[[Publications]]
*''Self-organization of spatio-temporal visual receptive fields''
**T. Takahashi and Y. Hirai,
IEICE Transactions on Information and Systems, vol.E79-D, no.7, pp.980--989, 1996.
**Abstract
A self-organizing neural network model of spatio-temporal visual receptive fields is proposed. It consists of a one-layer linear learning network with multiple temporal input channels, and each temporal channel has different impulse response. Every weight of the learning network is modified according to a Hebb-type learning algorithm proposed by Sanger. It is shown by simulation studies that various types of spatio-temporal receptive fields are self-organized by the network with random noise inputs. Some of them have similar response characteristics to X- and Y-type cells found in mammalian retina. The properties of receptive fields obtained by the network are analyzed theoretically. It is shown that only circularly symmetric receptive fields change their spatio-temporal characteristics depending on the bias of inputs. In particular, when the inputs are non-zero mean, the temporal properties of center-surround type receptive fields become heterogeneous and alter depending on the positions in the receptive fields.
**Keywords
self-organization,spatio-temporal receptive field
**PDF
http://search.ieice.org/1996/files/e000d07.htm#e79-d,7,980
![[PukiWiki]](image/blackuni3-80x80.png "[PukiWiki]")
