Paper Info
Title
Computational Modeling of Orientation Tuning Dynamics in Monkey Primary Visual Cortex
Abstract
In the primate visual pathway, orientation tuning of neurons is rst observed in the primary visual cortex. The LGN cells that comprise the thalamic input to V1 are not orientation tuned, but some V1 neurons are quite selective. Two main classes of theoretical models have been oered to explain orientation selectivity: feedforward models, in which inputs from spatially aligned LGN cells are summed together by one cortical neuron; and feedback models, in which an initial weak orientation bias due to convergent LGN input is sharpened and amplied by intracortical feedback. Recent data on the dynamics of orientation tuning, obtained by a cross- correlation technique, may help to distinguish between these classes of models. To test this possibility, we simulated the measurement of orientation tuning dynamics on various receptive eld models, including a simple Hubel-Wiesel type feedforward model: a linear spatio-temporal lter followed by an integrate-and-re spike generator. The computational study reveals that simple feedforward models may account for some aspects of the experimental data, but fail to ex- plain many salient features of orientation tuning dynamics in V1 cells. A simple feedback model of interacting cells is also considered. This model is successful in explaining the appearance of Mexican-hat orientation proles, but other features of the data continue to be unexplained.
Year
DOI
Venue
2000
10.1023/A:1008921231855
Journal of Computational Neuroscience
Keywords
Field
DocType
cortical dynamics,orientation tuning,monkey,primary visual cortex,layers
Receptive field,Visual cortex,Computer science,Theoretical models,Artificial intelligence,Machine learning,Salient,Feed forward
Journal
Volume
Issue
ISSN
8
2
1573-6873
Citations 
PageRank 
References 
13
2.85
0
Authors
4
Name
Order
Citations
PageRank
Mary C. Pugh1144.15
Dario L. Ringach2426.19
Robert Shapley3688.98
M. J. Shelley4132.85