In order to probe into the self-organizing emergence of simple cell orientation selectivity,we tried to construct a neural network model that consists of LGN neurons and simple cells in visual cortex and obeys the Heb...In order to probe into the self-organizing emergence of simple cell orientation selectivity,we tried to construct a neural network model that consists of LGN neurons and simple cells in visual cortex and obeys the Hebbian learning rule. We investigated the neural coding and representation of simple cells to a natural image by means of this model. The results show that the structures of their receptive fields are determined by the preferred orientation selectivity of simple cells.However, they are also decided by the emergence of self-organization in the unsupervision learning process. This kind of orientation selectivity results from dynamic self-organization based on the interactions between LGN and cortex.展开更多
基金the National Natural Science Foundation of China (Grant Nos. 39893340-06, 69835020, 39670186).
文摘In order to probe into the self-organizing emergence of simple cell orientation selectivity,we tried to construct a neural network model that consists of LGN neurons and simple cells in visual cortex and obeys the Hebbian learning rule. We investigated the neural coding and representation of simple cells to a natural image by means of this model. The results show that the structures of their receptive fields are determined by the preferred orientation selectivity of simple cells.However, they are also decided by the emergence of self-organization in the unsupervision learning process. This kind of orientation selectivity results from dynamic self-organization based on the interactions between LGN and cortex.
