2021 Special Issue on AI and Brain Science: Perspective Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research

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Neural Networks

Volume 144

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Tom Macpherson a

Anne Churchland b

Terry Sejnowski c d

James DiCarlo e

Yukiyasu Kamitani f g

Hidehiko Takahashi h

Takatoshi Hikida a

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https://doi.org/10.1016/j.neunet.2021.09.018

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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.

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Keywords

Artificial intelligence

Neuroscience

Neural imaging

Visual processing

Working memory

Computational psychiatry

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© 2021 The Author(s). Published by Elsevier Ltd.

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Neural Networks. Volume 144. Author links open overlay panel. Tom Macpherson a. Anne Churchland b. Terry Sejnowski c d. James DiCarlo e. Yukiyasu Kamitani f g. Hidehiko Takahashi h. Takatoshi Hikida a. Show more. Add to Mendeley. Share. Cite. https://doi.org/10.1016/j.neunet.2021.09.018. Get rights and content. Under a Creative Commons. license. 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. Previous article in issue. Next article in issue. Keywords. Artificial intelligence. Neuroscience. Neural imaging. Visual processing. Working memory. Computational psychiatry. Recommended articles. Cited by (0) © 2021 The Author(s). Published by Elsevier Ltd.