Low error discrimination using a correlated population code.

TitleLow error discrimination using a correlated population code.
Publication TypeJournal Article
Year of Publication2012
AuthorsSchwartz, G, Macke, J, Amodei, D, Tang, H, Berry, MJ
JournalJ Neurophysiol
Volume108
Issue4
Pagination1069-88
Date Published2012 Aug
ISSN1522-1598
KeywordsAction Potentials, Ambystoma, Animals, Discrimination (Psychology), Form Perception, Photic Stimulation, Retinal Ganglion Cells
Abstract

<p>We explored the manner in which spatial information is encoded by retinal ganglion cell populations. We flashed a set of 36 shape stimuli onto the tiger salamander retina and used different decoding algorithms to read out information from a population of 162 ganglion cells. We compared the discrimination performance of linear decoders, which ignore correlation induced by common stimulation, with nonlinear decoders, which can accurately model these correlations. Similar to previous studies, decoders that ignored correlation suffered only a modest drop in discrimination performance for groups of up to ∼30 cells. However, for more realistic groups of 100+ cells, we found order-of-magnitude differences in the error rate. We also compared decoders that used only the presence of a single spike from each cell with more complex decoders that included information from multiple spike counts and multiple time bins. More complex decoders substantially outperformed simpler decoders, showing the importance of spike timing information. Particularly effective was the first spike latency representation, which allowed zero discrimination errors for the majority of shape stimuli. Furthermore, the performance of nonlinear decoders showed even greater enhancement compared with linear decoders for these complex representations. Finally, decoders that approximated the correlation structure in the population by matching all pairwise correlations with a maximum entropy model fit to all 162 neurons were quite successful, especially for the spike latency representation. Together, these results suggest a picture in which linear decoders allow a coarse categorization of shape stimuli, whereas nonlinear decoders, which take advantage of both correlation and spike timing, are needed to achieve high-fidelity discrimination.</p>

DOI10.1152/jn.00564.2011
Alternate JournalJ. Neurophysiol.
PubMed ID22539825
PubMed Central IDPMC3424080
Grant ListEY014196 / EY / NEI NIH HHS / United States