Presentation 2005/6/16
Topological maps by STDP for input space with discrete and continuous features
Yutaka SAKAI,
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Abstract(in English) 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 spike-based model for topological maps based on the spike-timing-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.
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Keyword(in English) spike-timing-dependent plasticity (STDP) / SOM / topological map / inferior temporal (IT) cortex
Paper # NC2005-17
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Committee NC
Conference Date 2005/6/16(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Topological maps by STDP for input space with discrete and continuous features
Sub Title (in English)
Keyword(1) spike-timing-dependent plasticity (STDP)
Keyword(2) SOM
Keyword(3) topological map
Keyword(4) inferior temporal (IT) cortex
1st Author's Name Yutaka SAKAI
1st Author's Affiliation Faculty of Engineering, Tamagawa University()
Date 2005/6/16
Paper # NC2005-17
Volume (vol) vol.105
Number (no) 130
Page pp.pp.-
#Pages 6
Date of Issue