions which can be drawn. Parallel to this, I think that\ngraphical representation of the MePD circuit shown in Figures 3 and 4 are misleading. While\nI appreciate these diagrams refer to the mathematical model, many readers will also assume\nthey apply to the biological circuit. My concerns include the fact that UNC3 neurons co-\nrelease other fast neurotransmitters and that this is not shown in the diagrams/model or\ndiscussed in terms of its importance for circuit function. The fact that UNC3 optogenetic\nsimulation effects will be partly mediated by these co-transmitters is also not discussed\nsufficiently.\nResponse: We thank the reviewer for the useful comments. We agree that, in the\nabsence of circuit-mapping data, the precise arrangement of MePD connections\ncannot be conclusively established, and we have taken steps to ensure that our\nmodeling framework is not misinterpreted as a direct anatomical claim. We have\nrevised the captions for Figures 3 and 4 to state explicitly that these diagrams\nrepresent the in-silico model architecture rather than experimentally validated\nconnectivity.\nAdditionally, to clarify how input of the UCN3 neurons is modeled we describe\nbiological interpretation of the input function in the methods section. The\ndescription includes a fast excitatory component, representing potential co-\nrelease of fast neurotransmitters, and a slow component reflecting neuropeptide\nrelease (lines 816-818). We note it in results as well (lines 196-198). We have\nincorporated text in the Discussion addressing the potential role of fast excitatory\nneurotransmitters co-release for the MePD circuit function (lines 457-467). To\nfurther avoid the confusion between the mathematical abstraction and the\nbiological circuit, we now include an additional figure (Figure 7) that illustrates a\nplausible MePD circuit organisation based on current experimental evidence. We\nalso added text in the discussion that addresses potential co-release of GABA\nneurotransmitters that is prompted by our statistical analysis (lines 505-507).\nThank you for providing more details on how the miniscope imaging was analysed. It would\nalso be informative if the authors could include the number of neurons analysed for each\nanimal in each experiment, as well as the number of cells excluded from Ca2+ imaging\nanalysis for each experiment.\nResponse: We thank the reviewer for this helpful suggestion. We have now\nincluded Supplementary Table 1 and 2, that summarize the number of neurons\nidentified for each animal and each trial for stimulation and restraint, respectively.\nFor stimulation condition we also provide the number of neurons that were\nexcluded from our analysis based on our filtering criteria for co-expression of\nUCN3 and GABA (Supplementary Table 1).\nI noticed in the revised manuscript (Figure 1J, Supp Fig 7, 8) that multiple trials of the same\nmanipulation were performed in the same mouse. It appears that these are being treated as\nindependent samples for statistical purposes. Is that correct? If so, it would be best to repeat\nthe statistical analysis of these data with each animal contributing a single data point. Also,\nthe repetition number for each animal varies. Animal G37 was stressed twice but not other\nanimals? Animal G8 had 4 optogenetic experiments, but animal G7 only had 2. The rationale\nfor this was not explained.\nResponse: We thank the reviewer for these thoughtful comments. We have now\nrevised the analysis using a mixed-effects model, which accounts for the fact that\nmultiple trials were performed on the same animal (lines 787-793), and Figure 1\nhas been updated accordingly. Due to the complexity of the experimental setup, it\nwas not always possible to obtain the same number of experimental trials from\neach animal. Our aim was to conduct at least two independent stimulation trials\nper animal, with a maximum of four trials, we indicate it in the text (lines 663-665).\nFor the stress protocol, we performed a single trial per animal to minimize\nunnecessary distress, in line with the 3Rs principle. However, in the case of\nanimal G37, the restraint stress was applied twice to assess whether this limited\nrepetition would result in any habituation. As no habituation was observed, we\ndecided to include the repeated trial in our analysis. These details have now been\nincluded in the Methods section (lines 673-675).\nIn the revised text, it is stated that “Heatmaps of calcium activity (ΔF/F0) (left) in response to\noptogenetic stimulation of UCN3 neurons excluding GABA cells co-expressing UCN3 (see\nSupplementary Fig. 2) and (right) during restraint-induced stress.”\nI found this sentence hard to interpret. In the text, please add additional clarification that the\noptogenetic stimulation will target both UNC3 and UNC3+GABA co-expressing neurons.\nPlease also provide addition clarification that the populations of neurons captured in the two\nimaging experiments (panel H vs Panel I) will be different.\nResponse: The sentence has now been revised for clarity and to explicitly state\nthat the neuronal populations in the two cases are distinct, with the number of\nneurons involved in each case noted (lines 134-138).\nThe new data presented in the revised manuscript shows that “Varying the frequency of\noptogenetic stimulation of UCN3 neurons influenced the functional connectivity within the\nGABA network (Supplementary Fig. 7). Stimulation at 5 Hz produced no significant change\ncompared with controls, 10 Hz resulted in a statistically significant increase, while 20 Hz\nreduced the effect, consistent with a depolarization block.” The authors provide no evidence\nthat 20Hz stimulation will induce a depolarisation block and I suggest that this statement is\nremoved. Instead, this data calls into question whether certain\nneurotransmitters/neuropeptides are being released preferentially at these higher\nfrequencies of stimulation.\nResponse: We thank the reviewer for their helpful comment. The text has been\nmodified to address these issues (lines 161-164). Additionally, we added\ndiscussion regarding the involvement of potential\nneurotransmitters/neuropeptides (457-467, 505-508).\nThank you for reporting the additional LH data in supplementary Table 3. It would be great to\nalso include the statistical comparisons for this data.\nResponse: We thank the reviewer for your suggestion. Supplementary Tables 5\nand 6 have been updated to indicate statistically significant differences.\nReviewer 2 (Remarks to the Author):\nI thank the authors for this thorough revision, which has substantially improved the\nmanuscript in terms of rigour, transparency, and clarity. I have only a few relatively minor\ncomments remaining.\n1) The similarity of the effects of stress and UCN3 stimulation on GABA neurons appears to\nbe a central point of the study, and the causal involvement of GABAergic neurons in the\nstress cascade is suggested throughout the manuscript. However, I am not entirely\nconvinced that this is discussed in a sufficiently balanced way, especially given the\nadditional analyses and examples now included. The authors refer to a “comparable network\nreconfiguration”, and while the similarity in the anticorrelated clusters is indeed clear, the\neffects on overall activity (i.e. ΔF/F) appear less consistent. For example, in Fig. 1A and 1K,\nstress induces a substantial increase in activity, whereas UCN3 stimulation produces very\nlimited or virtually no increase. In any case, activity during stress seems 20-fold higher than\nUCN3 stimulation. In Fig. 2B, the increase following UCN3 stimulation seems more\nsubstantial. If the “rate” of GABA neurons is clearly less enhanced by UCN3 stimulation than\nby stress, this discrepancy should be acknowledged and discussed, rather than assuming\nthat the network state is entirely comparable. Potential explanations could include technical\nfactors, or additional biological mechanisms such as neuromodulators released during stress\nbut not during isolated UCN3 stimulation. As I mentioned in my earlier review, a direct way to\nassess causality would be to silence UCN3 neurons during stress to test whether GABAergic\nactivation and the observed clustering patterns are abolished. While such an experiment is\nbeyond the current scope, suggesting this approach in the Discussion should strengthen the\nmanuscript.\nResponse: We thank the reviewer for this constructive comment. We have now\nexpanded the Discussion to acknowledge that the overall magnitude of\nGABAergic activity (ΔF/F₀) differs between stress and UCN3 stimulation, despite\nthe comparable network reconfiguration observed (lines 423-428).\nFurthermore, we have added your suggestion that future studies could directly\ntest the causal role of UCN3 neurons by silencing them during stress exposure\n(lines 483-485).\n2) 119. Given what you are comparing, shouldn’t the sentence read: “Furthermore, stress\ninduces a SIGNIFICANTLY HIGHER population time-averaged calcium activity than UCN3\nstimulation”\nResponse: Text has been revised accordingly (lines 124-125).\n3) The label “opsin stimulation” is still present in Fig.3. Please replace with “stimulation”.\nResponse: We thank the reviewer for pointing it out, the figure 3 has been revised\naccordingly.\nOverall, I believe the paper is close to acceptance, and a fairer treatment of point 3 above\nwill further enhance its clarity, transparency and impact.\nReviewer #2 (Remarks on code availability):\nI have not tested the code, but it appears well organised and clearly explained.\nResponse: Thank you for this positive comment. We appreciate the reviewer’s\nassessment that the code is well organised and clearly explained.\nReviewer #3 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This\nis part of the Nature Communications initiative to facilitate training in peer review and to\nprovide appropriate recognition for Early Career Researchers who co-review manuscripts.\nResponse: Thank you very much.\nReviewer #4 (Remarks to the Author):\nThe authors have convincingly addressed the revisions requested in my previous\nassessment. I have no further concerns.\nResponse: Thank you for this positive appraisal of our manuscript."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The revised manuscript by Yu and colleagues addresses several of my points raised in the first round of review. However, I still have some concerns which are noted below.\nAs noted in the first round of review, circuit mapping experiments are essential to define the connectivity between MePD neurons. I appreciate that this cannot be achieved for this current paper. However, if the arrangement MePD circuit cannot be confirmed by circuit mapping, this limits the conclusions which can be drawn. Parallel to this, I think that graphical representation of the MePD circuit shown in Figures 3 and 4 are misleading. While I appreciate these diagrams refer to the mathematical model, many readers will also assume they apply to the biological circuit. My concerns include the fact that UNC3 neurons co-release other fast neurotransmitters and that this is not shown in the diagrams/model or discussed in terms of its importance for circuit function. The fact that UNC3 optogenetic simulation effects will be partly mediated by these co-transmitters is also not discussed sufficiently.\nThank you for providing more details on how the miniscope imaging was analysed. It would also be informative if the authors could include the number of neurons analysed for each animal in each experiment, as well as the number of cells excluded from Ca2+ imaging analysis for each experiment.\nI noticed in the revised manuscript (Figure 1J, Supp Fig 7, 8) that multiple trials of the same manipulation were performed in the same mouse. It appears that these are being treated as independent samples for statistical purposes. Is that correct? If so, it would be best to repeat the statistical analysis of these data with each animal contributing a single data point. Also, the repetition number for each animal varies. Animal G37 was stressed twice but not other animals? Animal G8 had 4 optogenetic experiments, but animal G7 only had 2. The rationale for this was not explained.\nIn the revised text, it is stated that “Heatmaps of calcium activity (ΔF/F0) (left) in response to optogenetic stimulation of UCN3 neurons excluding GABA cells co-expressing UCN3 (see Supplementary Fig. 2) and (right) during restraint-induced stress.”\nI found this sentence hard to interpret. In the text, please add additional clarification that the optogenetic stimulation will target both UNC3 and UNC3+GABA co-expressing neurons. Please also provide addition clarification that the populations of neurons captured in the two imaging experiments (panel H vs Panel I) will be different.\nThe new data presented in the revised manuscript shows that “Varying the frequency of optogenetic stimulation of UCN3 neurons influenced the functional connectivity within the GABA network (Supplementary Fig. 7). Stimulation at 5 Hz produced no significant change compared with controls, 10 Hz resulted in a statistically significant increase, while 20 Hz reduced the effect, consistent with a depolarization block.”\nThe authors provide no evidence that 20Hz stimulation will induce a depolarisation block and I suggest that this statement is removed. Instead, this data calls into question whether certain neurotransmitters/neuropeptides are being released preferentially at these higher frequencies of stimulation.\nThankyou for reporting the additional LH data in supplementary Table 3. It would be great to also include the statistical comparisons for this data.", "reviewer_2": "I thank the authors for this thorough revision, which has substantially improved the manuscript in terms of rigour, transparency, and clarity. I have only a few relatively minor comments remaining.\n1) The similarity of the effects of stress and UCN3 stimulation on GABA neurons appears to be a central point of the study, and the causal involvement of GABAergic neurons in the stress cascade is suggested throughout the manuscript. However, I am not entirely convinced that this is discussed in a sufficiently balanced way, especially given the additional analyses and examples now included. The authors refer to a “comparable network reconfiguration”, and while the similarity in the anticorrelated clusters is indeed clear, the effects on overall activity (i.e. ΔF/F) appear less consistent. For example, in Fig. 1A and 1K, stress induces a substantial increase in activity, whereas UCN3 stimulation produces very limited or virtually no increase. In any case, activity during stress seems 20-fold higher than UCN3 stimulation. In Fig. 2B, the increase following UCN3 stimulation seems more substantial. If the “rate” of GABA neurons is clearly less enhanced by UCN3 stimulation than by stress, this discrepancy should be acknowledged and discussed, rather than assuming that the network state is entirely comparable. Potential explanations could include technical factors, or additional biological mechanisms such as neuromodulators released during stress but not during isolated UCN3 stimulation. As I mentioned in my earlier review, a direct way to assess causality would be to silence UCN3 neurons during stress to test whether GABAergic activation and the observed clustering patterns are abolished. While such an experiment is beyond the current scope, suggesting this approach in the Discussion could strengthen the manuscript.\n2) 119. Given what you are comparing, shouldn’t the sentence read: “Furthermore, stress induces a SIGNIFICANTLY HIGHER population time-averaged calcium activity than UCN3 stimulation”\n3) The label “opsin stimulation” is still present in Fig.3. Please replace with “stimulation”.\nOverall, I believe the paper is close to acceptance, and a fairer treatment of point 3 above will further enhance its clarity, transparency and impact.", "reviewer_3": "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_4": "The authors have convincingly addressed the revisions requested in my previous assessment. I have no further concerns."}, "author_response": "Responses to reviewers’ comments\nWe would like to thank the reviewers for their further comments on our manuscript. We have\ncarefully considered all the feedback and have provided point-by-point responses below in\nbold text. Where appropriate, we have revised the manuscript accordingly to address the\nreviewers’ suggestions.\nReviewer 1 (Remarks to the Author):\nThe revised manuscript by Yu and colleagues addresses several of my points raised in the\nfirst round of review. However, I still have some concerns which are noted below.\nAs noted in the first round of review, circuit mapping experiments are essential to define the\nconnectivity between MePD neurons. I appreciate that this cannot be achieved for this\ncurrent paper. However, if the arrangement MePD circuit cannot be confirmed by circuit\nmapping, this limits the conclusions which can be drawn. Parallel to this, I think that\ngraphical representation of the MePD circuit shown in Figures 3 and 4 are misleading. While\nI appreciate these diagrams refer to the mathematical model, many readers will also assume\nthey apply to the biological circuit. My concerns include the fact that UNC3 neurons co-\nrelease other fast neurotransmitters and that this is not shown in the diagrams/model or\ndiscussed in terms of its importance for circuit function. The fact that UNC3 optogenetic\nsimulation effects will be partly mediated by these co-transmitters is also not discussed\nsufficiently.\nResponse: We thank the reviewer for the useful comments. We agree that, in the\nabsence of circuit-mapping data, the precise arrangement of MePD connections\ncannot be conclusively established, and we have taken steps to ensure that our\nmodeling framework is not misinterpreted as a direct anatomical claim. We have\nrevised the captions for Figures 3 and 4 to state explicitly that these diagrams\nrepresent the in-silico model architecture rather than experimentally validated\nconnectivity.\nAdditionally, to clarify how input of the UCN3 neurons is modeled we describe\nbiological interpretation of the input function in the methods section. The\ndescription includes a fast excitatory component, representing potential co-\nrelease of fast neurotransmitters, and a slow component reflecting neuropeptide\nrelease (lines 816-818). We note it in results as well (lines 196-198). We have\nincorporated text in the Discussion addressing the potential role of fast excitatory\nneurotransmitters co-release for the MePD circuit function (lines 457-467). To\nfurther avoid the confusion between the mathematical abstraction and the\nbiological circuit, we now include an additional figure (Figure 7) that illustrates a\nplausible MePD circuit organisation based on current experimental evidence. We\nalso added text in the discussion that addresses potential co-release of GABA\nneurotransmitters that is prompted by our statistical analysis (lines 505-507).\nThank you for providing more details on how the miniscope imaging was analysed. It would\nalso be informative if the authors could include the number of neurons analysed for each\nanimal in each experiment, as well as the number of cells excluded from Ca2+ imaging\nanalysis for each experiment.\nResponse: We thank the reviewer for this helpful suggestion. We have now\nincluded Supplementary Table 1 and 2, that summarize the number of neurons\nidentified for each animal and each trial for stimulation and restraint, respectively.\nFor stimulation condition we also provide the number of neurons that were\nexcluded from our analysis based on our filtering criteria for co-expression of\nUCN3 and GABA (Supplementary Table 1).\nI noticed in the revised manuscript (Figure 1J, Supp Fig 7, 8) that multiple trials of the same\nmanipulation were performed in the same mouse. It appears that these are being treated as\nindependent samples for statistical purposes. Is that correct? If so, it would be best to repeat\nthe statistical analysis of these data with each animal contributing a single data point. Also,\nthe repetition number for each animal varies. Animal G37 was stressed twice but not other\nanimals? Animal G8 had 4 optogenetic experiments, but animal G7 only had 2. The rationale\nfor this was not explained.\nResponse: We thank the reviewer for these thoughtful comments. We have now\nrevised the analysis using a mixed-effects model, which accounts for the fact that\nmultiple trials were performed on the same animal (lines 787-793), and Figure 1\nhas been updated accordingly. Due to the complexity of the experimental setup, it\nwas not always possible to obtain the same number of experimental trials from\neach animal. Our aim was to conduct at least two independent stimulation trials\nper animal, with a maximum of four trials, we indicate it in the text (lines 663-665).\nFor the stress protocol, we performed a single trial per animal to minimize\nunnecessary distress, in line with the 3Rs principle. However, in the case of\nanimal G37, the restraint stress was applied twice to assess whether this limited\nrepetition would result in any habituation. As no habituation was observed, we\ndecided to include the repeated trial in our analysis. These details have now been\nincluded in the Methods section (lines 673-675).\nIn the revised text, it is stated that “Heatmaps of calcium activity (ΔF/F0) (left) in response to\noptogenetic stimulation of UCN3 neurons excluding GABA cells co-expressing UCN3 (see\nSupplementary Fig. 2) and (right) during restraint-induced stress.”\nI found this sentence hard to interpret. In the text, please add additional clarification that the\noptogenetic stimulation will target both UNC3 and UNC3+GABA co-expressing neurons.\nPlease also provide addition clarification that the populations of neurons captured in the two\nimaging experiments (panel H vs Panel I) will be different.\nResponse: The sentence has now been revised for clarity and to explicitly state\nthat the neuronal populations in the two cases are distinct, with the number of\nneurons involved in each case noted (lines 134-138).\nThe new data presented in the revised manuscript shows that “Varying the frequency of\noptogenetic stimulation of UCN3 neurons influenced the functional connectivity within the\nGABA network (Supplementary Fig. 7). Stimulation at 5 Hz produced no significant change\ncompared with controls, 10 Hz resulted in a statistically significant increase, while 20 Hz\nreduced the effect, consistent with a depolarization block.” The authors provide no evidence\nthat 20Hz stimulation will induce a depolarisation block and I suggest that this statement is\nremoved. Instead, this data calls into question whether certain\nneurotransmitters/neuropeptides are being released preferentially at these higher\nfrequencies of stimulation.\nResponse: We thank the reviewer for their helpful comment. The text has been\nmodified to address these issues (lines 161-164). Additionally, we added\ndiscussion regarding the involvement of potential\nneurotransmitters/neuropeptides (457-467, 505-508).\nThank you for reporting the additional LH data in supplementary Table 3. It would be great to\nalso include the statistical comparisons for this data.\nResponse: We thank the reviewer for your suggestion. Supplementary Tables 5\nand 6 have been updated to indicate statistically significant differences.\nReviewer 2 (Remarks to the Author):\nI thank the authors for this thorough revision, which has substantially improved the\nmanuscript in terms of rigour, transparency, and clarity. I have only a few relatively minor\ncomments remaining.\n1) The similarity of the effects of stress and UCN3 stimulation on GABA neurons appears to\nbe a central point of the study, and the causal involvement of GABAergic neurons in the\nstress cascade is suggested throughout the manuscript. However, I am not entirely\nconvinced that this is discussed in a sufficiently balanced way, especially given the\nadditional analyses and examples now included. The authors refer to a “comparable network\nreconfiguration”, and while the similarity in the anticorrelated clusters is indeed clear, the\neffects on overall activity (i.e. ΔF/F) appear less consistent. For example, in Fig. 1A and 1K,\nstress induces a substantial increase in activity, whereas UCN3 stimulation produces very\nlimited or virtually no increase. In any case, activity during stress seems 20-fold higher than\nUCN3 stimulation. In Fig. 2B, the increase following UCN3 stimulation seems more\nsubstantial. If the “rate” of GABA neurons is clearly less enhanced by UCN3 stimulation than\nby stress, this discrepancy should be acknowledged and discussed, rather than assuming\nthat the network state is entirely comparable. Potential explanations could include technical\nfactors, or additional biological mechanisms such as neuromodulators released during stress\nbut not during isolated UCN3 stimulation. As I mentioned in my earlier review, a direct way to\nassess causality would be to silence UCN3 neurons during stress to test whether GABAergic\nactivation and the observed clustering patterns are abolished. While such an experiment is\nbeyond the current scope, suggesting this approach in the Discussion should strengthen the\nmanuscript.\nResponse: We thank the reviewer for this constructive comment. We have now\nexpanded the Discussion to acknowledge that the overall magnitude of\nGABAergic activity (ΔF/F₀) differs between stress and UCN3 stimulation, despite\nthe comparable network reconfiguration observed (lines 423-428).\nFurthermore, we have added your suggestion that future studies could directly\ntest the causal role of UCN3 neurons by silencing them during stress exposure\n(lines 483-485).\n2) 119. Given what you are comparing, shouldn’t the sentence read: “Furthermore, stress\ninduces a SIGNIFICANTLY HIGHER population time-averaged calcium activity than UCN3\nstimulation”\nResponse: Text has been revised accordingly (lines 124-125).\n3) The label “opsin stimulation” is still present in Fig.3. Please replace with “stimulation”.\nResponse: We thank the reviewer for pointing it out, the figure 3 has been revised\naccordingly.\nOverall, I believe the paper is close to acceptance, and a fairer treatment of point 3 above\nwill further enhance its clarity, transparency and impact.\nReviewer #2 (Remarks on code availability):\nI have not tested the code, but it appears well organised and clearly explained.\nResponse: Thank you for this positive comment. We appreciate the reviewer’s\nassessment that the code is well organised and clearly explained.\nReviewer #3 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This\nis part of the Nature Communications initiative to facilitate training in peer review and to\nprovide appropriate recognition for Early Career Researchers who co-review manuscripts.\nResponse: Thank you very much.\nReviewer #4 (Remarks to the Author):\nThe authors have convincingly addressed the revisions requested in my previous\nassessment. I have no further concerns.\nResponse: Thank you for this positive appraisal of our manuscript."}, {"round": 3, "reviewer_comments": {"reviewer_1": "The authors have addressed my previous comments. I have no further concerns."}, "author_response": ""}]

Decision letter