<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-06-28T09:48:34Z</responseDate><request verb="GetRecord" identifier="oai:docta.ucm.es:20.500.14352/24406" metadataPrefix="marc">https://docta.ucm.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:docta.ucm.es:20.500.14352/24406</identifier><datestamp>2024-02-26T15:09:28Z</datestamp><setSpec>com_20.500.14352_14</setSpec><setSpec>col_20.500.14352_15</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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      <subfield code="a">Selskii, Anton</subfield>
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      <subfield code="a">Makarov Slizneva, Valeriy</subfield>
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      <subfield code="c">2016</subfield>
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      <subfield code="a">The synchronization of oscillatory activity in neural networks is usually implemented by coupling the state variables describing neuronal dynamics. Here we study another, but complementary mechanism based on a learning process with memory. A driver network, acting as a teacher, exhibits winner-less competition (WLC) dynamics, while a driven network, a learner, tunes its internal couplings according to the oscillations observed in the teacher.
We show that under appropriate training the learner can “copy” the coupling structure and thus synchronize oscillations with the teacher. The replication of the WLC dynamics occurs for intermediate memory lengths only, consequently, the learner network exhibits a phenomenon of learning resonance.</subfield>
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      <subfield code="a">15603547</subfield>
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      <subfield code="a">http//:dx.doi.org.10.1134/S1560354716010056</subfield>
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      <subfield code="a">https://hdl.handle.net/20.500.14352/24406</subfield>
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      <subfield code="a">http://bit.ly/1NcOgjX</subfield>
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      <subfield code="a">Synchronization of heteroclinic circuits through learning in coupled neural networks.</subfield>
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