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The brain’s unique take on algorithms

Perspectives for understanding the brain vary across disciplines and this has challenged our ability to describe the brain’s functions. In this comment, we discuss how emerging theoretical computing frameworks that bridge top-down algorithm and bottom-up physics approaches may be ideally suited for...

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Detalles Bibliográficos
Autores principales: Aimone, James B., Parekh, Ojas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432563/
https://www.ncbi.nlm.nih.gov/pubmed/37587103
http://dx.doi.org/10.1038/s41467-023-40535-z
Descripción
Sumario:Perspectives for understanding the brain vary across disciplines and this has challenged our ability to describe the brain’s functions. In this comment, we discuss how emerging theoretical computing frameworks that bridge top-down algorithm and bottom-up physics approaches may be ideally suited for guiding the development of neural computing technologies such as neuromorphic hardware and artificial intelligence. Furthermore, we discuss how this balanced perspective may be necessary to incorporate the neurobiological details that are critical for describing the neural computational disruptions within mental health and neurological disorders.