A deep learning framework for neuroscience

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Title: A deep learning framework for neuroscience
Authors: Richards, BA
Lillicrap, TP
Beaudoin, P
Bengio, Y
Bogacz, R
Christensen, A
Clopath, C
Costa, RP
De Berker, A
Ganguli, S
Gillon, CJ
Hafner, D
Kepecs, A
Kriegeskorte, N
Latham, P
Lindsay, GW
Naud, R
Pack, CC
Poirazi, P
Roelfsema, P
Sacramento, J
Saxe, A
Scellier, B
Schapiro, A
Senn, W
Greg, W
Yamins, D
Zenke, F
Zylberberg, J
Therien, D
Kording, KP
Item Type: Journal Article
Abstract: Systems neuroscience seeks explanations for how the brain implements a wide variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to design computational systems based on the tasks they will have to solve. In the case of artificial neural networks, the three components specified by design are the objective functions, the learning rules, and architectures. With the growing success of deep learning, which utilizes brain-inspired architectures, these three designed components have increasingly become central to how we model, engineer and optimize complex artificial learning systems. Here we argue that a greater focus on these components would also benefit systems neuroscience. We give examples of how this optimization-based framework can drive theoretical and experimental progress in neuroscience. We contend that this principled perspective on systems neuroscience will help to generate more rapid progress.
Issue Date: 1-Nov-2019
Date of Acceptance: 23-Sep-2019
DOI: 10.1038/s41593-019-0520-2
ISSN: 1097-6256
Publisher: Nature Research
Start Page: 1761
End Page: 1770
Journal / Book Title: Nature Neuroscience
Volume: 22
Issue: 11
Copyright Statement: © 2019 Springer Nature America, Inc.
Sponsor/Funder: Wellcome Trust
Biotechnology and Biological Sciences Research Council (BBSRC)
Biotechnology and Biological Sciences Research Cou
Simons Foundation
National Institutes of Health
Funder's Grant Number: 200790/Z/16/Z
ORCA 64155 (BB/N013956/1)
Award ID:564408
Keywords: 1109 Neurosciences
1702 Cognitive Sciences
1701 Psychology
Neurology & Neurosurgery
Publication Status: Published
Embargo Date: 2020-05-30
Online Publication Date: 2019-10-28
Appears in Collections:Faculty of Engineering

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