Optimal neuronal tuning for finite stimulus spaces.
Journal Article
·
· Proposed for publication in Neural computation.
OSTI ID:951690
- California Institute of Technology, Pasadena, CA
The efficiency of neuronal encoding in sensory and motor systems has been proposed as a first principle governing response properties within the central nervous system. We present a continuation of a theoretical study presented by Zhang and Sejnowski, where the influence of neuronal tuning properties on encoding accuracy is analyzed using information theory. When a finite stimulus space is considered, we show that the encoding accuracy improves with narrow tuning for one- and two-dimensional stimuli. For three dimensions and higher, there is an optimal tuning width.
- Research Organization:
- Sandia National Laboratories
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 951690
- Report Number(s):
- SAND2004-4547J
- Journal Information:
- Proposed for publication in Neural computation., Journal Name: Proposed for publication in Neural computation.
- Country of Publication:
- United States
- Language:
- English
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