Title :
Effects of noise correlations on population coding
Author_Institution :
Grad. Sch. of Inf. Sci., Tohoku Univ., Sendai, Japan
Abstract :
Neural responses show trial-to-trial variability (=noise) even if the same sensory stimulus is presented. Therefore the brain is considered to average and reduce the noises in order to obtain accurate sensory representations. However, Zohary et al. (1994) theoretically showed that the noises cannot be reduced when inter-neuronal correlations in noises, if any, exist in the simulation of a simple mathematical model. Here we analyze the effects of noise correlations on population coding in extended, but still simple, mathematical models.
Keywords :
brain; correlation methods; mathematical analysis; neurophysiology; brain; interneuronal correlations; mathematical model; neural responses; noise correlations; population coding; sensory representations; sensory stimulus; trial-to-trial variability;
Conference_Titel :
Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on
Conference_Location :
Kobe
Print_ISBN :
978-1-4673-2742-8
DOI :
10.1109/SCIS-ISIS.2012.6505071
