@inproceedings{77bc8355cae74558be89c83b2b60d80f,
title = "An Information Theoretic Approach to the Functional Classification of Neurons",
abstract = "A population of neurons typically exhibits a broad diversity of responses to sensory inputs. The intuitive notion of functional classification is that cells can be clustered so that most of the diversity is captured by the identity of the clusters rather than by individuals within clusters. We show how this intuition can be made precise using information theory, without any need to introduce a metric on the space of stimuli or responses. Applied to the retinal ganglion cells of the salamander, this approach recovers classical results, but also provides clear evidence for subclasses beyond those identified previously. Further, we find that each of the ganglion cells is functionally unique, and that even within the same subclass only a few spikes are needed to reliably distinguish between cells.",
author = "Elad Schneidman and William Bialek and Berry, {Michael J.}",
note = "Publisher Copyright: {\textcopyright} NIPS 2002: Proceedings of the 15th International Conference on Neural Information Processing Systems. All rights reserved.; 15th International Conference on Neural Information Processing Systems, NIPS 2002 ; Conference date: 09-12-2002 Through 14-12-2002",
year = "2002",
language = "English (US)",
series = "NIPS 2002: Proceedings of the 15th International Conference on Neural Information Processing Systems",
publisher = "MIT Press Journals",
pages = "197--204",
editor = "Suzanna Becker and Sebastian Thrun and Klaus Obermayer",
booktitle = "NIPS 2002",
address = "United States",
}