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Shih-Cheng Yen, Jonathan L. Baker, Jean-Philippe Lachaux, Charles M. Gray; Natural movies evoke precise responses in cat visual cortex that are not predicted from non-uniform Poisson processes. Journal of Vision 2004;4(8):281. doi: 10.1167/4.8.281.
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© 2015 Association for Research in Vision and Ophthalmology.
The responses of striate cortical neurons are often modeled using non-uniform Poisson processes. This model has proved to be a good model of responses to simple, artificial stimuli, but has yet to be tested on naturalistic stimuli. We recorded the responses of isolated neurons in striate cortex of anesthetized cats while presenting repeated naturalistic movie sequences with frame durations of 35 ms (29 Hz). We found episodes of spike-count variability that were sub-Poisson (i.e. Fano Factor less than 1) in 61% (22/36) of the responsive neurons in our database, and in 21% (134/638) of the 35 ms windows with a mean spike count of at least 1. We also found episodes of spike times that were more precise than predicted in 78% (28/36) of the neurons, and in 22% (139/638) of the 35 ms windows with a mean spike count of at least 1. In addition, when we used an event analysis method to compute the interval between significant response epochs, we found inter-event intervals that were shorter than the frame duration in 27% (10/36) of the neurons. These rapid changes in the response, which made up 13% (28/216) of the intervals in those 10 neurons, had a range of inter-event intervals that were larger than those usually reported for neuronal bursts in striate cortex. This indicated that the neuronal responses were varying more dynamically than predicted. We verified that the episodes of low spike-count variability, high spike-time precision, and rapid response changes were not simply due to large changes in luminance in the movies resulting from scene changes. Our results suggest that when stimulated by natural movies, neurons in the striate cortex of the cat exhibit responses that are not well modeled by non-uniform Poisson processes.
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