September 2015
Volume 15, Issue 12
Free
Vision Sciences Society Annual Meeting Abstract  |   September 2015
A canonical circuit for visual contextual integration explains induction effects across visual modalities
Author Affiliations
  • David Mély
    Department of Cognitive, Linguistic and Psychological Sciences, Brown University Institute of Brain Science, Brown University
  • Thomas Serre
    Department of Cognitive, Linguistic and Psychological Sciences, Brown University Institute of Brain Science, Brown University
Journal of Vision September 2015, Vol.15, 1121. doi:10.1167/15.12.1121
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      David Mély, Thomas Serre; A canonical circuit for visual contextual integration explains induction effects across visual modalities. Journal of Vision 2015;15(12):1121. doi: 10.1167/15.12.1121.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

The perception of a stimulus is largely determined by its surrounding. Examples abound from color (Land and McCann, 1971) and motion induction (Anstis and Casco, 2006) to orientation tilt effects (O’Toole and Wenderoth, 1976). Many of these phenomena have been studied separately using monkey neurophysiology techniques. In these experiments, a center stimulus coincides with a cell’s classical “center” receptive field (cRF), whose activity is modulated by an annular, extra-cRF “surround” stimulus. A large and disparate body of work in electrophysiology has shown the prevalence of such center-surround integration (CSI); however, we are still lacking a common unifying mechanism across visual modalities. Here, we present an extension of a popular cortical inhibition circuit, divisive normalization (Carandini and Heeger, 2011), which yields a computational model that is consistent with psychophysical data across visual modalities. We have found that a common characteristic of CSI across modalities is a shift in neural population responses induced by surround activity. Typical implementations of the divisive normalization model rely on gain control mechanisms from an ‘untuned’ suppressive pool of cells; that is, the identity of that pool is the same for every cell being suppressed. As such, the circuit cannot account for the selective shift in population response curves observed in contextual effects. In contrast, we show that the addition of a suppressive ‘tuned’ pool of cells which selectively inhibits different parts of a population response curve is sufficient to explain complex shifts in population tuning responses. Overall, our results suggest that a normalization circuit based on two forms of inhibition, gain control and selective suppression, captures shifts in population responses associated with center-surround integration and yields a model that is consistent with contextual phenomena across visual modalities.

Meeting abstract presented at VSS 2015

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