Decoding the activity of neuronal populations in macaque primary visual cortex.

ABSTRACT: Visual function depends on the accuracy of signals carried by visual cortical neurons. Combining information across neurons should improve this accuracy because single neuron activity is variable. We examined the reliability of information inferred from populations of simultaneously recorded neurons in macaque primary visual cortex. We considered a decoding framework that computes the likelihood of visual stimuli from a pattern of population activity by linearly combining neuronal responses and tested this framework for orientation estimation and discrimination. We derived a simple parametric decoder assuming neuronal independence and a more sophisticated empirical decoder that learned the structure of the measured neuronal response distributions, including their correlated variability. Th

SUBMITTER: Graf AB 

PROVIDER: S-EPMC3081541 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature