Division and subtraction by distinct cortical inhibitory networks in vivo


Brain circuits process information through specialized neuronal subclasses interacting within a network. Revealing their interplay requires activating specific cells while monitoring others in a functioning circuit. Here we use a new platform for two-way light-based circuit interrogation in visual cortex in vivo to show the computational implications of modulating different subclasses of inhibitory neurons during sensory processing. We find that soma-targeting, parvalbumin-expressing (PV) neurons principally divide responses but preserve stimulus selectivity, whereas dendrite-targeting, somatostatin-expressing (SOM) neurons principally subtract from excitatory responses and sharpen selectivity. Visualized in vivo cell-attached recordings show that division by PV neurons alters response gain, whereas subtraction by SOM neurons shifts response levels. Finally, stimulating identified neurons while scanning many target cells reveals that single PV and SOM neurons functionally impact only specific subsets of neurons in their projection fields. These findings provide direct evidence that inhibitory neuronal subclasses have distinct and complementary roles in cortical computations.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: All-optical network dissection of cortical subclasses during visual computations.
Figure 2: Impact of PV- and SOM-driven inhibition on the tuning of neuronal responses.
Figure 3: Electrophysiological analysis of PV- and SOM-driven inhibition.
Figure 4: Modulation of response gain by PV and SOM cells during targeted cell-attached recordings.
Figure 5: Dual-laser optical mapping of network connections to reveal maps of functional inhibition by single PV and SOM neurons.
Figure 6: Spatial and functional analysis of targeting by single PV and SOM neurons.


  1. 1

    Freund, T. F. & Buzsáki, G. Interneurons of the hippocampus. Hippocampus 6, 347–470 (1996)

    CAS  Article  Google Scholar 

  2. 2

    Markram, H. et al. Interneurons of the neocortical inhibitory system. Nature Rev. Neurosci. 5, 793–807 (2004)

    CAS  Article  Google Scholar 

  3. 3

    Klausberger, T. & Somogyi, P. Neuronal diversity and temporal dynamics: the unity of hippocampal circuit operations. Science 321, 53–57 (2008)

    ADS  CAS  Article  Google Scholar 

  4. 4

    Lewis, D. A. GABAergic local circuit neurons and prefrontal cortical dysfunction in schizophrenia. Brain Res. Brain Res. Rev. 31, 270–276 (2000)

    CAS  Article  Google Scholar 

  5. 5

    Sillito, A. M. The contribution of inhibitory mechanisms to the receptive field properties of neurones in the striate cortex of the cat. J. Physiol. (Lond.) 250, 305–329 (1975)

    CAS  Article  Google Scholar 

  6. 6

    Crook, J. M., Kisvárday, Z. F. & Eysel, U. T. Evidence for a contribution of lateral inhibition to orientation tuning and direction selectivity in cat visual cortex: reversible inactivation of functionally characterized sites combined with neuroanatomical tracing techniques. Eur. J. Neurosci. 10, 2056–2075 (1998)

    CAS  Article  Google Scholar 

  7. 7

    Tsumoto, T., Eckart, W. & Creutzfeldt, O. D. Modification of orientation sensitivity of cat visual cortex neurons by removal of GABA-mediated inhibition. Exp. Brain Res. 34, 351–363 (1979)

    CAS  Article  Google Scholar 

  8. 8

    Ferster, D. & Miller, K. D. Neural mechanisms of orientation selectivity in the visual cortex. Annu. Rev. Neurosci. 23, 441–471 (2000)

    CAS  Article  Google Scholar 

  9. 9

    Wehr, M. & Zador, A. M. Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex. Nature 426, 442–446 (2003)

    ADS  CAS  Article  Google Scholar 

  10. 10

    Monier, C., Chavane, F., Baudot, P., Graham, L. J. & Frégnac, Y. Orientation and direction selectivity of synaptic inputs in visual cortical neurons: a diversity of combinations produces spike tuning. Neuron 37, 663–680 (2003)

    CAS  Article  Google Scholar 

  11. 11

    Carandini, M. & Heeger, D. J. Summation and division by neurons in primate visual cortex. Science 264, 1333–1336 (1994)

    ADS  CAS  Article  Google Scholar 

  12. 12

    Somers, D. C., Nelson, S. B. & Sur, M. An emergent model of orientation selectivity in cat visual cortical simple cells. J. Neurosci. 15, 5448–5465 (1995)

    CAS  Article  Google Scholar 

  13. 13

    Reynolds, J. H. & Heeger, D. J. The normalization model of attention. Neuron 61, 168–185 (2009)

    CAS  Article  Google Scholar 

  14. 14

    Ohshiro, T., Angelaki, D. E. & DeAngelis, G. C. A normalization model of multisensory integration. Nature Neurosci. 14, 775–782 (2011)

    CAS  Article  Google Scholar 

  15. 15

    Louie, K. & Glimcher, P. W. Separating value from choice: delay discounting activity in the lateral intraparietal area. J. Neurosci. 30, 5498–5507 (2010)

    CAS  Article  Google Scholar 

  16. 16

    Rudy, B., Fishell, G., Lee, S. & Hjerling-Leffler, J. Three groups of interneurons account for nearly 100% of neocortical GABAergic neurons. Dev. Neurobiol. 71, 45–61 (2011)

    Article  Google Scholar 

  17. 17

    Xu, X., Roby, K. D. & Callaway, E. M. Immunochemical characterization of inhibitory mouse cortical neurons: three chemically distinct classes of inhibitory cells. J. Comp. Neurol. 518, 389–404 (2010)

    Article  Google Scholar 

  18. 18

    Schummers, J., Yu, H. & Sur, M. Tuned responses of astrocytes and their influence on hemodynamic signals in the visual cortex. Science 320, 1638–1643 (2008)

    ADS  CAS  Article  Google Scholar 

  19. 19

    Runyan, C. A. et al. Response features of parvalbumin-expressing interneurons suggest precise roles for subtypes of inhibition in visual cortex. Neuron 67, 847–857 (2010)

    CAS  Article  Google Scholar 

  20. 20

    Bock, D. D. et al. Network anatomy and in vivo physiology of visual cortical neurons. Nature 471, 177–182 (2011)

    ADS  CAS  Article  Google Scholar 

  21. 21

    Yoshimura, Y. & Callaway, E. M. Fine-scale specificity of cortical networks depends on inhibitory cell type and connectivity. Nature Neurosci. 8, 1552–1559 (2005)

    CAS  Article  Google Scholar 

  22. 22

    Fino, E. & Yuste, R. Dense inhibitory connectivity in neocortex. Neuron 69, 1188–1203 (2011)

    CAS  Article  Google Scholar 

  23. 23

    Packer, A. M. & Yuste, R. Dense, unspecific connectivity of neocortical parvalbumin-positive interneurons: a canonical microcircuit for inhibition? J. Neurosci. 31, 13260–13271 (2011)

    CAS  Article  Google Scholar 

  24. 24

    Ko, H. et al. Functional specificity of local synaptic connections in neocortical networks. Nature 473, 87–91 (2011)

    ADS  CAS  Article  Google Scholar 

  25. 25

    Lillis, K. P., Eng, A., White, J. A. & Mertz, J. Two-photon imaging of spatially extended neuronal network dynamics with high temporal resolution. J. Neurosci. Methods 172, 178–184 (2008)

    Article  Google Scholar 

  26. 26

    Atallah, B. V., Bruns, W., Carandini, M. & Scanziani, M. Parvalbumin-expressing interneurons linearly transform cortical responses to visual stimuli. Neuron 73, 159–170 (2012)

    CAS  Article  Google Scholar 

  27. 27

    Katzner, S., Busse, L. & Carandini, M. GABAA inhibition controls response gain in visual cortex. J. Neurosci. 31, 5931–5941 (2011)

    CAS  Article  Google Scholar 

  28. 28

    Anderson, J. S., Carandini, M. & Ferster, D. Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex. J. Neurophysiol. 84, 909–926 (2000)

    CAS  Article  Google Scholar 

  29. 29

    Mariño, J. et al. Invariant computations in local cortical networks with balanced excitation and inhibition. Nature Neurosci. 8, 194–201 (2005)

    ADS  Article  Google Scholar 

  30. 30

    Kerlin, A. M., Andermann, M. L., Berezovskii, V. K. & Reid, R. C. Broadly tuned response properties of diverse inhibitory neuron subtypes in mouse visual cortex. Neuron 67, 858–871 (2010)

    CAS  Article  Google Scholar 

  31. 31

    Hofer, S. B. et al. Differential connectivity and response dynamics of excitatory and inhibitory neurons in visual cortex. Nature Neurosci. 14, 1045–1052 (2011)

    CAS  Article  Google Scholar 

  32. 32

    Tan, A. Y., Brown, B. D., Scholl, B., Mohanty, D. & Priebe, N. J. Orientation selectivity of synaptic input to neurons in mouse and cat primary visual cortex. J. Neurosci. 31, 12339–12350 (2011)

    CAS  Article  Google Scholar 

  33. 33

    Nelson, S., Toth, L., Sheth, B. & Sur, M. Orientation selectivity of cortical neurons during intracellular blockade of inhibition. Science 265, 774–777 (1994)

    ADS  CAS  Article  Google Scholar 

  34. 34

    Xing, D., Ringach, D. L., Hawken, M. J. & Shapley, R. M. Untuned suppression makes a major contribution to the enhancement of orientation selectivity in macaque v1. J. Neurosci. 31, 15972–15982 (2011)

    CAS  Article  Google Scholar 

  35. 35

    Liu, B. H. et al. Broad inhibition sharpens orientation selectivity by expanding input dynamic range in mouse simple cells. Neuron 71, 542–554 (2011)

    CAS  Article  Google Scholar 

  36. 36

    Jia, H., Rochefort, N. L., Chen, X. & Konnerth, A. Dendritic organization of sensory input to cortical neurons in vivo. Nature 464, 1307–1312 (2010)

    ADS  CAS  Article  Google Scholar 

  37. 37

    Mao, R. et al. Influence of a subtype of inhibitory interneuron on stimulus-specific responses in visual cortex. Cereb. Cortex 22, 493–508 (2011)

    Article  Google Scholar 

  38. 38

    Tan, A. Y., Zhang, L. I., Merzenich, M. M. & Schreiner, C. E. Tone-evoked excitatory and inhibitory synaptic conductances of primary auditory cortex neurons. J. Neurophysiol. 92, 630–643 (2004)

    Article  Google Scholar 

  39. 39

    Okun, M. & Lampl, I. Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities. Nature Neurosci. 11, 535–537 (2008)

    CAS  Article  Google Scholar 

  40. 40

    Gentet, L. J., Avermann, M., Matyas, F., Staiger, J. F. & Petersen, C. C. Membrane potential dynamics of GABAergic neurons in the barrel cortex of behaving mice. Neuron 65, 422–435 (2010)

    CAS  Article  Google Scholar 

  41. 41

    Haider, B., Duque, A., Hasenstaub, A. R. & McCormick, D. A. Neocortical network activity in vivo is generated through a dynamic balance of excitation and inhibition. J. Neurosci. 26, 4535–4545 (2006)

    CAS  Article  Google Scholar 

  42. 42

    Yazaki-Sugiyama, Y., Kang, S., Câteau, H., Fukai, T. & Hensch, T. K. Bidirectional plasticity in fast-spiking GABA circuits by visual experience. Nature 462, 218–221 (2009)

    ADS  CAS  Article  Google Scholar 

  43. 43

    Koch, C., Poggio, T. & Torre, V. Nonlinear interactions in a dendritic tree: localization, timing, and role in information processing. Proc. Natl Acad. Sci. USA 80, 2799–2802 (1983)

    ADS  CAS  Article  Google Scholar 

  44. 44

    Kulik, A. et al. Compartment-dependent colocalization of Kir3.2-containing K+ channels and GABAB receptors in hippocampal pyramidal cells. J. Neurosci. 26, 4289–4297 (2006)

    CAS  Article  Google Scholar 

  45. 45

    Nusser, Z., Sieghart, W., Benke, D., Fritschy, J. M. & Somogyi, P. Differential synaptic localization of two major gamma-aminobutyric acid type A receptor alpha subunits on hippocampal pyramidal cells. Proc. Natl Acad. Sci. USA 93, 11939–11944 (1996)

    ADS  CAS  Article  Google Scholar 

Download references


We thank J. Huang for providing the SOM–Cre mouse line; C. Le for performing animal care support and viral injections; S. Yan and Y. Deng for help in the development of optogenetics and imaging methods in vitro; S. El-Boustani for collecting data for in vivo deconvolution; J. Sharma, M. Goard and A. Banerjee for comments and discussions on the manuscript; L.-H. Tsai, K. Meletis and M. Carlen for early provision of viral constructs and PV–Cre viral injections; and James Schummers and Hiroki Sugihara for participating in early pilot experiments testing optogenetics stimulation in vivo. This work was supported by postdoctoral fellowships from the US National Institutes of Health (NIH) and the Simons Foundation (N.R.W.), an NIH predoctoral fellowship (C.A.R.) and grants from the NIH and the Simons Foundation (M.S.).

Author information




Author Contributions N.R.W. conceived experiments, designed and engineered circuit interface and analysis systems, carried out in vivo and in vitro experiments, and performed analyses. C.A.R. conceived experiments, performed surgeries and viral injections, carried out in vivo experiments, and performed analyses. F.L.W. carried out in vivo experiments, and performed analyses. M.S. conceived experiments and contributed to analysis of experiments. N.R.W., C.A.R. and M.S. wrote the paper.

Corresponding authors

Correspondence to Nathan R. Wilson or Mriganka Sur.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Methods and additional references, Supplementary Figures 1-21 and full legends for Supplementary Movies 1-4. (PDF 7930 kb)

Supplementary Movie 1

This file contains a movie showing increased dwell time in cells during two-photon imaging via targeted scan imaging (see Supplementary Information file for full legend). (MOV 15157 kb)

Supplementary Movie 2

This file contains a movie showing targeted scanning of identified cells responding to visual stimuli (see Supplementary Information file for full legend). (MOV 4567 kb)

Supplementary Movie 3

This file contains a movie showing targeted scanning combined with full-field optogenetic stimulation (see Supplementary Information file for full legend). (MOV 5211 kb)

Supplementary Movie 4

This file contains a movie showing targeted scanning combined with single-cell optogenetic stimulation (see Supplementary Information file for full legend). (MOV 5034 kb)

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Wilson, N., Runyan, C., Wang, F. et al. Division and subtraction by distinct cortical inhibitory networks in vivo. Nature 488, 343–348 (2012). https://doi.org/10.1038/nature11347

Download citation

Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.