Excitatory and suppressive receptive field subunits in awake monkey primary visual cortex (V1)

An essential step in understanding visual processing is to characterize the neuronal receptive fields (RFs) at each stage of the visual pathway. However, RF characterization beyond simple cells in the primary visual cortex (V1) remains a major challenge. Recent application of spike-triggered covariance (STC) analysis has greatly facilitated characterization of complex cell RFs in anesthetized animals. Here we apply STC to RF characterization in awake monkey V1. We found up to nine subunits for each cell, including one or two dominant excitatory subunits as described by the standard model, along with additional excitatory and suppressive subunits with weaker contributions. Compared with the dominant subunits, the nondominant excitatory subunits prefer similar orientations and spatial frequencies but have larger spatial envelopes. They contribute to response invariance to small changes in stimulus orientation, position, and spatial frequency. In contrast, the suppressive subunits are tuned to orientations 45°–90° different from the excitatory subunits, which may underlie cross-orientation suppression. Together, the excitatory and suppressive subunits form a compact description of RFs in awake monkey V1, allowing prediction of the responses to arbitrary visual stimuli.

[1]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.

[2]  L. Maffei,et al.  Neural Correlate of Perceptual Adaptation to Gratings , 1973, Science.

[3]  J. Movshon,et al.  Spatial summation in the receptive fields of simple cells in the cat's striate cortex. , 1978, The Journal of physiology.

[4]  J. Movshon,et al.  Receptive field organization of complex cells in the cat's striate cortex. , 1978, The Journal of physiology.

[5]  E H Adelson,et al.  Spatiotemporal energy models for the perception of motion. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[6]  J. P. Jones,et al.  The two-dimensional spatial structure of simple receptive fields in cat striate cortex. , 1987, Journal of neurophysiology.

[7]  Klein,et al.  Nonlinear directionally selective subunits in complex cells of cat striate cortex. , 1987, Journal of neurophysiology.

[8]  William Bialek,et al.  Real-time performance of a movement-sensitive neuron in the blowfly visual system: coding and information transfer in short spike sequences , 1988, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[9]  A. B. Bonds Role of Inhibition in the Specification of Orientation Selectivity of Cells in the Cat Striate Cortex , 1989, Visual Neuroscience.

[10]  A. B. Bonds,et al.  Classifying simple and complex cells on the basis of response modulation , 1991, Vision Research.

[11]  Chao-Yi Li,et al.  A simple and comprehensive method for the construction, repair and recycling of single and double tungsten microelectrodes , 1995, Journal of Neuroscience Methods.

[12]  R. Shapley,et al.  The use of m-sequences in the analysis of visual neurons: Linear receptive field properties , 1997, Visual Neuroscience.

[13]  Frances S. Chance,et al.  Complex cells as cortically amplified simple cells , 1999, Nature Neuroscience.

[14]  William Bialek,et al.  Adaptive Rescaling Maximizes Information Transmission , 2000, Neuron.

[15]  D. Wilkin,et al.  Neuron , 2001, Brain Research.

[16]  Liam Paninski,et al.  Convergence properties of three spike-triggered analysis techniques , 2003, NIPS.

[17]  D. Ringach,et al.  On the classification of simple and complex cells , 2002, Vision Research.

[18]  J. Touryan,et al.  Isolation of Relevant Visual Features from Random Stimuli for Cortical Complex Cells , 2002, The Journal of Neuroscience.

[19]  Bevil R. Conway,et al.  Applicability of white-noise techniques to analyzing motion responses. , 2010, Journal of neurophysiology.

[20]  Adrienne L. Fairhall,et al.  What Causes a Neuron to Spike? , 2003, Neural Computation.

[21]  J. Gallant,et al.  Natural Stimulus Statistics Alter the Receptive Field Structure of V1 Neurons , 2004, The Journal of Neuroscience.

[22]  J. Touryan,et al.  Spatial Structure of Complex Cell Receptive Fields Measured with Natural Images , 2005, Neuron.

[23]  Eero P. Simoncelli,et al.  Spatiotemporal Elements of Macaque V1 Receptive Fields , 2005, Neuron.

[24]  Feng Qi Han,et al.  Cortical Sensitivity to Visual Features in Natural Scenes , 2005, PLoS biology.

[25]  Kenneth D. Miller,et al.  Adaptive filtering enhances information transmission in visual cortex , 2006, Nature.

[26]  Laurenz Wiskott,et al.  On the Analysis and Interpretation of Inhomogeneous Quadratic Forms as Receptive Fields , 2006, Neural Computation.

[27]  R. Rosenfeld Nature , 2009, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.