Beyond GLMs: a generative mixture modeling approach to neural system identification.
Generalized linear models (GLMs) represent a popular choice for the probabilistic characterization of neural spike responses. While GLMs are attractive for their computational tractability, they also impose strong assumptions and thus only allow for a limited range of stimulus-response relationships...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2013-01-01
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| Series: | PLoS Computational Biology |
| Online Access: | http://europepmc.org/articles/PMC3836720?pdf=render |