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000285807 0247_ $$2doi$$a10.1109/EMBC58623.2025.11254218
000285807 0247_ $$2pmid$$apmid:41336996
000285807 037__ $$aDZNE-2026-00343
000285807 041__ $$aEnglish
000285807 1001_ $$0P:(DE-2719)2814182$$aHu, Xin$$b0$$eFirst author$$udzne
000285807 1112_ $$a47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society$$cCopenhagen$$d2025-07-14 - 2025-07-18$$gEMBC$$wDenmark
000285807 245__ $$aA Computational Framework for Learning and Memory: Network Motif Evolution During LTP-Induced Plasticity.
000285807 260__ $$bIEEE$$c2025
000285807 29510 $$a2025 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
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000285807 3367_ $$0PUB:(DE-HGF)8$$2PUB:(DE-HGF)$$aContribution to a conference proceedings$$bcontrib$$mcontrib$$s1775045149_19741
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000285807 500__ $$aMissing Journal: Annu Int Conf IEEE Eng Med Biol Soc = 2375-7477 (import from CrossRef Conference, PubMed, , Journals: pub.dzne.de)
000285807 520__ $$aUnraveling 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.
000285807 536__ $$0G:(DE-HGF)POF4-351$$a351 - Brain Function (POF4-351)$$cPOF4-351$$fPOF IV$$x0
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000285807 650_2 $$2MeSH$$aLong-Term Potentiation: physiology
000285807 650_2 $$2MeSH$$aAnimals
000285807 650_2 $$2MeSH$$aMemory: physiology
000285807 650_2 $$2MeSH$$aNeuronal Plasticity: physiology
000285807 650_2 $$2MeSH$$aLearning: physiology
000285807 650_2 $$2MeSH$$aModels, Neurological
000285807 650_2 $$2MeSH$$aRats
000285807 650_2 $$2MeSH$$aNerve Net: physiology
000285807 7001_ $$0P:(DE-2719)9001867$$aKhanzada, Shahrukh$$b1$$udzne
000285807 7001_ $$0P:(DE-2719)9001361$$aEmery, Brett Addison$$b2$$udzne
000285807 7001_ $$0P:(DE-2719)2812628$$aAmin, Hayder$$b3$$eLast author$$udzne
000285807 773__ $$a10.1109/EMBC58623.2025.11254218
000285807 8564_ $$uhttps://pub.dzne.de/record/285807/files/DZNE-2026-00343_Restricted.pdf
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000285807 9101_ $$0I:(DE-588)1065079516$$6P:(DE-2719)2814182$$aDeutsches Zentrum für Neurodegenerative Erkrankungen$$b0$$kDZNE
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000285807 9101_ $$0I:(DE-588)1065079516$$6P:(DE-2719)2812628$$aDeutsches Zentrum für Neurodegenerative Erkrankungen$$b3$$kDZNE
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000285807 9201_ $$0I:(DE-2719)1710010$$kAG Amin$$lBiohybrid Neuroelectronics (BIONICS)$$x0
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