Contemporary neurocognitive models of memory: A descriptive comparative analysis.
Evolution
Homeostasis
Memory systems
Neural networks
Predictive coding
Journal
Neuropsychologia
ISSN: 1873-3514
Titre abrégé: Neuropsychologia
Pays: England
ID NLM: 0020713
Informations de publication
Date de publication:
29 Feb 2024
29 Feb 2024
Historique:
received:
03
11
2023
revised:
27
02
2024
accepted:
27
02
2024
medline:
3
3
2024
pubmed:
3
3
2024
entrez:
2
3
2024
Statut:
aheadofprint
Résumé
The great complexity involved in the study of memory has given rise to numerous hypotheses and models associated with various phenomena at different levels of analysis. This has allowed us to delve deeper in our knowledge about memory but has also made it difficult to synthesize and integrate data from different lines of research. In this context, this work presents a descriptive comparative analysis of contemporary models that address the structure and function of multiple memory systems. The main goal is to outline a panoramic view of the key elements that constitute these models in order to visualize both the current state of research and possible future directions. The elements that stand out from different levels of analysis are distributed neural networks, hierarchical organization, predictive coding, homeostasis, and evolutionary perspective.
Identifiants
pubmed: 38430963
pii: S0028-3932(24)00061-7
doi: 10.1016/j.neuropsychologia.2024.108846
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
108846Informations de copyright
Copyright © 2024. Published by Elsevier Ltd.
Déclaration de conflit d'intérêts
Declaration of competing interest The author declare that she has no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.