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Input normalization by global feedforward inhibition expands cortical dynamic range

Nature Neuroscience volume 12, pages 1577–1585 (2009)Cite this article

Abstract

The cortex is sensitive to weak stimuli, but responds to stronger inputs without saturating. The mechanisms that enable this wide range of operation are not fully understood. We found that the amplitude of excitatory synaptic currents necessary to fire rodent pyramidal cells, the threshold excitatory current, increased with stimulus strength. Consequently, the relative contribution of individual afferents in firing a neuron was inversely proportional to the total number of active afferents. Feedforward inhibition, acting homogeneously across pyramidal cells, ensured that threshold excitatory currents increased with stimulus strength. In contrast, heterogeneities in the distribution of excitatory currents in the neuronal population determined the specific set of pyramidal cells recruited. Together, these mechanisms expand the range of afferent input strengths that neuronal populations can represent.

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Figure 1: The stronger the stimulus, the larger the excitation necessary to recruit a pyramidal cell.
Figure 2: Feedforward inhibition expands the dynamic range of the pyramidal cell population.
Figure 3: Pyramidal cells spike after the onset of feedforward inhibition.
Figure 4: Homogeneous inhibition and heterogeneous excitation control the recruitment of pyramidal cells.
Figure 5: Fast-spiking interneurons enforce dynamic EPSGT.
Figure 6: Model of activation curve with dynamic EPSGT.
Figure 7: The stronger the photostimulation of L2/3 pyramidal cells, the larger the excitation necessary to recruit L5 pyramidal cells.

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References

  1. 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).

    Article  CAS  Google Scholar 

  2. Otmakhov, N., Shirke, A.M. & Malinow, R. Measuring the impact of probabilistic transmission on neuronal output. Neuron 10, 1101–1111 (1993).

    Article  CAS  Google Scholar 

  3. Marr, D. A theory of cerebellar cortex. J. Physiol. (Lond.) 202, 437–470 (1969).

    Article  CAS  Google Scholar 

  4. Vogels, T.P. & Abbott, L.F. Signal propagation and logic gating in networks of integrate-and-fire neurons. J. Neurosci. 25, 10786–10795 (2005).

    Article  CAS  Google Scholar 

  5. Shadlen, M.N. & Newsome, W.T. The variable discharge of cortical neurons: implications for connectivity, computation and information coding. J. Neurosci. 18, 3870–3896 (1998).

    Article  CAS  Google Scholar 

  6. Diesmann, M., Gewaltig, M.O. & Aertsen, A. Stable propagation of synchronous spiking in cortical neural networks. Nature 402, 529–533 (1999).

    Article  CAS  Google Scholar 

  7. Arabzadeh, E., Zorzin, E. & Diamond, M.E. Neuronal encoding of texture in the whisker sensory pathway. PLoS Biol. 3, e17 (2005).

    Article  Google Scholar 

  8. Wilson, M.A. & McNaughton, B.L. Dynamics of the hippocampal ensemble code for space. Science 261, 1055–1058 (1993).

    Article  CAS  Google Scholar 

  9. Csicsvari, J., Hirase, H., Mamiya, A. & Buzsaki, G. Ensemble patterns of hippocampal CA3–CA1 neurons during sharp wave–associated population events. Neuron 28, 585–594 (2000).

    Article  CAS  Google Scholar 

  10. Shu, Y., Hasenstaub, A., Badoual, M., Bal, T. & McCormick, D.A. Barrages of synaptic activity control the gain and sensitivity of cortical neurons. J. Neurosci. 23, 10388–10401 (2003).

    Article  CAS  Google Scholar 

  11. Mitchell, S.J. & Silver, R.A. Shunting inhibition modulates neuronal gain during synaptic excitation. Neuron 38, 433–445 (2003).

    Article  CAS  Google Scholar 

  12. Chance, F.S., Abbott, L.F. & Reyes, A.D. Gain modulation from background synaptic input. Neuron 35, 773–782 (2002).

    Article  CAS  Google Scholar 

  13. Carvalho, T.P. & Buonomano, D.V. Differential effects of excitatory and inhibitory plasticity on synaptically driven neuronal input-output functions. Neuron 61, 774–785 (2009).

    Article  CAS  Google Scholar 

  14. Tropp Sneider, J., Chrobak, J.J., Quirk, M.C., Oler, J.A. & Markus, E.J. Differential behavioral state-dependence in the burst properties of CA3 and CA1 neurons. Neuroscience 141, 1665–1677 (2006).

    Article  CAS  Google Scholar 

  15. Pouille, F. & Scanziani, M. Enforcement of temporal fidelity in pyramidal cells by somatic feedforward inhibition. Science 293, 1159–1163 (2001).

    Article  CAS  Google Scholar 

  16. Buzsáki, G. Feed-forward inhibition in the hippocampal formation. Prog. Neurobiol. 22, 131–153 (1984).

    Article  Google Scholar 

  17. Alger, B.E. & Nicoll, R.A. Feed-forward dendritic inhibition in rat hippocampal pyramidal cells studied in vitro. J. Physiol. (Lond.) 328, 105–123 (1982).

    Article  CAS  Google Scholar 

  18. Nicoll, R.A., Alger, B.E. & Jahr, C.E. Enkephalin blocks inhibitory pathways in the vertebrate CNS. Nature 287, 22–25 (1980).

    Article  CAS  Google Scholar 

  19. Somogyi, P. & Klausberger, T. Defined types of cortical interneurone structure space and spike timing in the hippocampus. J. Physiol. (Lond.) 562, 9–26 (2005).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  21. Glickfeld, L.L. & Scanziani, M. Distinct timing in the activity of cannabinoid-sensitive and cannabinoid-insensitive basket cells. Nat. Neurosci. 9, 807–815 (2006).

    Article  CAS  Google Scholar 

  22. Maccaferri, G. & Dingledine, R. Control of feedforward dendritic inhibition by NMDA receptor–dependent spike timing in hippocampal interneurons. J. Neurosci. 22, 5462–5472 (2002).

    Article  CAS  Google Scholar 

  23. Geiger, J.R., Lubke, J., Roth, A., Frotscher, M. & Jonas, P. Submillisecond AMPA receptor–mediated signaling at a principal neuron-interneuron synapse. Neuron 18, 1009–1023 (1997).

    Article  CAS  Google Scholar 

  24. Cruikshank, S.J., Lewis, T.J. & Connors, B.W. Synaptic basis for intense thalamocortical activation of feedforward inhibitory cells in neocortex. Nat. Neurosci. 10, 462–468 (2007).

    Article  CAS  Google Scholar 

  25. Sayer, R.J., Friedlander, M.J. & Redman, S.J. The time course and amplitude of EPSPs evoked at synapses between pairs of CA3/CA1 neurons in the hippocampal slice. J. Neurosci. 10, 826–836 (1990).

    Article  CAS  Google Scholar 

  26. Gabernet, L., Jadhav, S.P., Feldman, D.E., Carandini, M. & Scanziani, M. Somatosensory integration controlled by dynamic thalamocortical feed-forward inhibition. Neuron 48, 315–327 (2005).

    Article  CAS  Google Scholar 

  27. 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).

    Article  CAS  Google Scholar 

  28. Daw, M.I., Ashby, M.C. & Isaac, J.T. Coordinated developmental recruitment of latent fast spiking interneurons in layer IV barrel cortex. Nat. Neurosci. 10, 453–461 (2007).

    Article  CAS  Google Scholar 

  29. Mittmann, W., Koch, U. & Hausser, M. Feed-forward inhibition shapes the spike output of cerebellar Purkinje cells. J. Physiol. (Lond.) 563, 369–378 (2005).

    Article  CAS  Google Scholar 

  30. Saito, T. & Nakatsuji, N. Efficient gene transfer into the embryonic mouse brain using in vivo electroporation. Dev. Biol. 240, 237–246 (2001).

    Article  CAS  Google Scholar 

  31. Petreanu, L., Huber, D., Sobczyk, A. & Svoboda, K. Channelrhodopsin-2–assisted circuit mapping of long-range callosal projections. Nat. Neurosci. 10, 663–668 (2007).

    Article  CAS  Google Scholar 

  32. Bruno, R.M. & Sakmann, B. Cortex is driven by weak, but synchronously active, thalamocortical synapses. Science 312, 1622–1627 (2006).

    CAS  Google Scholar 

  33. Porter, J.T., Johnson, C.K. & Agmon, A. Diverse types of interneurons generate thalamus-evoked feedforward inhibition in the mouse barrel cortex. J. Neurosci. 21, 2699–2710 (2001).

    Article  CAS  Google Scholar 

  34. Poo, C. & Isaacson, J.S. Odor representations in olfactory cortex: “sparse” coding, global inhibition and oscillations. Neuron 62, 850–861 (2009).

    Article  CAS  Google Scholar 

  35. Holmgren, C., Harkany, T., Svennenfors, B. & Zilberter, Y. Pyramidal cell communication within local networks in layer 2/3 of rat neocortex. J. Physiol. (Lond.) 551, 139–153 (2003).

    Article  CAS  Google Scholar 

  36. Beierlein, M., Gibson, J.R. & Connors, B.W. Two dynamically distinct inhibitory networks in layer 4 of the neocortex. J. Neurophysiol. 90, 2987–3000 (2003).

    Article  Google Scholar 

  37. Thomson, A.M., West, D.C., Wang, Y. & Bannister, A.P. Synaptic connections and small circuits involving excitatory and inhibitory neurons in layers 2–5 of adult rat and cat neocortex: triple intracellular recordings and biocytin labeling in vitro. Cereb. Cortex 12, 936–953 (2002).

    Article  Google Scholar 

  38. Buhl, E.H., Halasy, K. & Somogyi, P. Diverse sources of hippocampal unitary inhibitory postsynaptic potentials and the number of synaptic release sites. Nature 368, 823–828 (1994).

    Article  CAS  Google Scholar 

  39. Blitz, D.M. & Regehr, W.G. Timing and specificity of feed-forward inhibition within the LGN. Neuron 45, 917–928 (2005).

    Article  CAS  Google Scholar 

  40. Agmon, A. & Connors, B.W. Thalamocortical responses of mouse somatosensory (barrel) cortex in vitro. Neuroscience 41, 365–379 (1991).

    Article  CAS  Google Scholar 

  41. Vaillend, C., Mason, S.E., Cuttle, M.F. & Alger, B.E. Mechanisms of neuronal hyperexcitability caused by partial inhibition of Na+-K+-ATPases in the rat CA1 hippocampal region. J. Neurophysiol. 88, 2963–2978 (2002).

    Article  CAS  Google Scholar 

  42. Nakamura, M., Sekino, Y. & Manabe, T. GABAergic interneurons facilitate mossy fiber excitability in the developing hippocampus. J. Neurosci. 27, 1365–1373 (2007).

    Article  CAS  Google Scholar 

  43. Winegar, B.D. & MacIver, M.B. Isoflurane depresses hippocampal CA1 glutamate nerve terminals without inhibiting fiber volleys. BMC Neurosci. 7, 5 (2006).

    Article  Google Scholar 

  44. Steiger, J.H. Tests for comparing elements of a correlation matrix. Psychol. Bull. 87, 245–251 (1980).

    Article  Google Scholar 

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Acknowledgements

We thank P. Abelkop for anatomical reconstructions of biocytin filled neurons, F. Fröhlich for developing the initial versions of model, M. Carandini and J. Isaacson for comments and suggestions during the entire course of the project, C. Poo and F. Bertaso for inputs on the manuscript, and all of the members of the Scanziani laboratory for their input on the project and the manuscript. M.S. thanks C. Staub for the original discussions leading to the project. This work was funded in part by the US National Institutes of Health (MH71401 to M.S. and NS061521 to B.V.A.). H.A. is a fellow of the Helen Hay Whithney Foundation. M.S. is an investigator of the Howard Hughes Medical Institute.

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Author notes

  1. Frédéric Pouille and Antonia Marin-Burgin: These authors contributed equally to this work.

Authors and Affiliations

  1. Division of Biology, Howard Hughes Medical Institute and Neurobiology Section, University of California San Diego, La Jolla, California, USA

    Frédéric Pouille, Antonia Marin-Burgin, Hillel Adesnik, Bassam V Atallah & Massimo Scanziani

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  1. Frédéric Pouille
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  2. Antonia Marin-Burgin
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Contributions

F.P. and A.M.-B. conducted the experiments in the hippocampus; H.A. conducted the experiments in the somatosensory cortex; B.V.A. made the model; and M.S. supervised the project and wrote the manuscript.

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Correspondence to Massimo Scanziani.

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Pouille, F., Marin-Burgin, A., Adesnik, H. et al. Input normalization by global feedforward inhibition expands cortical dynamic range. Nat Neurosci 12, 1577–1585 (2009). https://doi.org/10.1038/nn.2441

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