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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd http://dublincore.org/schemas/xmls/qdc/dcterms.xsd"><dc:language>eng</dc:language><dc:creator>Hu, Xin</dc:creator><dc:creator>Khanzada, Shahrukh</dc:creator><dc:creator>Emery, Brett Addison</dc:creator><dc:creator>Amin, Hayder</dc:creator><dc:title>A Computational Framework for Learning and Memory: Network Motif Evolution During LTP-Induced Plasticity.</dc:title><dc:subject>Long-Term Potentiation: physiology</dc:subject><dc:subject>Animals</dc:subject><dc:subject>Memory: physiology</dc:subject><dc:subject>Neuronal Plasticity: physiology</dc:subject><dc:subject>Learning: physiology</dc:subject><dc:subject>Models, Neurological</dc:subject><dc:subject>Rats</dc:subject><dc:subject>Nerve Net: physiology</dc:subject><dc:description>Unraveling the complexity of network-level synaptic plasticity remains a challenge due to the dynamic and interconnected nature of neural circuits. In this study, we employ network motifs-recurrent, functionally specialized patterns of connectivity-as a framework to dissect long-term potentiation (LTP)-induced reorganization in hippocampal CA1-CA3 networks. Using network LTP recordings from highdensity microelectrode arrays (HD-MEA), we systematically tracked motif evolution before and after high-frequency stimulation, assessing their roles in network stability, synaptic strength modulation, and criticality-redundancy trade-offs, linking these dynamics to firing synchrony and network potentiation. The Graph-theoretic analysis further demonstrated that LTP-induced reorganization follows a structured motif-guided trajectory, with early-phase motif recruitment optimizing efficiency, followed by phase-dependent refinement. These findings provide new insights into how structured connectivity enables network-level plasticity, balancing efficiency with stability, and offer a potential framework for understanding memory encoding mechanisms and their dysfunction in neurological disorders.</dc:description><dc:source>IEEE 1-4 (2025). doi:10.1109/EMBC58623.2025.11254218</dc:source><dc:type>info:eu-repo/semantics/conferenceObject</dc:type><dc:type>info:eu-repo/semantics/publishedVersion</dc:type><dc:source>2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) : [Proceedings] - IEEE, 2025. - ISBN 979-8-3315-8618-8 - doi:10.1109/EMBC58623.2025.11254218</dc:source><dc:source>2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) : [Proceedings] - IEEE, 2025. - ISBN 979-8-3315-8618-8 - doi:10.1109/EMBC58623.2025.11254218&lt;br/&gt;47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, Copenhagen, Denmark, 2025-07-14 - 2025-07-18</dc:source><dc:publisher>IEEE</dc:publisher><dc:date>2025</dc:date><dc:rights>info:eu-repo/semantics/closedAccess</dc:rights><dc:coverage>DE</dc:coverage><dc:identifier>https://pub.dzne.de/record/285807</dc:identifier><dc:identifier>https://pub.dzne.de/search?p=id:%22DZNE-2026-00343%22</dc:identifier><dc:audience>Researchers</dc:audience><dc:relation>info:eu-repo/semantics/altIdentifier/doi/10.1109/EMBC58623.2025.11254218</dc:relation><dc:relation>info:eu-repo/semantics/altIdentifier/pmid/pmid:41336996</dc:relation></oai_dc:dc>

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