Can Hebbian Volume Learning Explain Discontinuities in Cortical Maps?

摘要

It has recently been shown that orientation and retinotopic position, both of which are mapped in primary visual cortex, can show correlated jumps (Das & Gilbert, 1997). This is not consistent with maps generated by Ko- honen's algorithm (Kohonen, 1982), where changes in mapped variables tend to be anticorrelated. We show that it is possible to obtain corre- lated jumps by introducing a Hebbian component (Hebb, 1949) into Ko- honen's algorithm.