A computational approach to a neuromorphic sequential memory bio-inspired on the Hippocampus and Entorhinal Cortex formation

Part of the book series: Springer Proceedings in Materials ((SPM,volume 50)) Included in the following conference series: X Workshop in R&D+i & International Workshop on STEM of EPS

Detalles Bibliográficos
Autores: Casanueva Morato, Daniel, Ayuso Martínez, Álvaro, Pérez-Peña, Antonio Manuel, Domínguez Morales, Juan Pedro, Jiménez Moreno, Gabriel
Tipo de recurso: capítulo de libro
Estado:Versión aceptada para publicación
Fecha de publicación:2024
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/164022
Acceso en línea:https://hdl.handle.net/11441/164022
https://doi.org/10.1007/978-3-031-64106-0_41
Access Level:acceso abierto
Palabra clave:Hippocampus model
Sequential memory
Spiking Neural Networks
Neuromorphic engineering
SpiNNaker
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spelling A computational approach to a neuromorphic sequential memory bio-inspired on the Hippocampus and Entorhinal Cortex formationCasanueva Morato, DanielAyuso Martínez, ÁlvaroPérez-Peña, Antonio ManuelDomínguez Morales, Juan PedroJiménez Moreno, GabrielHippocampus modelSequential memorySpiking Neural NetworksNeuromorphic engineeringSpiNNakerPart of the book series: Springer Proceedings in Materials ((SPM,volume 50)) Included in the following conference series: X Workshop in R&D+i & International Workshop on STEM of EPSThe brain is considered one of the most powerful and efficient machines in existence. This is why neuromorphic engineering is trying to mimic biology to develop new systems that incorporate these superior capabilities. Within this field, bio-inspired learning and memory systems are still a challenge to be solved, and this is where the hippocampus and entorhinal cortex is involved. This brain formation acts as a short-term memory capable of learning by self-association of memories from different sources of information. In this work, we propose a fully functional bio-inspired spike-based hippocampus and entorhinal cortex sequential memory system capable of learning memories, recalling individual and sequential memories from a single fragment, and forgetting them. This model has been implemented on SpiNNaker using Spiking Neural Networks, and a set of experiments were performed to demonstrate its correct operation. This model will pave the road for the development of future more complex neuromorphic systems with a large amount of applicability.SpringerArquitectura y Tecnología de ComputadoresTEP108: Robótica y Tecnología de ComputadoresMinisterio de Ciencia e Innovación (MICIN). España2024info:eu-repo/semantics/bookPartinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/164022https://doi.org/10.1007/978-3-031-64106-0_41reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésRecent Advances and Emerging Challenges in STEMTED2021-130825B-I00PID2019-105556GB-C33https://link.springer.com/chapter/10.1007/978-3-031-64106-0_41Cham, Suizainfo:eu-repo/semantics/openAccessoai:idus.us.es:11441/1640222026-06-17T12:51:07Z
dc.title.none.fl_str_mv A computational approach to a neuromorphic sequential memory bio-inspired on the Hippocampus and Entorhinal Cortex formation
title A computational approach to a neuromorphic sequential memory bio-inspired on the Hippocampus and Entorhinal Cortex formation
spellingShingle A computational approach to a neuromorphic sequential memory bio-inspired on the Hippocampus and Entorhinal Cortex formation
Casanueva Morato, Daniel
Hippocampus model
Sequential memory
Spiking Neural Networks
Neuromorphic engineering
SpiNNaker
title_short A computational approach to a neuromorphic sequential memory bio-inspired on the Hippocampus and Entorhinal Cortex formation
title_full A computational approach to a neuromorphic sequential memory bio-inspired on the Hippocampus and Entorhinal Cortex formation
title_fullStr A computational approach to a neuromorphic sequential memory bio-inspired on the Hippocampus and Entorhinal Cortex formation
title_full_unstemmed A computational approach to a neuromorphic sequential memory bio-inspired on the Hippocampus and Entorhinal Cortex formation
title_sort A computational approach to a neuromorphic sequential memory bio-inspired on the Hippocampus and Entorhinal Cortex formation
dc.creator.none.fl_str_mv Casanueva Morato, Daniel
Ayuso Martínez, Álvaro
Pérez-Peña, Antonio Manuel
Domínguez Morales, Juan Pedro
Jiménez Moreno, Gabriel
author Casanueva Morato, Daniel
author_facet Casanueva Morato, Daniel
Ayuso Martínez, Álvaro
Pérez-Peña, Antonio Manuel
Domínguez Morales, Juan Pedro
Jiménez Moreno, Gabriel
author_role author
author2 Ayuso Martínez, Álvaro
Pérez-Peña, Antonio Manuel
Domínguez Morales, Juan Pedro
Jiménez Moreno, Gabriel
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Arquitectura y Tecnología de Computadores
TEP108: Robótica y Tecnología de Computadores
Ministerio de Ciencia e Innovación (MICIN). España
dc.subject.none.fl_str_mv Hippocampus model
Sequential memory
Spiking Neural Networks
Neuromorphic engineering
SpiNNaker
topic Hippocampus model
Sequential memory
Spiking Neural Networks
Neuromorphic engineering
SpiNNaker
description Part of the book series: Springer Proceedings in Materials ((SPM,volume 50)) Included in the following conference series: X Workshop in R&D+i & International Workshop on STEM of EPS
publishDate 2024
dc.date.none.fl_str_mv 2024
dc.type.none.fl_str_mv info:eu-repo/semantics/bookPart
info:eu-repo/semantics/acceptedVersion
format bookPart
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/164022
https://doi.org/10.1007/978-3-031-64106-0_41
url https://hdl.handle.net/11441/164022
https://doi.org/10.1007/978-3-031-64106-0_41
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Recent Advances and Emerging Challenges in STEM
TED2021-130825B-I00
PID2019-105556GB-C33
https://link.springer.com/chapter/10.1007/978-3-031-64106-0_41
Cham, Suiza
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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