Tony Movshon

Local And Global Operations Performed By Neurons In Macaque Area MT

New York University

Neurons in macaque area MT have receptive fields that are roughly 30 times larger than those of their inputs from V1. It is generally assumed that the large RF size in MT results from convergence of inputs from a wide area of V1, but the way that visual signals are transformed by that convergence is unclear. We have uncovered two contrasting rules for this convergence, one local and one global.

One observation is derived from the demonstration that MT neurons combine information from multiple orientation sensitive neurons in V1 to compute "pattern motion". When the different orientations that define pattern motion are presented to spatially separated patches within the RF, the pattern motion calculation is disrupted and MT neuron responses mostly reflect the independent local motions.

A second observation is based on earlier results showing that cortical neuron responses are reduced following a period of adaptation to a strong stimulus. When adapting and test stimuli are presented to different parts of an MT RF, the adaptation effect does not transfer from one patch to the other, suggesting that the adaptation effect, like the motion calculation, is based on local computations.

A third observation is based on the observation that visual stimuli affect the contrast gain of cortical neurons through the action of a recurrent gain control network. Presenting a stimulus to one part of an MT RF strongly affects contrast gain for stimuli presented in other, remote parts of the RF, suggesting that contrast gain control is based on global, not local, computations.

These observations are consistent with a model in which most RF properties are determined by local circuits before they converge to create large RFs. Overall contrast gain, however, seems to be different, and is controlled by convergent signals from the whole large RF.
Thursday, March 28, 2024
About the Swartz Foundation...
 
The Swartz Foundation was established by Jerry Swartz (bio) in 1994 . . .
more>
 
Follow us...
 
The Swartz Foundation is on Twitter: SwartzCompNeuro
more>
 
 
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 2024