Recent Advances at the Interface of Neuroscience and Artificial Neural Networks.
J Neurosci
; 42(45): 8514-8523, 2022 11 09.
Article
em En
| MEDLINE
| ID: mdl-36351830
ABSTRACT
Biological neural networks adapt and learn in diverse behavioral contexts. Artificial neural networks (ANNs) have exploited biological properties to solve complex problems. However, despite their effectiveness for specific tasks, ANNs are yet to realize the flexibility and adaptability of biological cognition. This review highlights recent advances in computational and experimental research to advance our understanding of biological and artificial intelligence. In particular, we discuss critical mechanisms from the cellular, systems, and cognitive neuroscience fields that have contributed to refining the architecture and training algorithms of ANNs. Additionally, we discuss how recent work used ANNs to understand complex neuronal correlates of cognition and to process high throughput behavioral data.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neurociências
/
Inteligência Artificial
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article