Photorefraction Simulates Well the Plasticity of Neural Synaptic Connections.

all-optical systems artificial intelligence learning neural networks neuromorphic systems neuroplasticity photonic hardware photorefractive solitons

Journal

Biomimetics (Basel, Switzerland)
ISSN: 2313-7673
Titre abrégé: Biomimetics (Basel)
Pays: Switzerland
ID NLM: 101719189

Informations de publication

Date de publication:
13 Apr 2024
Historique:
received: 06 03 2024
revised: 09 04 2024
accepted: 11 04 2024
medline: 26 4 2024
pubmed: 26 4 2024
entrez: 26 4 2024
Statut: epublish

Résumé

In recent years, the need for systems capable of achieving the dynamic learning and information storage efficiency of the biological brain has led to the emergence of neuromorphic research. In particular, neuromorphic optics was born with the idea of reproducing the functional and structural properties of the biological brain. In this context, solitonic neuromorphic research has demonstrated the ability to reproduce dynamic and plastic structures capable of learning and storing through conformational changes in the network. In this paper, we demonstrate that solitonic neural networks are capable of mimicking the functional behaviour of biological neural tissue, in terms of synaptic formation procedures and dynamic reinforcement.

Identifiants

pubmed: 38667243
pii: biomimetics9040231
doi: 10.3390/biomimetics9040231
pii:
doi:

Types de publication

Journal Article

Langues

eng

Auteurs

Alessandro Bile (A)

Department of Fundamental and Applied Sciences for Engineering, Sapienza Università di Roma, Via Scarpa 16, 00161 Roma, Italy.

Hamed Tari (H)

Department of Fundamental and Applied Sciences for Engineering, Sapienza Università di Roma, Via Scarpa 16, 00161 Roma, Italy.

Riccardo Pepino (R)

Department of Fundamental and Applied Sciences for Engineering, Sapienza Università di Roma, Via Scarpa 16, 00161 Roma, Italy.

Arif Nabizada (A)

Department of Fundamental and Applied Sciences for Engineering, Sapienza Università di Roma, Via Scarpa 16, 00161 Roma, Italy.

Eugenio Fazio (E)

Department of Fundamental and Applied Sciences for Engineering, Sapienza Università di Roma, Via Scarpa 16, 00161 Roma, Italy.

Classifications MeSH