J. Andrew Henrie

Population models for coding orientation in the visual cortex, and the effect of stimulus size

New York University

We have previously analyzed the classical psychophysical relationship between orientation acuity and stimulus size by applying an optimal decision model to the output of a population of physiologically inspired linear spatial filters (Henrie & Shapley, 2001). The implementation of this model failed to account for the relatively slow falloff in orientation acuity with decreasing stimulus size. This model estimates orientation acuity by application of optimal estimation techniques to the half-rectified response of a bank of linear spatial operators spanning all orientations whose size and form (Gabor) were matched to the single unit properties of primary visual cortex (V1) neurons. This model, which has been applied to many visual psychophysical phenomena, predicted a much faster decrease in acuity with decreasing stimulus size than observed behaviorally. The suggested reason for this discrepancy is a fundamental inadequacy of a static linear filter at capturing the response selectivity of V1 units. In the work I will talk about here, the size of the linear Gabor filter (the first stage of the model) was decreased until the model's output fit the behavioral relationship between orientation acuity and stimulus size. The spatial tuning properties of these relatively tiny Gabor filters was then compared to the tuning properties of V1 neurons. There is a considerable discrepancy between these fitted Gabor functions and measured V1 receptive fields. We interpret the discrepancy between the linear filter which can account for the data and the observable form of V1 selectivity as a reflection of a non-linear interaction among the individual elements in V1. In particular, non-linear suppression (e.g. inhibition) from units preferring different stimuli may be able to explain this. For example, divisive inhibition has recently been used as a single explanation for detection and discrimination of spatial stimuli (Itti et al. 2000), and Ringach et al. (submitted for publication) found physiological evidence that highly selective neurons in V1 require non-linear suppression to account for their response.

Monday, June 5, 2023
About the Swartz Foundation...
The Swartz Foundation was established by Jerry Swartz (bio) in 1994 . . .
Follow us...
The Swartz Foundation is on Twitter: SwartzCompNeuro
2013 Stony Brook Mind/Brain Lecture - Michael Wigler, PhD
2012 Stony Brook Mind/Brain Lecture - John Donoghue
Sloan-Swartz Centers Annual Meeting 2011
2011 Stony Brook Mind/Brain Lecture - Allison J. Doupe
2011 Banbury Workshop
Sloan-Swartz Centers Annual Meeting 2010
2010 Stony Brook Mind/Brain Lecture
Sloan-Swartz Centers Annual Meeting 2009
Conference on Neural Dynamics
2009 Stony Brook Mind/Brain Lecture
Canonical Neural Computation, April 2009
2009 Banbury Workshop
Sloan-Swartz Centers Annual Meeting 2008
Theoretical and Experimental Approaches to Auditory and Visual Attention - Banbury 2008
Stony Brook Mind/Brain 2008: Patricia Smith Churchland, B. Phil. D
Sloan-Swartz Centers Annual Meeting 2007
New Frontiers In Studies Of Nonconscious Processing - Banbury 2007
Stony Brook Mind/Brain 2007: Professor Michael Shadlen, MD, PhD
Multi-level Brain Modeling Workshop 2006
Sloan Swartz Centers Annual Meeting 2006
Banbury 2006: Computational Approaches to Cortical Functions
Stony Brook Mind/Brain 2006: Helen Fisher -- Lecture Videos
Sloan-Swartz Centers for Theoretical Neurobiology
Swartz Center for Computational Neuroscience
Banbury Center Workshop Series
Other Events
www.theswartzfoundation.org                           Copyright © The Swartz Foundation 2023