Author response: Complementary networks of cortical somatostatin interneurons enforce layer specific control (2019)

Article Figures and data Abstract Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract The neocortex is functionally organized into layers. Layer four receives the densest bottom up sensory inputs, while layers 2/3 and 5 receive top down inputs that may convey predictive information. A subset of cortical somatostatin (SST) neurons, the Martinotti cells, gate top down input by inhibiting the apical dendrites of pyramidal cells in layers 2/3 and 5, but it is unknown whether an analogous inhibitory mechanism controls activity in layer 4. Using high precision circuit mapping, in vivo optogenetic perturbations, and single cell transcriptional profiling, we reveal complementary circuits in the mouse barrel cortex involving genetically distinct SST subtypes that specifically and reciprocally interconnect with excitatory cells in different layers: Martinotti cells connect with layers 2/3 and 5, whereas non-Martinotti cells connect with layer 4. By enforcing layer-specific inhibition, these parallel SST subnetworks could independently regulate the balance between bottom up and top down input. https://doi.org/10.7554/eLife.43696.001 Introduction The neocortex is divided across its vertical axis into discrete layers. Excitatory principal cells (PCs) in each layer differentially encode and process sensory information (Feldmeyer, 2012; Harris and Shepherd, 2015), due in part to the fact that they receive different external inputs. ‘Bottom-up’ sensory inputs primarily enter L4, while ‘top down’ inputs target PCs in supragranular and infragranular layers. The relative impact of these two main input pathways is likely to be crucial for sensory-guided behavior. Dendrite-targeting somatostatin (SST)-expressing interneurons are well known for shaping sensory coding through lateral and recurrent inhibition, and for gating top-down input by regulating dendritic spiking and synaptic plasticity (Adesnik et al., 2012; Kim, 2016; Kvitsiani et al., 2013; Makino and Komiyama, 2015; Urban-Ciecko and Barth, 2016; Kato et al., 2017; Veit et al., 2017; Adesnik, 2017). While it is well established that SST neurons send and receive synaptic connections with neurons across multiple cortical layers (Apicella et al., 2012; Jiang et al., 2015; Jiang et al., 2013; Anastasiades et al., 2016; Otsuka and Kawaguchi, 2009; Yoshimura and Callaway, 2005; Kapfer et al., 2007), it is unclear whether SST circuits impact all layers in a global manner, or if instead they selectively control specific layers, which could have profound impacts for cortical computation. Studies which have examined connectivity of SST cells (Fino and Yuste, 2011) and GABAergic interneurons more generally (Bock et al., 2011; Scholl et al., 2015; Hofer et al., 2011; Packer and Yuste, 2011) have found that inhibitory neurons interconnect with excitatory cells densely and non-selectively, which has led to the emerging hypothesis that excitatory circuits are overlaid by a ‘blanket of inhibition’. While these studies have usually focused on connectivity within a single layer, one possibility is that this principle generalizes to the rest of the circuit, meaning that SST cells wire up irrespective of layer to globally regulate cortical networks. However, the SST population is highly heterogeneous (Urban-Ciecko and Barth, 2016; Yavorska and Wehr, 2016) and can be divided into multiple subgroups of cells which exhibit distinct electrophysiological, morphological, genetic (Tasic et al., 2016), and in vivo functional properties (Kim, 2016; Kvitsiani et al., 2013; Muñoz et al., 2017; Ma et al., 2010; Reimer et al., 2014; Nakajima et al., 2014). Intriguingly, some of these subgroups target their axons to different laminar domains (Ma et al., 2006; Muñoz et al., 2014; Nigro et al., 2018), and it has been hypothesized that subgroups of SST cells might be specialized to differentially modulate the activity of specific layers (Muñoz et al., 2017), perhaps by forming distinct subnetworks. Such an architecture would allow for independent gating of different cortical pathways by complementary networks of SST interneurons. We addressed these contrasting hypotheses by combining high-resolution optogenetic circuit mapping, paired intracellular recordings, single-cell RNA sequencing, and in vivo optogenetics. With a focus on SST neurons in layer 5, the layer in which they are most numerous, we identified two distinct sub-networks of SST neurons with strikingly contrasting connectivity and in vivo function. The first sub-group of SST neurons was composed of Martinotti cells (MCs), a well-studied cell type which has classically been defined by its ascending axonal projection to L1. The second subgroup was morphologically, transcriptionally, and synaptically distinct from MCs and composed of SST neurons that primarily target L4 instead of L1. The connectivity and function of this second sub-class of SST neurons, which have sometimes been referred to simply as ‘non-Martinotti’ cells or ‘NMCs’ (Muñoz et al., 2017; Ma et al., 2006; Nigro et al., 2018), are largely unknown. Our data on L5 SST neurons show that these two SST subgroups comprise highly distinct inhibitory subnetworks that exhibit exquisitely specific and strikingly complementary laminar patterns of connectivity and in vivo impact. MCs receive input from L2/3 and L5, whereas NMCs receive input from L4 and the L5B/L6 border. In turn, MCs provide reciprocal inhibition to PCs in L5 but not to those in L4, while NMCs selectively inhibit PCs in L4. Optogenetically activating MCs and NMCs in vivo results in extremely distinct laminar patterns of suppression, suggesting they may have contrasting roles in sensory computation and behavior. Single-cell RNA sequencing on >2000 individual SST neurons revealed transcriptomically defined SST sub-classes that showed distinct somal lamination profiles across the cortical range of depth. Taken together, these results demonstrate that of these, two major subgroups of cortical SST cells, by virtue of their layer-selective synaptic connectivity, can independently modulate the activity of different cortical layers during sensation. This highly selective synaptic and functional architecture supports a model in which distinct sub-networks of SST neurons may fine tune the balance of activity across the layers of the neocortex. Results Two distinct sub-networks of SST neurons defined by layer-specific connectivity To probe the synaptic architecture of SST circuits, we employed a combination of one and two photon optogenetics, single cell reconstructions, and paired recording. To make targeted recordings from SST neurons belonging to putatively different sub-classes, we took advantage of transgenic reporter mouse lines that label either all SST neurons (Sst-IRES-Cre) (Taniguchi et al., 2011), or different anatomical sub-classes of SST neurons in the barrel cortex (GIN, X94, and X98) (Ma et al., 2006; Oliva et al., 2000). We focused our investigation on SST neurons in L5 which harbors a large and diverse population of SST cells (Markram et al., 2004; Rudy et al., 2011). Consistent with prior data, the anatomy and intrinsic physiology of L5 GIN cells demonstrated that they are MCs (41/44; 93%; Figure 1a and Figure 1—figure supplement 1) (Wang et al., 2004; Kawaguchi, 1993; Fanselow et al., 2008; Kinnischtzke et al., 2012). By similar analyses, neurons in the X94 line were non-Martinotti cells (32/35; 91%), which formed a dense axonal plexus in L4 rather than L1 (Figure 1a, Figure 1—figure supplement 2) and exhibited quasi-fast-spiking electrophysiological phenotypes (Figure 1b, Figure 1—figure supplement 1). While the X94 line labels only ~15% of SST cells in L5 (Ma et al., 2006), additional recordings from L5 SST-TdT cells suggested that the X94 line subsamples the NMC population (consistent with a previous report) since 30–40% of recorded L5 SST cells exhibited an NMC phenotype (Figure 1—figure supplement 1c–g). Aligning biocytin reconstructions of L5 MCs and NMCs revealed that these two populations have strikingly complementary vertical profiles of neurite density: MCs primarily innervated layers 1, 2/3 and 5, and NMCs primarily innervated L4 and the L5/L6 border (Figure 1c). Although some is known about their differing anatomical and physiological features (Muñoz et al., 2017; Ma et al., 2006; Nigro et al., 2018), relatively little is understood about how these two sub-classes of SST neurons, especially NMCs, might differentially integrate into and influence the cortical excitatory network. Figure 1 with 4 supplements see all Download asset Open asset Optogenetic circuit mapping reveals complementary synaptic input patterns to two subtypes of L5 SST cells. (A) Confocal images of dye filled neurons revealing two morphological phenotypes of L5 SST cells. Left: an L5 GIN cell. Right: an L5 × 94 cell. Scale bar: 200 µm. (B) Example traces during current step injections from an L5 GIN cell (black) and an L5 × 94 cell (red). (C) Left: Overlaid morphological reconstructions of L5 GIN/MC cells (black, n = 14) and L5 × 94/NMCs (red, n = 10) showing differences in laminar distribution of neurites. Right: Normalized neurite density versus cortical depth for L5 GIN (black) and L5 × 94 cells (red). Data are represented as mean ±C.I. Note that these reconstructions do not distinguish between axon and dendrite; for detailed morphological analysis of these cells, see (Ma et al., 2006) (D) Schematic of experimental configuration. A digital micromirror device was used to focally photo-stimulate excitatory cells in different regions of the slice in order to map the spatial profile of excitatory inputs to GFP +L5 MCs (Emx1-Cre; GIN) or GFP +L5 NMCs (Emx1-Cre; X94). (E) Example heat maps of median EPSC charge transfer evoked at each stimulus site for example L5 SST cells. Left: An L5 MC that received inputs from L5 and L2/3. Right: An L5 NMC that received inputs from L4 and the L5/6 border. Soma locations are indicated by red/black bordered white dot). Scale bar: 200 µm. (F) Left: Grand averages of input maps reveal cell-type specific patterns of laminar input. Soma locations are indicated as above. Right: Normalized charge transfer versus distance from L4-L5 border for MC (black) and NMC (red) populations. Scale bar: 200 µm. Inset: Swarm plots showing the proportion of total evoked charge transfer in each map that originated from sites in L4 +L6, that is [L4+L6] / [L2/3+L4+L5+L6] for the MC (black; median, 27%; range, 13–36%) and NMC (red; median, 62%; range, 38–84%) populations. Proportions were significantly different between L5 MCs and L5 NMCs (25 ± 3% in n = 15 MCs versus 62 ± 7% in n = 14 NMCs, mean ±C.I.; p=6.5 · 10−10; two-sample t-test). See also Figure 1—figure supplement 1–4. https://doi.org/10.7554/eLife.43696.002 To begin to answer this question, we first asked whether MCs and NMCs receive different patterns of excitatory inputs across the cortical layers. We transgenically expressed ChR2 in cortical excitatory neurons across all layers, and used scanning photostimulation to map the spatial profile of excitatory inputs to NMCs and MCs (Figure 1d,e,f; Figure 1—figure supplement 4). Remarkably, we found that L5 MCs and NMCs receive inputs from highly specific and largely non-overlapping sources. MCs, but not NMCs, frequently received excitatory input from either upper L5, L2/3, or from both L2/3 and L5, but received little input from L4 or L6, broadly consistent with prior studies (Apicella et al., 2012; Jiang et al., 2015; Anastasiades et al., 2016; Kapfer et al., 2007). In contrast, NMCs received strong input from L4 and/or the L5B/L6 border (Figure 1e,f; input from L4 and L6 was 62 ± 7% of total input for n = 14 NMCs versus 25 ± 3% for n = 15 MCs; p=6.5 · 10−10; two sample T-test; see also Figure 1—figure supplement 3) but relatively little input from L2/3 and L5. Thus, L5 MCs and NMCs appear to receive distinct and complementary patterns of excitatory innervation. An important caveat to these experiments is that our optogenetic stimulation did not recruit the same amount of activity in excitatory neurons across different layers (Figure 1—figure supplement 4f), presumably due to differences in intrinsic excitability or opsin expression levels. Although this makes it difficult to assess the relative strength of laminar input pathways in an absolute sense, stimulation of sites in non-preferred layers (e.g. stimulating L2/3 while recording from an L5 NMC) almost never evoked a response that was significantly greater than the background level of EPSCs, except at sites which were close to the borders between layers (Figure 1—figure supplement 3k). This suggests that input from most sites in non-preferred layers (L4 and L6 for MCs, L2/3 and L5A for NMCs) was either absent or too small to be detected via this method. The striking laminar differences in inputs to NMCs and MCs suggested that they might be differentially recruited by activity of different cortical layers. To test this possibility, we specifically photo-stimulated L4 excitatory neurons via Cre-dependent expression of ChR2 in Scnn1-Cre mice (crossed to GIN or X94; Figure 2a). L4-specific photo-stimulation (with two different stimulus protocols, across four different intensities) drove large EPSCs in NMCs but evoked little to no input in MCs under identical conditions (Figure 2b,c; Figure 2—figure supplement 1). Current clamp recordings under the same conditions showed that L4 photo-stimulation reliably drove spiking in L5 NMCs, but not in L5 MCs (Figure 2b,d; Figure 2—figure supplement 1) despite the fact that MCs are intrinsically more excitable than NMCs (Figure 1—figure supplement 1). The lack of evoked responses in MCs was not due to differences in the degree of L4 activation (see Figure 2—figure supplement 1 for controls). Thus, these results indicate a stark difference between L5 NMCs and MCs: L4 densely innervates and powerfully drives firing in L5 NMCs, but not L5 MCs. Figure 2 with 1 supplement see all Download asset Open asset L4 photo-stimulation excites L5 NMCs but not L5 MCs. (A) Top: Schematic of the experimental configuration. L5 × 94 or GIN cells were recorded during photo-stimulation of L4 excitatory neurons. Bottom: Confocal image of a filled L5 × 94 neuron (white) with ChR2-TdTomato expression (red) visible in L4. Scale bar: 150 µm. (B) Top row: Example traces recorded in the current clamp (upper traces) or voltage clamp (lower traces) configurations during a 1 s ramp photo-stimulation. Bottom row: As above, but for photo-stimulation with a 40 Hz train of ten 1 ms pulses. (C) Quantification of excitatory charge transfer during maximum intensity 1 s ramp stimulation trials. Mean 122 ± 41 pC in n = 20 NMCs versus 15 ± 8 pC in n = 15 MCs; p=3.9 · 10−6, Wilcoxon rank sum test. (D) Quantification of the mean number of evoked action potentials during maximum intensity 1 s ramp stimulation trials. Mean 8.1 ± 5.5 spikes per trial in n = 15 NMCs versus 0.03 ± 0.05 spikes per trial in n = 15 MCs; p=6.6 · 10−4, Wilcoxon rank sum test. (E) As in C, for maximum intensity 40 Hz pulse train stimulation. Mean 200 ± 56 pA in n = 20 NMCs versus 18 ± 12 pA in n = 15 MCs; p=2.8 · 10−6, Wilcoxon rank sum test. (F) As in D, for maximum intensity 40 Hz pulse train stimulation. Mean 8.7 ± 2.4 spikes per trial in n = 15 NMCs versus 0.5 ± 0.9 spikes per trial in n = 15 MCs; p=1.5 · 10−6, Wilcoxon rank sum test. Error bars denote mean ±95% confidence interval. Three asterisks denotes p<0.001. https://doi.org/10.7554/eLife.43696.007 Common input mapping reveals subnetwork structure in L5 SST cell output We next asked whether NMCs and MCs also exhibit layer-specificity in their inhibitory outputs. Since SST cells have been implicated in generating feedback inhibition (Adesnik et al., 2012; Kapfer et al., 2007; Silberberg and Markram, 2007), we hypothesized that MCs and NMCs might target their inhibitory outputs in order to reciprocally inhibit the same PC populations that excite them. For example, NMCs but not MCs would inhibit L4 PCs, whereas MCs but not NMCs would inhibit L5 PCs. Alternatively, MCs, NMCs, or both cell types could globally target PCs within and across layers non-selectively. To address this, we used two photon optogenetic circuit mapping to determine whether the outputs of individual SST cells (in the non-specific SST-Cre line) diverge onto PCs in multiple layers. If individual SST cells target either L4 or L5 PCs, but not both, then we should never observe common input to pairs of L4 and L5 PCs when photo-stimulating single SST neurons. This can be tested by mapping optogenetically evoked unitary SST inhibitory connections onto multiple PCs recorded simultaneously and analyzing the spatiotemporal coincidence of evoked IPSCs onto different pairs of PCs, thereby measuring the amount of common input shared between pairs of PCs in different layers (Yoshimura et al., 2005; Morgenstern et al., 2016), (Merel et al., 2016). Although this approach does not discriminate between MCs and NMCs directly, it performs a more stringent test by extending our hypothesis to apply to the structure of the outputs of the L5 SST population as a whole, rather than the sparser subsets set labeled in the GFP lines. To maximize the spatial precision of photo-stimulation we used a soma-targeted opsin (Figure 3a,b,c) (Baker et al., 2016) and computer-generated holography (Figure 3a,b; Figure 3—figure supplement 1a). Since SST → PC synapses are often located on the distal dendrites of PCs, we recorded IPSCs using a cesium-based internal solution, and took additional steps to minimize false negatives (see Materials and methods). Using this method, we simultaneously mapped SST inputs to pairs of L4-L5 PCs and L5-L5 PCs (Figure 3d,e,f; Figure 3—figure supplement 2f). Figure 3 with 2 supplements see all Download asset Open asset two photon optogenetic circuit mapping reveals that L4 and L5 PCs are inhibited by separate populations of L5 SST cells. (A) Schematic of the experimental configuration. IPSCs are recorded from a pair of PCs (either an L4/L5 pair or an L5/L5 pair) while SST cells expressing soma-targeted ChrimsonR-mRuby2 are focally activated using 2P photo-stimulation and computer generated holography. (B) Left: post-hoc confocal image showing SST cells expressing soma-targeted-ChrimsonR-mRuby2 (red) and biocytin fills of recorded PCs in L4 and L5 (white) at 10x magnification. Right: Confocal image at 20x magnification showing the grid of photo-stimulated target locations. Both images are max z-projections over 100 μm. (C) Spatial photo-excitation profile of a soma-targeted-ChrimsonR-mRuby2 expressing SST cell. Whole cell current-clamp recordings from this cell showing multiple trials of photo-stimulation at a 4 × 4 subsection of the photo-stimulation grid with 20 μm spacing between stimulation locations. The SST cell is recruited to spike only at a small number of stimulation sites, but does so reliably and with low jitter across trials at these sites. (D) Example traces showing IPSCs recorded from an L4 PC during SST photo-stimulation at a single site (corresponding to in over multiple trials. each indicate the of detected IPSCs (E) Example of maps showing the mean number of IPSCs at detected input locations during photo-stimulation for a simultaneously recorded L4 PC the mean number of IPSCs evoked from background per (F) As in but for an L5 PC Example traces for of common inputs to pairs of simultaneously recorded PCs. Left: traces at a single site recorded simultaneously in two PCs PC is indicated by or traces) and detected IPSCs with in despite the jitter in suggesting that a SST cell which onto both recorded PCs is at this site jitter Right: traces from a different IPSCs are in both cells, but the lack of suggests they from SST cells each indicate the of detected of common SST input per photo-stimulated site for pairs of L4 PCs and L5 PCs versus pairs of two L5 PCs. common input locations were detected in n = L4-L5 pairs versus ± of all input locations locations in n = L5-L5 · Wilcoxon rank sum test Data are by mean Schematic of main for SST L5 SST cells inhibitory connections onto L4 PCs and or L5 PCs but not In L4-L5 PC pairs we little common input when photo-stimulating SST neurons, but common input in L5-L5 pairs ± inputs of all input locations in n = L4-L5 versus ± in n = L5-L5 · Wilcoxon rank sum that more than one SST cell might be at target (Figure 2—figure supplement we employed a test for fine of IPSCs between the cells at each both cells received to determine whether the IPSCs from a single SST cell onto both recorded PCs et al., Figure Figure 3—figure supplement Using this more test for the of common we detected no locations in which stimulation evoked common inputs for L4-L5 whereas we detected at one common input in of L5-L5 pairs (Figure no locations in n = L4-L5 pairs versus ± of all input locations in n = L5-L5 · Wilcoxon rank sum see also Figure 3—figure supplement data that individual L5 SST cells connect to either L4 PCs or to L5 PCs, but never to In L4 PCs and L5 PCs are inhibited by non-overlapping subnetworks of L5 SST cells. recordings show and selective and connectivity To the mapping suggested by the optogenetic data above, we paired intracellular recordings between both types of SST neurons and PCs in L4 and L5. We targeted L5 MCs and NMCs with the GIN and X94 lines as above, but also used the SST-TdT line to L5 SST cells more and SST-TdT cells as MCs or NMCs on their electrophysiological properties (Figure 1—figure supplement 1) and/or We extremely L5 NMC → L4 PC connections pairs Figure across ± mean Figure supplement suggesting that L5 NMCs connect densely onto L4. In the we also frequently excitatory connections from L4 PCs onto L5 NMCs, consistent with the optogenetic experiments pairs synapses exhibited profound during firing in the cell (Figure Figure supplement which is a of excitatory connections onto SST cells, et al., 2007; et al., et al., NMCs et al., and 2016; et al., In we tested connectivity we frequently reciprocal connections pairs Thus, L5 NMCs and L4 PCs a feedback inhibitory We also connections from L5 NMCs onto L4 cells pairs Figure supplement similar to a known circuit in which L4 non-Martinotti SST cells inhibit L4 cells (Ma et al., 2006; et al., Figure 4 with 3 supplements see all Download asset Open asset MCs and NMCs exhibit different patterns of connectivity with L4 and L5 PCs. (A) recordings of L4 PCs and L5 Left: of the tested example traces of evoked spikes in a L4 PC and the excitatory synaptic current in a L5 NMC (red). Right: example traces of evoked in a L4 PC in response to a single action in a L5 NMC (red). (B) between L4 PCs and L5 MCs and L4 PCs and L5 NMCs for = connections tested onto versus L4 NMC = connections tested onto for = connections tested from versus L5 NMC = connections tested from test. (C) As in but pairs between L5 and L5 PCs (D) As in but for connections with L5 PCs. for L5 MC = connections tested onto 20 versus L5 NMC = connections tested onto for L5 PC = connections tested from versus L5 NMC PC = connections tested from test. See also Figure supplement and 1 for MCs and NMCs recorded in different transgenic to Figure 4. show paired recording data using the GIN and X94 lines to target MCs and NMCs in L5. show the same data and data using the SST-TdT with L5 SST cells as MCs or NMCs on their intrinsic not show the number and of pairs in which a was detected for a GIN · · · · In contrast, we almost never excitatory connections from L4 PCs to L5 MCs pairs Figure or from L5 MCs onto L4 PCs pairs despite the fact that these pairs were by than L4 PC L5 NMC pairs ± mean Figure supplement 1). In a subset of these we recorded from L4 PCs in the voltage clamp at a cesium-based internal but did not observe connections more frequently pairs data that L5 NMCs are into the densely of L4 PCs and interneurons et al., and whereas L5 MCs are from We next to the by our 2P mapping experiments that L5 MCs would specifically and reciprocally connect to L5 PCs, while NMCs would we inhibitory connections from L5 MCs onto L5 PCs pairs Figure in with prior et al., 2015; and Yuste, 2011; et al., We also excitatory connections from L5 PCs onto L5 MCs, more pairs Figure but at a consistent with the et al., 2015; and 2012). In contrast, we detected inhibitory outputs from L5 NMCs onto L5 PCs pairs Figure or excitatory connections from L5 PCs onto L5 NMCs pairs Figure despite the fact that L5 PCs were on located to L5 NMCs than were L4 PCs. The L5 PCs we recorded from in these experiments were from L5A and and both and PCs. The of connectivity between L5 PCs and L5 NMCs in stark to the dense connectivity between L5 PCs and L5 MCs, as well as in inhibitory circuits (Fino and Yuste, 2011; Packer and Yuste, 2011; and 2012). our that MCs and NMCs specifically target L5 PCs and L4 PCs results from a et al., 2018), to the that MCs and NMCs are into selective subnetworks with distinct laminar populations. genetic to subtypes of SST cells The highly specific connectivity revealed by our circuit mapping experiments suggests that MCs and NMCs are specialized for different in cortical computation. If this is the we would that the activity of these of interneurons have different on cortical on our circuit mapping results (Figure Figure we hypothesized that NMC activity optogenetically would