Title :
Optimize the distribution of preferred stimulus in a population code
Author :
Wu, Si ; Nakahara, Hiroyuki
Author_Institution :
Brain Sci. Inst., RIKEN, Saitama, Japan
Abstract :
We consider two methods to optimize the distribution of preferred stimulus in a population code based on the knowledge of the distribution of stimulus. One method is to maximize the mean Fisher information of the population with respect to the stimulus ensemble. The other is to minimize the lower bound of the mean decoding error. The implication of the two methods is discussed
Keywords :
neural nets; optimisation; mean Fisher information maximisation; mean decoding error lower bound minimisation; population code; preferred stimulus distribution optimisation; stimulus ensemble; Biological information theory; Chemicals; Cost function; Encoding; Gaussian noise; Maximum likelihood decoding; Maximum likelihood estimation; Mutual information; Neurons; Optimization methods;
Conference_Titel :
Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-5871-6
DOI :
10.1109/ICONIP.1999.844008
