<?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>2026-04-17T04:07:37Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:10230/23077" metadataPrefix="marc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:10230/23077</identifier><datestamp>2025-12-24T09:03:26Z</datestamp><setSpec>com_2072_6</setSpec><setSpec>col_2072_452952</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">Deco, Gustavo</subfield>
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      <subfield code="a">Jirsa, Viktor K.</subfield>
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      <subfield code="c">2015-01-27T08:32:03Z</subfield>
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      <subfield code="c">2015-01-27T08:32:03Z</subfield>
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      <subfield code="c">2012</subfield>
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      <subfield code="a">The ongoing activity of the brain at rest, i.e., under no stimulation and in absence of any task, is astonishingly highly structured into/nspatiotemporal patterns. These spatiotemporal patterns, called resting state networks, display low-frequency characteristics (&amp;lt;0.1 Hz)/nobserved typically in the BOLD-fMRI signal of human subjects. We aim here to understand the origins of resting state activity through/nmodeling via a global spiking attractor network of the brain. This approach offers a realistic mechanistic model at the level of each single/nbrain area based on spiking neurons and realistic AMPA, NMDA, and GABA synapses. Integrating the biologically realistic diffusion/ntensor imaging/diffusion spectrum imaging-based neuroanatomical connectivity into the brain model, the resultant emerging resting/nstate functional connectivity of the brain network fits quantitatively best the experimentally observed functional connectivity in humans/nwhen the brain network operates at the edge of instability. Under these conditions, the slow fluctuating (&amp;lt;/n0.1 Hz) resting state networks/nemerge as structured noise fluctuations around a stable low firing activity equilibrium state in the presence of latent “ghost” multistable/nattractors. The multistable attractor landscape defines a functionally meaningful dynamic repertoire of the brain network that is inher-/nently present in the neuroanatomical connectivity.</subfield>
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      <subfield code="a">G.D. was supported by the European Union Grant EC005-024, by SAF2010-16085 and the “La Marato”/nFoundation,andbytheCONSOLIDER-INGENIO2010ProgrammeCSD2007-00012.The research reported here in was/nsupported by the Brain Network Recovery Group through the James S. McDonnell Foundation and the FP7-ICT/nBrainScales.</subfield>
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      <subfield code="a">Ongoing cortical activity at rest: criticality, multistability,/nand ghost attractors</subfield>
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