Second order dimensionality reduction using minimum and maximum mutual information models.

Second order dimensionality reduction using minimum and maximum mutual information models.

Conventional methods used to characterize multidimensional neural feature selectivity, such as spike-triggered covariance (STC) or maximally informative dimensions (MID), are limited to Gaussian stimuli or are only able to identify a small number of features due to the curse of dimensionality. To ov...

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Bibliographic Details
Main Authors: Jeffrey D Fitzgerald, Ryan J Rowekamp, Lawrence C Sincich, Tatyana O Sharpee
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2011-10-01
Series:PLoS Computational Biology
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22046122/?tool=EBI

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