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2024-01-01

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cc-by (c) Bavassi, Luz et al., 2024
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/217924

Segregation-to-Integration Transformation Model of Memory Evolution

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Abstract

The Segregation-to-Integration Transformation (SIT) model provides a framework for memory transformation based on changes in the neural network properties. SIT posits that memories shift from highly modular to less modular network forms over time, driven by neural reactivations, activation spread, and plasticity rules. The SIT model identified a critical period, shortly after memory formation, where reactivations can induce significant structural modifications. As repeated reactivation passes, the network becomes more stable and integrated, becoming more resistant to change, thus preserving the core information while reducing the likelihood of distortion or loss.

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https://doi.org/10.1162/netn_a_00415

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Memòria, Xarxes neuronals (Neurobiologia)

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Memory, Neural networks (Neurobiology)

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Articles publicats en revistes (Cognició, Desenvolupament i Psicologia de l'Educació)
Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))

Citation

BAVASSI, Luz and FUENTEMILLA GARRIGA, Lluís. Segregation-to-Integration Transformation Model of Memory Evolution. Network Neuroscience. 2024. Vol. 8, num. 4, pags. 1529-1544. ISSN 2472-1751. [consulted: 7 of October of 2026]. Available at: https://hdl.handle.net/2445/217924

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