Abstract
The complexity of natural stimuli has made it difficult to understand how cortical neurons encode and process information about them. Even in V1, where neurons have well characterized receptive field properties, efforts to deduce which features of a natural scene stimulus a neuron responds to, have generally been unable to fully account for most of the neurons' spiking statistics. It has been proposed that this is at least partly due to activity of the network in which the neuron is embedded. Such activity depends on the stimulus in the whole visual field, not only that in the neuron's receptive field.
Highlights
Eighteenth Annual Computational Neuroscience Meeting: CNS*2009 Don H Johnson Meeting abstracts – A single PDF containing all abstracts in this Supplement is available here. http://www.biomedcentral.com/content/pdf/1471-2202-10-S1-info.pdf
Even in V1, where neurons have well characterized receptive field properties, efforts to deduce which features of a natural scene stimulus a neuron responds to, have generally been unable to fully account for most of the neurons' spiking statistics
The Generalized Linear Models (GLMs) included a PSTH-like term accounting for the stimulus and a second renewal process-type term accounting for the neuron's previous spiking history
Summary
Eighteenth Annual Computational Neuroscience Meeting: CNS*2009 Don H Johnson Meeting abstracts – A single PDF containing all abstracts in this Supplement is available here. http://www.biomedcentral.com/content/pdf/1471-2202-10-S1-info.pdf . Published: 13 July 2009 BMC Neuroscience 2009, 10(Suppl 1):P306 doi:10.1186/1471-2202-10-S1-P306 Even in V1, where neurons have well characterized receptive field properties, efforts to deduce which features of a natural scene stimulus a neuron responds to, have generally been unable to fully account for most of the neurons' spiking statistics.
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