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Adaptation maintains population homeostasis in primary visual cortex

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Abstract

Sensory systems exhibit mechanisms of neural adaptation, which adjust neuronal activity on the basis of recent stimulus history. In primary visual cortex (V1) in particular, adaptation controls the responsiveness of individual neurons and shifts their visual selectivity. What benefits does adaptation confer on a neuronal population? We measured adaptation in the responses of populations of cat V1 neurons to stimulus ensembles with markedly different statistics of stimulus orientation. We found that adaptation served two homeostatic goals. First, it maintained equality in the time-averaged responses across the population. Second, it maintained independence in selectivity across the population. Adaptation scaled and distorted population activity according to a simple multiplicative rule that depended on neuronal orientation preference and on stimulus orientation. We conclude that adaptation in V1 acts as a mechanism of homeostasis, enforcing a tendency toward equality and independence in neural activity across the population.

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Figure 1: Adaptation in visual cortex prevents biases in the population.
Figure 2: Adaptation equalizes population responses.
Figure 3: Adaptation decorrelates population responses.
Figure 4: Neuron-specific and stimulus-specific components of adaptation.
Figure 5: Effects of adaptation on tuning curves and population responses.
Figure 6: Adaptation to biased ensembles does not affect pairwise noise correlations.

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References

  1. Anstis, S., Verstraten, F.A. & Mather, G. The motion aftereffect. Trends Cogn. Sci. 2, 111–117 (1998).

    Article  CAS  Google Scholar 

  2. Gardner, J.L., Tokiyama, S.N. & Lisberger, S.G. A population decoding framework for motion aftereffects on smooth pursuit eye movements. J. Neurosci. 24, 9035–9048 (2004).

    Article  CAS  Google Scholar 

  3. Gibson, J.J. & Radner, M. Adaptation, after-effect, and contrast in the perception of tilted lines: I. Quantitative studies. J. Exp. Psychol. 20, 453–467 (1937).

    Article  Google Scholar 

  4. Jin, D.Z., Dragoi, V., Sur, M. & Seung, H.S. Tilt aftereffect and adaptation-induced changes in orientation tuning in visual cortex. J. Neurophysiol. 94, 4038–4050 (2005).

    Article  Google Scholar 

  5. Wark, B., Lundstrom, B.N. & Fairhall, A. Sensory adaptation. Curr. Opin. Neurobiol. 17, 423–429 (2007).

    Article  CAS  Google Scholar 

  6. Kohn, A. Visual adaptation: physiology, mechanisms, and functional benefits. J. Neurophysiol. 97, 3155–3164 (2007).

    Article  Google Scholar 

  7. Smirnakis, S.M., Berry, M.J., Warland, D.K., Bialek, W. & Meister, M. Adaptation of retinal processing to image contrast and spatial scale. Nature 386, 69–73 (1997).

    Article  CAS  Google Scholar 

  8. Brenner, N., Bialek, W. & de Ruyter van Steveninck, R. Adaptive rescaling maximizes information transmission. Neuron 26, 695–702 (2000).

    Article  CAS  Google Scholar 

  9. Fairhall, A.L., Lewen, G.D., Bialek, W. & de Ruyter Van Steveninck, R.R. Efficiency and ambiguity in an adaptive neural code. Nature 412, 787–792 (2001).

    Article  CAS  Google Scholar 

  10. Ulanovsky, N., Las, L. & Nelken, I. Processing of low-probability sounds by cortical neurons. Nat. Neurosci. 6, 391–398 (2003).

    Article  CAS  Google Scholar 

  11. Condon, C.D. & Weinberger, N.M. Habituation produces frequency-specific plasticity of receptive fields in the auditory cortex. Behav. Neurosci. 105, 416–430 (1991).

    Article  CAS  Google Scholar 

  12. Nagel, K.I. & Doupe, A.J. Temporal processing and adaptation in the songbird auditory forebrain. Neuron 51, 845–859 (2006).

    Article  CAS  Google Scholar 

  13. Dean, I., Harper, N.S. & McAlpine, D. Neural population coding of sound level adapts to stimulus statistics. Nat. Neurosci. 8, 1684–1689 (2005).

    Article  CAS  Google Scholar 

  14. Maravall, M., Petersen, R.S., Fairhall, A.L., Arabzadeh, E. & Diamond, M.E. Shifts in coding properties and maintenance of information transmission during adaptation in barrel cortex. PLoS Biol. 5, e19 (2007).

    Article  Google Scholar 

  15. Movshon, J.A. & Lennie, P. Pattern-selective adaptation in visual cortical neurones. Nature 278, 850–852 (1979).

    Article  CAS  Google Scholar 

  16. Müller, J.R., Metha, A.B., Krauskopf, J. & Lennie, P. Rapid adaptation in visual cortex to the structure of images. Science 285, 1405–1408 (1999).

    Article  Google Scholar 

  17. Dragoi, V., Sharma, J., Miller, E.K. & Sur, M. Dynamics of neuronal sensitivity in visual cortex and local feature discrimination. Nat. Neurosci. 5, 883–891 (2002).

    Article  CAS  Google Scholar 

  18. Ohzawa, I., Sclar, G. & Freeman, R.D. Contrast gain control in the cat visual cortex. Nature 298, 266–268 (1982).

    Article  CAS  Google Scholar 

  19. Carandini, M. & Ferster, D. A tonic hyperpolarization underlying contrast adaptation in cat visual cortex. Science 276, 949–952 (1997).

    Article  CAS  Google Scholar 

  20. Sanchez-Vives, M.V., Nowak, L.G. & McCormick, D.A. Membrane mechanisms underlying contrast adaptation in cat area 17 in vivo. J. Neurosci. 20, 4267–4285 (2000).

    Article  CAS  Google Scholar 

  21. Dragoi, V., Sharma, J. & Sur, M. Adaptation-induced plasticity of orientation tuning in adult visual cortex. Neuron 28, 287–298 (2000).

    Article  CAS  Google Scholar 

  22. Yao, H., Shen, Y. & Dan, Y. Intracortical mechanism of stimulus-timing-dependent plasticity in visual cortical orientation tuning. Proc. Natl. Acad. Sci. USA 101, 5081–5086 (2004).

    Article  CAS  Google Scholar 

  23. Dayan, P. & Abbott, L.F. Theoretical Neuroscience (MIT Press, 2001).

  24. Schwartz, O., Hsu, A. & Dayan, P. Space and time in visual context. Nat. Rev. Neurosci. 8, 522–535 (2007).

    Article  CAS  Google Scholar 

  25. Clifford, C.W., Wenderoth, P. & Spehar, B. A functional angle on some after-effects in cortical vision. Proc. R. Soc. Lond. B 267, 1705–1710 (2000).

    Article  CAS  Google Scholar 

  26. Ullman, S. & Schechtman, G. Adaptation and gain normalization. Proc. R. Soc. Lond. B Biol. Sci. 216, 299–313 (1982).

    Article  CAS  Google Scholar 

  27. Benucci, A., Ringach, D.L. & Carandini, M. Coding of stimulus sequences by population responses in visual cortex. Nat. Neurosci. 12, 1317–1324 (2009).

    Article  CAS  Google Scholar 

  28. Cohen, M.R. & Kohn, A. Measuring and interpreting neuronal correlations. Nat. Neurosci. 14, 811–819 (2011).

    Article  CAS  Google Scholar 

  29. Barlow, H.B. & Földiák, P. in The Computing Neuron (eds. Durbin, R., Miall, C. & Mitchison, C.) 54–72 (Addison-Wesley, 1989).

  30. Barlow, H.B. in Vision: Coding and Efficiency (ed. Blakemore, C.) 363–375 (Cambridge Univ. Press, 1990).

  31. Reich, D.S., Mechler, F. & Victor, J.D. Independent and redundant information in nearby cortical neurons. Science 294, 2566–2568 (2001).

    Article  CAS  Google Scholar 

  32. Wark, B., Fairhall, A. & Rieke, F. Timescales of inference in visual adaptation. Neuron 61, 750–761 (2009).

    Article  CAS  Google Scholar 

  33. Ulanovsky, N., Las, L., Farkas, D. & Nelken, I. Multiple time scales of adaptation in auditory cortex neurons. J. Neurosci. 24, 10440–10453 (2004).

    Article  CAS  Google Scholar 

  34. Kohn, A. & Movshon, J.A. Adaptation changes the direction tuning of macaque MT neurons. Nat. Neurosci. 7, 764–772 (2004).

    Article  CAS  Google Scholar 

  35. Gutnisky, D.A. & Dragoi, V. Adaptive coding of visual information in neural populations. Nature 452, 220–224 (2008).

    Article  CAS  Google Scholar 

  36. Wissig, S.C. & Kohn, A. The influence of surround suppression on adaptation effects in primary visual cortex. J. Neurophysiol. 107, 3370–3384 (2012).

    Article  Google Scholar 

  37. Sekuler, R. & Pantle, A. A model for after-effects of seen movement. Vision Res. 7, 427–439 (1967).

    Article  CAS  Google Scholar 

  38. Blakemore, C., Nachmias, J. & Sutton, P. The perceived spatial frequency shift: evidence for frequency-selective neurones in the human brain. J. Physiol. (Lond.) 210, 727–750 (1970).

    Article  CAS  Google Scholar 

  39. Blakemore, C. & Campbell, F.W. On the existence of neurones in the human visual system selectively sensitive to the orientation and size of retinal images. J. Physiol. (Lond.) 203, 237–260 (1969).

    Article  CAS  Google Scholar 

  40. Graham, N.V.S. Visual Pattern Analyzers (Oxford Univ. Press, 1989).

  41. Clifford, C.W. et al. Visual adaptation: neural, psychological and computational aspects. Vision Res. 47, 3125–3131 (2007).

    Article  Google Scholar 

  42. Chung, S., Li, X. & Nelson, S.B. Short-term depression at thalamocortical synapses contributes to rapid adaptation of cortical sensory responses in vivo. Neuron 34, 437–446 (2002).

    Article  CAS  Google Scholar 

  43. Chance, F.S. & Abbott, L.F. Input-specific adaptation in complex cells through synaptic depression. Neurocomputing 38–40, 141–146 (2001).

    Article  Google Scholar 

  44. Stocker, A.A. & Simoncelli, E.P. Visual motion aftereffects arise from a cascade of two isomorphic adaptation mechanisms. J. Vis. 9, 9 1–14, doi:10.1167/9.9.9 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Kohn, A. & Movshon, J.A. Neuronal adaptation to visual motion in area MT of the macaque. Neuron 39, 681–691 (2003).

    Article  CAS  Google Scholar 

  46. Turrigiano, G.G. & Nelson, S.B. Homeostatic plasticity in the developing nervous system. Nat. Rev. Neurosci. 5, 97–107 (2004).

    Article  CAS  Google Scholar 

  47. Katzner, S. et al. Local origin of field potentials in visual cortex. Neuron 61, 35–41 (2009).

    Article  CAS  Google Scholar 

  48. Movshon, J.A., Thompson, I.D. & Tolhurst, D.J. Spatial and temporal contrast sensitivity of neurones in areas 17 and 18 of the cat's visual cortex. J. Physiol. (Lond.) 283, 101–120 (1978).

    Article  CAS  Google Scholar 

  49. Simoncelli, E.P., Paninski, L., Pillow, J. & Schwartz, O. Characterization of neural responses with stochastic stimuli. Cognitive Neurosciences III 3rd edn. (ed. Gazzaniga, M.S.) 327–338 (2004).

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Acknowledgements

We thank L. Busse and S. Katzner for help with data acquisition, and numerous colleagues for useful suggestions. This work was supported by the US National Institutes of Health, the European Research Council and the Wellcome Trust. M.C. holds the GlaxoSmithKline/Fight for Sight Chair in Visual Neuroscience.

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A.B. and M.C. conceived the experiments, A.B. acquired the data, A.B. did the analysis in Figures 1,2,3, M.C. did the analysis in Figures 4 and 5, and A.S. did the analysis in Figure 6. A.B. and M.C. wrote the paper.

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Correspondence to Andrea Benucci.

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The authors declare no competing financial interests.

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Benucci, A., Saleem, A. & Carandini, M. Adaptation maintains population homeostasis in primary visual cortex. Nat Neurosci 16, 724–729 (2013). https://doi.org/10.1038/nn.3382

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