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Complex Dynamics of V1 Population Responses Explained by a Simple Gain-Control Model (2009)
Yiu Fai Sit
, Yuzhi Chen,
Wilson S. Geisler
,
Risto Miikkulainen
, and
Eyal Seidemann
To understand sensory encoding and decoding, it is essential to characterize the dynamics of population responses in sensory cortical areas. Using voltage-sensitive dye imaging in awake, fixating monkeys, we obtained complete quantitative measurements of the spatiotemporal dynamics of V1 responses over the entire region activated by small, briefly presented stimuli. The responses exhibit several complex properties: they begin to rise approximately simultaneously over the entire active region, but reach their peak more rapidly at the center. However, at stimulus offset the responses fall simultaneously and at the same rate at all locations. Although response onset depends on stimulus contrast, both the peak spatial profile and the offset dynamics are independent of contrast. We show that these results are consistent with a simple population gain-control model that generalizes earlier single-neuron contrast gain-control models. This model provides valuable insight and is likely to be applicable to other brain areas.
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Citation:
Neuron
, 64:943-956, 2009.
Bibtex:
@Article{sit:neuron09, title={Complex Dynamics of V1 Population Responses Explained by a Simple Gain-Control Model}, author={Yiu Fai Sit and Yuzhi Chen and Wilson S. Geisler and Risto Miikkulainen and Eyal Seidemann}, volume={64}, journal={Neuron}, pages={943-956}, url="http://nn.cs.utexas.edu/?sit:neuron09", year={2009} }
People
Wilson S. Geisler
Former Collaborator
geisler [at] psy utexas edu
Risto Miikkulainen
Faculty
risto [at] cs utexas edu
Eyal Seidemann
Former Collaborator
eyal [at] mail cps utexas edu
Yiu Fai Sit
Ph.D. Alumni
yfsit [at] cs utexas edu
Areas of Interest
Visual Cortex
Neuroimaging
Computational Neuroscience