Abstract
In most areas of the brain, information is encoded in the correlated activity of large populations of neurons. We ask how neural responses should be coupled to best represent information about different ensembles of correlated stimuli. Three classical population coding strategies are independence, decorrelation and error correction. Here we demonstrate that balance between the intrinsic noise level and the statistics of the input ensemble induces smooth transitions between these three coding strategies in a network composed of pairwise-coupled neurons and tuned to maximize its information capacity.
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
We demonstrate that balance between the intrinsic noise level and the statistics of the input ensemble induces smooth transitions between these three coding strategies in a network composed of pairwise-coupled neurons and tuned to maximize its information capacity
We find the pairwise couplings to maximize information conveyed by neural states about different input ensembles in the presence of intrinsic noise
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 . Email: Gasper Tkacik* - gtkacik@sas.upenn.edu * Corresponding author from Eighteenth Annual Computational Neuroscience Meeting: CNS*2009 Berlin, Germany. Published: 13 July 2009 BMC Neuroscience 2009, 10(Suppl 1):O13 doi:10.1186/1471-2202-10-S1-O13 In most areas of the brain, information is encoded in the correlated activity of large populations of neurons.
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