Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research

Macpherson, Tom, Churchland, Anne, Sejnowski, Terry, DiCarlo, James, Kamitani, Yukiyasu, Takahashi, Hidehiko, Hikida, Takatoshi (September 2021) Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research. Neural Networks. ISSN 0893-6080

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DOI: 10.1016/j.neunet.2021.09.018

Abstract

Neuroscience and artificial intelligence (AI) share a long history of collaboration. Advances in neuroscience, alongside huge leaps in computer processing power over the last few decades, have given rise to a new generation of in silico neural networks inspired by the architecture of the brain. These AI systems are now capable of many of the advanced perceptual and cognitive abilities of biological systems, including object recognition and decision making. Moreover, AI is now increasingly being employed as a tool for neuroscience research and is transforming our understanding of brain functions. In particular, deep learning has been used to model how convolutional layers and recurrent connections in the brain’s cerebral cortex control important functions, including visual processing, memory, and motor control. Excitingly, the use of neuroscience-inspired AI also holds great promise for understanding how changes in brain networks result in psychopathologies, and could even be utilized in treatment regimes. Here we discuss recent advancements in four areas in which the relationship between neuroscience and AI has led to major advancements in the field; (1) AI models of working memory, (2) AI visual processing, (3) AI analysis of big neuroscience datasets, and (4) computational psychiatry.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > computational biology > algorithms
bioinformatics > computational biology
organism description > animal behavior > memory
neurobiology
neurobiology > neuroscience
organism description > animal behavior > visual
CSHL Authors:
Communities: CSHL labs > Churchland lab
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: 28 September 2021
Date Deposited: 30 Sep 2021 18:43
Last Modified: 25 Jan 2024 15:15
URI: https://repository.cshl.edu/id/eprint/40378

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