Anatomical and physiological experiments have outlined a blueprint for the feedforward flow of activity in cortical circuits: signals are thought to propagate primarily from the middle cortical layer (layer 4, L4) up to L2/3 and down to the major cortical output layer (L5). Pharmacological manipulations, however, have contested this model and have suggested that L4 may not be critical for sensory responses of neurons in either superficial or deep layers. To address these conflicting models, we reversibly manipulated L4 activity in awake, behaving mice using cell type–specific optogenetics. In contrast with both prevailing models, we found that activity in L4 directly suppressed L5, in part by activating deep, fast-spiking inhibitory neurons. Our data suggest that the net effect of L4 activity is to sharpen the spatial representations of L5 neurons. Thus, we establish a previously unknown translaminar inhibitory circuit in the sensory cortex that acts to enhance the feature selectivity of cortical output.
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Ramón y Cajal, S. Histology of the Nervous System of Man and Vertebrates (Oxford University Press, New York, 1995).
Gilbert, C.D. & Kelly, J.P. The projections of cells in different layers of the cat's visual cortex. J. Comp. Neurol. 163, 81–105 (1975).
Thomson, A.M. & Lamy, C. Functional maps of neocortical local circuitry. Front. Neurosci. 1, 19–42 (2007).
Feldmeyer, D. Excitatory neuronal connectivity in the barrel cortex. Front. Neuroanat. 6, 24 (2012).
Lefort, S., Tomm, C., Floyd Sarria, J.C. & Petersen, C.C. The excitatory neuronal network of the C2 barrel column in mouse primary somatosensory cortex. Neuron 61, 301–316 (2009).
Douglas, R.J. & Martin, K.A. Neuronal circuits of the neocortex. Annu. Rev. Neurosci. 27, 419–451 (2004).
Binzegger, T., Douglas, R.J. & Martin, K.A. A quantitative map of the circuit of cat primary visual cortex. J. Neurosci. 24, 8441–8453 (2004).
Malpeli, J.G. Activity of cells in area 17 of the cat in absence of input from layer a of lateral geniculate nucleus. J. Neurophysiol. 49, 595–610 (1983).
Constantinople, C.M. & Bruno, R.M. Deep cortical layers are activated directly by thalamus. Science 340, 1591–1594 (2013).
Mignard, M. & Malpeli, J.G. Paths of information-flow through visual-cortex. Science 251, 1249–1251 (1991).
Armstrong-James, M., Fox, K. & Dasgupta, A. Flow of excitation within rat barrel cortex on striking a single vibrissa. J. Neurophysiol. 68, 1345–1358 (1992).
Krupa, D.J., Wiest, M.C., Shuler, M.G., Laubach, M. & Nicolelis, M.A. Layer-specific somatosensory cortical activation during active tactile discrimination. Science 304, 1989–1992 (2004).
Haider, B., Hausser, M. & Carandini, M. Inhibition dominates sensory responses in the awake cortex. Nature 493, 97–100 (2013).
Niell, C.M. & Stryker, M.P. Modulation of visual responses by behavioral state in mouse visual cortex. Neuron 65, 472–479 (2010).
Gradinaru, V. et al. Molecular and cellular approaches for diversifying and extending optogenetics. Cell 141, 154–165 (2010).
Atasoy, D., Aponte, Y., Su, H.H. & Sternson, S.M. A FLEX switch targets Channelrhodopsin-2 to multiple cell types for imaging and long-range circuit mapping. J. Neurosci. 28, 7025–7030 (2008).
Madisen, L. et al. A robust and high-throughput Cre reporting and characterization system for the whole mouse brain. Nat. Neurosci. 13, 133–140 (2010).
Niell, C.M. & Stryker, M.P. Highly selective receptive fields in mouse visual cortex. J. Neurosci. 28, 7520–7536 (2008).
Nowak, L.G., Azouz, R., Sanchez-Vives, M.V., Gray, C.M. & McCormick, D.A. Electrophysiological classes of cat primary visual cortical neurons in vivo as revealed by quantitative analyses. J. Neurophysiol. 89, 1541–1566 (2003).
Agmon, A. & Connors, B.W. Correlation between intrinsic firing patterns and thalamocortical synaptic responses of neurons in mouse barrel cortex. J. Neurosci. 12, 319–329 (1992).
Curtis, J.C. & Kleinfeld, D. Phase-to-rate transformations encode touch in cortical neurons of a scanning sensorimotor system. Nat. Neurosci. 12, 492–501 (2009).
O'Connor, D.H., Peron, S.P., Huber, D. & Svoboda, K. Neural activity in barrel cortex underlying vibrissa-based object localization in mice. Neuron 67, 1048–1061 (2010).
Diamond, M.E., von Heimendahl, M., Knutsen, P.M., Kleinfeld, D. & Ahissar, E. 'Where' and 'what' in the whisker sensorimotor system. Nat. Rev. Neurosci. 9, 601–612 (2008).
Brumberg, J.C., Pinto, D.J. & Simons, D.J. Spatial gradients and inhibitory summation in the rat whisker barrel system. J. Neurophysiol. 76, 130–140 (1996).
Helmstaedter, M., Staiger, J.F., Sakmann, B. & Feldmeyer, D. Efficient recruitment of layer 2/3 interneurons by layer 4 input in single columns of rat somatosensory cortex. J. Neurosci. 28, 8273–8284 (2008).
Tarczy-Hornoch, K., Martin, K.A.C., Jack, J.J.B. & Stratford, K.J. Synaptic interactions between smooth and spiny neurones in layer 4 of cat visual cortex in vitro. J. Physiol. (Lond.) 508, 351–363 (1998).
Bortone, D.S., Olsen, S.R. & Scanziani, M. Translaminar inhibitory cells recruited by layer 6 corticothalamic neurons suppress visual cortex. Neuron 82, 474–485 (2014).
Feldmeyer, D., Roth, A. & Sakmann, B. Monosynaptic connections between pairs of spiny stellate cells in layer 4 and pyramidal cells in layer 5A indicate that lemniscal and paralemniscal afferent pathways converge in the infragranular somatosensory cortex. J. Neurosci. 25, 3423–3431 (2005).
Feldmeyer, D. & Sakmann, B. Synaptic efficacy and reliability of excitatory connections between the principal neurons of the input (layer 4) and output layer (layer 5) of the neocortex. J. Physiol. (Lond.) 525, 31–39 (2000).
Tamás, G., Buhl, E.H. & Somogyi, P. Fast IPSPs elicited via multiple synaptic release sites by different types of GABAergic neurone in the cat visual cortex. J. Physiol. (Lond.) 500, 715–738 (1997).
Xiang, Z., Huguenard, J.R. & Prince, D.A. Synaptic inhibition of pyramidal cells evoked by different interneuronal subtypes in layer v of rat visual cortex. J. Neurophysiol. 88, 740–750 (2002).
Packer, A.M. & Yuste, R. Dense, unspecific connectivity of neocortical parvalbumin-positive interneurons: a canonical microcircuit for inhibition? J. Neurosci. 31, 13260–13271 (2011).
Gorski, J.A. et al. Cortical excitatory neurons and glia, but not GABAergic neurons, are produced in the Emx1-expressing lineage. J. Neurosci. 22, 6309–6314 (2002).
Kätzel, D., Zemelman, B.V., Buetfering, C., Wolfel, M. & Miesenbock, G. The columnar and laminar organization of inhibitory connections to neocortical excitatory cells. Nat. Neurosci. 14, 100–107 (2011).
Li, L.Y. et al. A Feedforward inhibitory circuit mediates lateral refinement of sensory representation in upper layer 2/3 of mouse primary auditory cortex. J. Neurosci. 34, 13670–13683 (2014).
Gong, S. et al. Targeting cre recombinase to specific neuron populations with bacterial artificial chromosome constructs. J. Neurosci. 27, 9817–9823 (2007).
Apicella, A.J., Wickersham, I.R., Seung, H.S. & Shepherd, G.M.G. Laminarly orthogonal excitation of fast-spiking and low-threshold-spiking interneurons in mouse motor cortex. J. Neurosci. 32, 7021–7033 (2012).
Otsuka, T. & Kawaguchi, Y. Cortical inhibitory cell types differentially form intralaminar and interlaminar subnetworks with excitatory neurons. J. Neurosci. 29, 10533–10540 (2009).
Ma, Y., Hu, H., Berrebi, A.S., Mathers, P.H. & Agmon, A. Distinct subtypes of somatostatin-containing neocortical interneurons revealed in transgenic mice. J. Neurosci. 26, 5069–5082 (2006).
Oliva, A.A., Jiang, M.H., Lam, T., Smith, K.L. & Swann, J.W. Novel hippocampal interneuronal subtypes identified using transgenic mice that express green fluorescent protein in GABAergic interneurons. J. Neurosci. 20, 3354–3368 (2000).
Royer, S. et al. Control of timing, rate and bursts of hippocampal place cells by dendritic and somatic inhibition. Nat. Neurosci. 15, 769–775 (2012).
Fanselow, E.E. & Nicolelis, M.A. Behavioral modulation of tactile responses in the rat somatosensory system. J. Neurosci. 19, 7603–7616 (1999).
Khatri, V., Hartings, J.A. & Simons, D.J. Adaptation in thalamic barreloid and cortical barrel neurons to periodic whisker deflections varying in frequency and velocity. J. Neurophysiol. 92, 3244–3254 (2004).
Jiang, X.L., Wang, G.F., Lee, A.J., Stornetta, R.L. & Zhu, J.J. The organization of two new cortical interneuronal circuits. Nat. Neurosci. 16, 201–2018 2013).
Helmstaedter, M., Sakmann, B. & Feldmeyer, D. Neuronal correlates of local, lateral, and translaminar inhibition with reference to cortical columns. Cereb. Cortex 19, 926–937 (2009).
Priebe, N.J. & Ferster, D. Inhibition, spike threshold, and stimulus selectivity in primary visual cortex. Neuron 57, 482–497 (2008).
Adesnik, H. & Scanziani, M. Lateral competition for cortical space by layer-specific horizontal circuits. Nature 464, 1155–1160 (2010).
Hirsch, J.A., Alonso, J.M., Reid, R.C. & Martinez, L.M. Synaptic integration in striate cortical simple cells. J. Neurosci. 18, 9517–9528 (1998).
Isaacson, J.S. & Scanziani, M. How inhibition shapes cortical activity. Neuron 72, 231–243 (2011).
Ozeki, H., Finn, I.M., Schaffer, E.S., Miller, K.D. & Ferster, D. Inhibitory stabilization of the cortical network underlies visual surround suppression. Neuron 62, 578–592 (2009).
Tamamaki, N. et al. Green fluorescent protein expression and colocalization with calretinin, parvalbumin, and somatostatin in the GAD67-GFP knock-in mouse. J. Comp. Neurol. 467, 60–79 (2003).
Hill, D.N., Mehta, S.B. & Kleinfeld, D. Quality metrics to accompany spike sorting of extracellular signals. J. Neurosci. 31, 8699–8705 (2011).
Nicholson, C. & Freeman, J.A. Theory of current source-density analysis and determination of conductivity tensor for anuran cerebellum. J. Neurophysiol. 38, 356–368 (1975).
Reyes-Puerta, V. et al. Spatial structure of spiking correlations in the barrel cortex of anesthetized rats. J. Mol. Neurosci. 53, S6 (2014).
Reyes-Puerta, V., Sun, J.J., Kim, S., Kilb, W. & Luhmann, H.J. Large-scale neural assembly sequences evoked by sensory stimulation in the adult rat barrel cortex in vivo. Acta Physiol. (Oxf.) 210, 66 (2014).
Legéndy, C.R. & Salcman, M. Bursts and recurrences of bursts in the spike trains of spontaneously active striate cortex neurons. J. Neurophysiol. 53, 926–939 (1985).
Reyes-Puerta, V., Sun, J.J., Kim, S., Kilb, W. & Luhmann, H.J. laminar and columnar structure of sensory-evoked multineuronal spike sequences in adult rat barrel cortex in vivo. Cereb. Cortex 25, 2001–2021 (2014).
Silberberg, G. & Markram, H. Disynaptic inhibition between neocortical pyramidal cells mediated by martinotti cells. Neuron 53, 735–746 (2007).
Clack, N.G. et al. Automated tracking of whiskers in videos of head fixed rodents. PLOS Comput. Biol. 8, e1002591 (2012).
We are grateful to K. Deisseroth (Stanford University) and S. Sternson (Janelia Farms Research Campus, HHMI) for optogenetic reagents and to D. Kleinfeld (University of California, San Diego) for spike sorting software. This work was supported by National Institute of Neurological Disorders and Stroke grant DP2NS087725-01 and National Eye Institute grant R01EY023756-01, and a Whitehall foundation grant to H.A. J.V. was supported by a grant from the Swiss National Foundation.
The authors declare no competing financial interests.
Integrated supplementary information
Supplementary Figure 1 Scnn1-tg3-Cre line labels excitatory cortical neurons preferentially in layer 4
a, Left: Laser scanning confocal image of an scnn1-tg3-Cre mouse injected with AAV9-ef1a-DIO-YFP. Scale bar: 100 μm. Right: histogram of the proportion of labeled cells observed vs. cortical depth. b, Top: Example image from L4 of an scnn1-tg3-Cre;Rosa-LSL-tdtomato; GAD67-GFP mouse. Bottom: Quantification of the number of cells expressing tdTomato (85%) or GFP (15%). No cells co-expressing GFP and tdTomato were observed. Scale bar: 100 μm. c, Plot of normalized spike rate under light vs. control conditions in L4 RS units for rank- ordered stimulus preference. d, Plot of the proportion of synaptic excitation and synaptic inhibition blocked by application of the glutamatergic antagonists NBQX and CPP (10 μM each, p = 0.00012, n = 14 cells in 14 slices from 5 mice, Wilcoxon signed rank test, z = 3.28). e, Firing rate vs current injection plots of L4 eNpHR3.0-expressing excitatory neurons under control conditions (black) and during illumination of the slice (n = 8 cells in 4 slices from 3 mice). Inset: example trace showing light evoked suppression of action potential firing.
Supplementary Figure 2 Verification of depth estimates of extracellularly recorded units
a, Example current source density plot computed from a 32-channel laminar probe inserted into S1 during whisker deflection. b, Histogram of the computed error in L4/5 boundary by comparing depth from the micromanipulator reading to the depth indicated by CSD analysis. c, Left: example imaging of a DiI track of a recording electrode inserted into the barrel cortex. Green: eNpHR-YFP, red: DiI. Right: same but for V1. d, Example images from four layer-specific Cre lines crossed to a Rosa-LSL-tdTomato reporter line used to compute laminar boundaries. e, Average laminar boundaries measured from the layer-specific Cre lines (n = 2 Drd3-Cre mice, n = 3 scnn1a-cre mice, n = 2 Rbp4-Cre mice, n = 1 Ntsr1 mouse, measurements in multiple sections for each mouse). f, Example spatial tuning curves for three units recorded on adjacent shanks of a multi-shank probes (200 μm spacing), with adjacent shanks in three neighboring barrel columns. g, Cumulative distribution plots of the preferred positions of units recorded on multi-shank laminar probes (p < 10-6, n = 125, Kruskal-wallis). Note the smooth shift in preferred position across the probe shanks.
Supplementary Figure 3 Illumination of the cortex in mice expressing YFP alone shows no effect on the cortical response to sensory stimulation
a, Left: Raster plot (top) and PSTH (bottom) of an example L5 RS unit during illumination of the cortex. Middle: Population PSTH under control conditions (black) and during illumination (red). Light had no effect on the spatial tuning curve of L5 RS units (p = 0.36, n =33 units from 3 mice, 2-way ANOVA, f(1) = 0.8445). b, As in a) but for L5 FS neurons (p = 0.7, n = 19 units from 3 mice, 2-way ANOVA, f(1) = 0.1108). c, As in a) but for L4 units (p = 0.5, n = 16 units from 3 mice, 2-way ANOVA, f(1) = 0.45). d, Scatter plot of neuronal firing rates of L5 RS units under control and photo-suppression conditions for their preferred tactile stimulus (n = 33 from 3 mice, p = 0.15, paired t-test). e, As in d) but for the non-contact condition (p = 0.62, paired t-test). f, Scatter plot of the spatial tuning index of L5 RS units under control and illumination conditions (p = 0.95, paired t-test).
Supplementary Figure 4 Photo-suppression of L4 does not alter whisking behavior
a, Top: Imaging schematic with a high-speed camera for whisker tracking. Middle: example image and tracked whisker (blue line) from the high-speed imaging stream. Bottom: example traces of whisker movement under control conditions (black) and during photo-suppression of L4. Black dots indicated contacts with the tactile stimulus bar. b, Top: Cumulative distribution plot of whisk amplitudes (p = 0.71, n = 422 whisk cycles in 4 mice, 2-way ANOVA, f(1) = 0.14); whisker set point (p = 0.56, n = 422 whisk cycles in 4 mice, 2-way ANOVA, f(1) = 0.33), whisk frequency (p = 0.47, n = 422 whisk cycles in 4 mice, 2-way ANOVA, f(1) = 0.51), and contact rate (p = 0.38, 2-way ANOVA) under control (black) and during L4 photo-suppression (red) (±95% confidence intervals, dotted lines). All error bars are one standard deviation of the mean.
Supplementary Figure 5 Photo-suppression of L4 preferentially enhances L5 firing for non-optimal stimuli
a, Scatter plot comparing OMI for the non-preferred stimulus position vs. the preferred stimulus position (mean OMInon-preferred: 0.35±0.04; mean OMIpreferred: 0.02±0.03; p < 10-6, n = 75 units from 9 mice, paired t-test, t(74) = 8.2). b, Scatter plot of raw firing rates of L5 RS units for the least-preferred stimulus position comparing control and L4 photo-suppression conditions (p < 10-6, n = 75 units from 9 mice, paired t-test, t(74) = 7.9). c, As in b) except for the most-preferred stimulus position (p = 0.0006, n = 75 units from 9 mice, paired t-test, t(74) = 3.7). d, Histograms of a mean OMI of L5 RS units between animals tested will all the whiskers intact (‘full pad’, black), and those trimmed to the principal whisker (green). e, As in d) except for L5 FS units. L4 suppression significantly (p = 1.3×10-4, n = 24, f(1) = 15) enhanced L5 RS cells and significantly (p<0.002, n = 12, f(1) = 10) suppressed L5 FS cells during single whisker stimulation (2-way ANOVA). OMI distributions for L5 RS and L5 FS units were not significantly different between full and single whisker stimulation (p = 0.34 and 0.69, respectively, two-tailed t-test).
Supplementary Figure 6 The impact of L4 photo-suppression on FS units across layers
a, Plot of the average normalized spike rates for FS units across L2/3, L5 and L6 between control and L4 photo-suppression conditions, grouped by ranked stimulus response. b, Histograms of the mean OMI for FS units across these layers across all stimulus conditions. c, Plot of the mean OMI across all stimulus conditions for FS units across all layers during photo-suppression of L4. d, As in c) but for L4 photo-activation (n.d., not done). e-f As in c) and d) but showing changes in the raw firing rates of FS units across layers. Firing rates in L2/3 (p = 0.005, n = 50 units from 5 mice, 2-way ANOVA, f(1) = 9.13), L4 (n = 35 units from 6 mice, p < 10-6, 2-way ANOVA, f(1) = 26.6), and L5 (p < 10-5, n = 53 units from 9 mice, 2-way ANOVA, f(1) = 24) were significantly reduced during L4 photo-suppression. However, firing rates in L6 were not significantly affected (p = 0.55, n = 25 from 3 mice, 2-way ANOVA, f(1) = 0.36).
Supplementary Figure 7 Separation of FS and RS units
a, Example waveforms for units categorized as FS (green) or RS (black) based on several waveform parameters. b, Scatter plot of amplitude asymmetry vs. trough to 2nd peak for recorded units. Units were categorized by k-means clustering. FS units: green, RS units: black, grey: excluded units, red: cells recorded in cell-attached mode prior to intracellular recording. c, Histogram of sEPSC decay time constants in identified FS (green) or RS neurons (black) from acute brain slices. Cells were identified by their firing characteristics to current injection in the whole-cell mode. Inset: example average sEPSCs from an FS neuron (green) and an RS neuron (black). d, As in c) but for neurons recorded using the blind patch technique in vivo. e, Example supra-threshold response of a PV+ neuron recorded with a K+-based internal solution in a brain slice to current injection showing the characteristic non-adapting high frequency firing. f, As in e) but for a blind-patched pFS L5 neuron in vivo. Note that the variance in spike timing likely arises due to fluctuations in the background synaptic conductance in vivo. g, Average estimated series resistance (left), input resistance (center), and membrane time constant (right) for recorded RS and FS L5 cells in vivo (17 cells, 12 mice) and in vitro (in vitro: n = 42 cells in 36 slices from 17 mice). h, Average responses to a -4 mV voltages step in the RS (left) and pFS (center) neurons recorded in vivo. Right: expansion of the average current relaxation in RS and pFS cells after the end of the voltage step.
Supplementary Figure 8 Spatial resolution of DMD-based optogenetic mapping and input maps of L5 FS neurons
a, Left: schematic of DMD-based setup for photo-stimulation. Right: Example spike probability maps of an example excitatory neuron in L5, L4, and L2/3. b, Spatial resolution of light-evoked spiking in ChR2+ excitatory neurons in the emx1-Cre line. c, Plot of spike probability vs. distance of the photo-stimulation light from the soma of the recorded neuron. d, As in c) but for mean number of action potentials evoked per photo-stimulation trial. e, Scatter plot of the mean excitatory input of recorded L5 FS neurons comparing input from L4 and L5. f, Top: All 31 excitatory input maps of L5 FS neurons ranked ordered according to the ratio of their mean excitatory input from L4 to L5. Maps have been rotated and cropped to show only the region corresponding to the barrel column in which each FS cell was located. White lines correspond to the upper and lower borders of L4. Green and white dots indicate the soma location of the recorded cell. Bottom: Corresponding log value of the ratio of mean charge transfer per unit area of L4 to mean charge transfer per unit area of L5 for each map. g, As in top panel of f), but with each map normalized to its range. h, Left: Average excitatory input map for all L5 FS cells (n = 31 cells in 26 slices from 13 mice), after aligning the barrel of the home column of each recorded cell. Right: As in left panel, but after horizontally aligning maps to the soma of each recorded cell. Scale bar: 200 μm. i, Quantification of the proportion of excitatory charge transfer to L5 FS cells originating from within the home column versus surrounding columns across cortical layers, normalized to total charge transfer in each map.
Supplementary Figure 9 PV interneuron mediated inhibitory input to L5 cells
a, Average of normalized inhibitory input maps for all L5 pyramidal cells (n = 16 cells in 9 slices from 4 mice) recorded in PV-Cre;flexed-ChR2 brain slices. Maps are vertically aligned to laminar borders and horizontally aligned to the soma of the recorded cell (blue circles). b, Plot of the mean proportion of inhibitory input onto L5 pyramidal cells from PV neurons in each cortical layer, separated by barrel column. H: home column. ±1: adjacent barrel column. Dark gray: mean proportion of home column inhibitory input; light gray: same, but for the surrounding two columns. c, Top: Average spike probability map for all recorded PV neurons (n = 19 ChR2+ PV cells in total, in 11 slices from 5 mice; n = 4 in L2/3; n = 6 in L4; n = 7 in L5; n=2 in L6) under the photo-stimulation conditions using for mapping inhibitory input to L5 PCs. Bottom: Plot of firing probability versus distance from the soma of the recorded PV neuron. d, As in c) except for mean number of action potentials evoked in PV neurons during each photo-stimulus. e, Top: All 16 individual inhibitory input maps for L5 pyramidal cells. Bottom: four example inhibitory input maps in intracellularly recorded PV neurons (recorded at the reversal potential of the ChR2-photocurrent).
Supplementary Figure 10 Impact of photo-suppression of L2/3 excitatory neurons on L5 FS units
a, Example image from a Drd3-Cre mouse injected with a DIO-eNpHR3.0-YFP (green) and recorded with a DiI-labeled laminar multi-electrode array. Scale bar: 200 μm b, Box and whisker plot of the average percent change in L5 FS unit firing rate when photo-suppressing L4 (in the scnn1-tg3-Cre line) or L2/3 (in the Drd3-Cre line). c, Spatial tuning curve of an example photo-suppressed L2/3 RS unit with (red) and without (black) light. d, Raster plot (top) and PSTH (bottom) of the example unit in c) during photo-suppression of L2/3 during sensory stimulation. e, Plot of the proportion of synaptic excitation and synaptic inhibition blocked by application of the glutamatergic antagonists NBQX and CPP (p = 0.00024, n = 13 cells in 8 slices from 4 mice, Wilcoxon signed rank test, z = 3.16). f, Example traces of light evoked IPSCs recorded in a L5 pyramidal cells in drd3-cre mice injected with flexed-ChR2. Black: control, grey: after application of glutamatergic antagonists, showing near 100% block.
Supplementary Figure 11 Photo-suppression of L4 does not increase burst rate of L5 RS cells
a, Histogram of the fraction of high frequency spikes (see Methods) for L5 RS units with (red) and without (black) photo-suppression of L4 (p = 0.46, n = 75 units from 9 mice, Wilcoxon signed rank test). b, Scatter plot of the coefficient of variation of the inter-spike-intervals (ISIs) of L5 RS units with and without photo-suppression of L4 (light vs no light, p = 0.22, n = 75 units from 9 mice, Wilcoxon signed rank test). c, Histogram of the change in burst rate of L5 RS units during photo-suppression of L4 (p=0.67, n=75 units from 9 mice, Wilcoxon signed rank test). d, As in d) but for L5 RS units recorded in the visual cortex. e, As in c) but for V1 units. f, As in e) but for photo-suppression of SOM+ inhibitory neurons. g, As in f) but for SOM photo-suppression. In figure panels d), e) and g), burst rate was calculated using a Poisson surprise algorithm53.
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Pluta, S., Naka, A., Veit, J. et al. A direct translaminar inhibitory circuit tunes cortical output. Nat Neurosci 18, 1631–1640 (2015). https://doi.org/10.1038/nn.4123
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