We have investigated how optimal coding for neural systems changes with the time available for decoding. Optimization was in terms of maximizing information transmission. We have estimated the parameters for Poisson neurons that optimize Shannon transinformation with the assumption of rate coding. We observed a hierarchy of phase transitions from binary coding, for small decoding times, toward discrete (M-ary) coding with two, three and more quantization levels for larger decoding times. We postulate that the presence of subpopulations with specific neural characteristics could be a signiture of an optimal population coding scheme and we use the mammalian auditory system as an example.
|Title of host publication||Noise and fluctuations in biological, biophysical, and biomedical systems|
|Editors||Sergey M. Bezrukov|
|Number of pages||9|
|ISBN (Print)||0-8194-6739-1, 978-0-8194-6739-3|
|Publication status||Published - 2007|
|Event||Noise and fluctuations in biological, biophysical, and biomedical systems - Firenze, Italy|
Duration: 21 Jan 2007 → 23 Jan 2007
|Conference||Noise and fluctuations in biological, biophysical, and biomedical systems|
|Period||21/01/07 → 23/01/07|
Bibliographical noteA. Nikitin ; N. G. Stocks and R. P. Morse "A hierarchy of phase transitions in optimal neuronal coding: from binary to M -ary discrete optimal codes", Proc. SPIE 6602, Noise and Fluctuations in Biological, Biophysical, and Biomedical Systems, 66020H (June 08, 2007);
Copyright 2007 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
- mutual information
- phase transition
- optimal neuronal coding