Desiderata for Normative Models of Synaptic Plasticity.
Neural Comput
; 36(7): 1245-1285, 2024 Jun 07.
Article
em En
| MEDLINE
| ID: mdl-38776950
ABSTRACT
Normative models of synaptic plasticity use computational rationales to arrive at predictions of behavioral and network-level adaptive phenomena. In recent years, there has been an explosion of theoretical work in this realm, but experimental confirmation remains limited. In this review, we organize work on normative plasticity models in terms of a set of desiderata that, when satisfied, are designed to ensure that a given model demonstrates a clear link between plasticity and adaptive behavior, is consistent with known biological evidence about neural plasticity and yields specific testable predictions. As a prototype, we include a detailed analysis of the REINFORCE algorithm. We also discuss how new models have begun to improve on the identified criteria and suggest avenues for further development. Overall, we provide a conceptual guide to help develop neural learning theories that are precise, powerful, and experimentally testable.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Modelos Neurológicos
/
Plasticidade Neuronal
Limite:
Animals
/
Humans
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article