Title :
Orientation selective cells emerge in a sparsely coding Boltzmann machine
Author :
Weber, Cornelius ; Obermayer, Klaus
Author_Institution :
Tech. Univ. Berlin, Germany
Abstract :
Investigates a sparse coded Boltzmann machine as a model for the formation of orientation selective receptive fields in primary visual cortex. The model consists of two layers of neurons which are recurrently connected and which represent the lateral geniculate nucleus and primary visual cortex. Neurons have ternary activity values +1, -1, and 0, where the 0-state is degenerate being assumed with higher prior probability. The probability for a (stochastic) activation vector on the net obeys the Boltzmann distribution and maximum-likelihood leads to the standard Boltzmann learning rule. The authors apply a mean-field version of this model to natural image processing and find that neurons develop localized and oriented receptive fields
Keywords :
Boltzmann machines; Boltzmann distribution; Boltzmann learning rule; lateral geniculate nucleus; maximum likelihood; natural image processing; orientation selective cell emergence; orientation selective receptive field formation; primary visual cortex; sparsely coding Boltzmann machine; stochastic activation vector; ternary activity values; visual neurophysiology;
Conference_Titel :
Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470)
Conference_Location :
Edinburgh
Print_ISBN :
0-85296-721-7
DOI :
10.1049/cp:19991123