A Bio-realistic Synthetic Hippocampus for Robotic Cognition
Vallverdú, Jordi 1973- (Universitat Autònoma de Barcelona)
Feinstein, Xenia (National Institute of Mental Health)
Robertson, Paul (Dynamic Object Language Labs)
Kipelkin, Ivan (B-Rain Ark FZ-LLC)
Talanov, Max (University of Messina)

Date:	2025
Abstract:	Current robotic systems struggle with adaptive generalisation beyond curated training domains. Inspired by hippocampal dynamics in biological cognition, we introduce a synthetic memory architecture that segregates online sensorimotor interaction from offline consolidation and generative replay. Implemented via spiking neural networks and neuromorphic substrates, our framework enables bidirectional memory traversal, goal-prioritised plasticity updates, and energy-efficient policy synthesis. This dual-state system bridges real-time control with autonomous learning, advancing a biologically grounded pathway toward resilient, context-adaptive robotic intelligence.
Grants:	Ministerio de Ciencia, Innovación y Universidades PID2023-148336NB-100
Note:	Altres ajuts: acords transformatius de la UAB
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Sleep ; Hippocampus ; Robotic ; Spiking neural networks ; Memristive device
Published in:	BioNanoScience, Vol. 15, Issue 4 (October 2025) , art. 591, ISSN 2191-1649

DOI: 10.1007/s12668-025-02229-2

14 p, 2.1 MB

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