Literature DB >> 20064399

Complex dynamics of V1 population responses explained by a simple gain-control model.

Yiu Fai Sit1, Yuzhi Chen, Wilson S Geisler, Risto Miikkulainen, Eyal Seidemann.   

Abstract

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. 2009 Elsevier Inc. All rights reserved.

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Year:  2009        PMID: 20064399      PMCID: PMC2807412          DOI: 10.1016/j.neuron.2009.08.041

Source DB:  PubMed          Journal:  Neuron        ISSN: 0896-6273            Impact factor:   17.173


  52 in total

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2.  The relationship between voltage-sensitive dye imaging signals and spiking activity of neural populations in primate V1.

Authors:  Yuzhi Chen; Chris R Palmer; Eyal Seidemann
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3.  Dominant vertical orientation processing without clustered maps: early visual brain dynamics imaged with voltage-sensitive dye in the pigeon visual Wulst.

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Review 10.  Catching the voltage gradient-asymmetric boost of cortical spread generates motion signals across visual cortex: a brief review with special thanks to Amiram Grinvald.

Authors:  Dirk Jancke
Journal:  Neurophotonics       Date:  2017-02-10       Impact factor: 3.593

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