Summary
International Symposium on Nonlinear Theory and its Applications
2005
Session Number:1-2-3
Session:
Number:1-2-3-1
Topological maps by STDP for input space of discrete and continuous features
Yutaka Sakai,
pp.230-233
Publication Date:2005/10/18
Online ISSN:2188-5079
Summary:
Position-and-scale-free representations of shapes are acquired by neurons in the inferior temporal (IT) cortex. So each neuron receives information from the whole visual field. Familiar shapes are extremely limited from all the possible shapes on the whole visual field. So they must be clustered in the shape space to have mixed structure of continuity and discreteness. We demonstrate that multiple representation can be acquired in a spikebased model for topological maps based on the spiketiming-dependent synaptic plasticity (STDP), subjected to a set of inputs on two rings, which is a simple example of mixed structure. In this representation, the position on each ring is represented by a center of active neurons and the difference of rings is represented by a detail pattern of active neurons. Neurons in the same region exhibit high activities for an input on the other ring. The result is consistent with the fact observed in IT cortex that neighboring neurons exhibit different preferences while the region of active neurons is continuously shifted for continuous changes of object.