Learning Structure of Sensory Inputs with Synaptic Plasticity Leads to Interference
Synaptic plasticity is often explored as a form of unsupervised adaptationin cortical microcircuits to learn the structure of complex sensoryinputs and thereby improve performance of classification and prediction. The question of whether the specific structure of the input patterns is encoded in the...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2015-08-01
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| Series: | Frontiers in Computational Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fncom.2015.00103/full |