Direct Fit to Nature: An Evolutionary Perspective on Biological and Artificial Neural Networks

Uri Hasson; Samuel A. Nastase; Ariel Goldstein

doi:10.1016/j.neuron.2019.12.002

Direct Fit to Nature: An Evolutionary Perspective on Biological and Artificial Neural Networks

Uri Hasson^*
, Samuel A. Nastase
, Ariel Goldstein

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

282 Scopus citations

Abstract

To guide adaptive behavior and support predictions in real-life contexts, the brain may rely on opaque, over-parameterized models capable of directly fitting to the multidimensional world, while being blind—like evolution—to the underlying rules and causes.

Original language	English
Pages (from-to)	416-434
Number of pages	19
Journal	Neuron
Volume	105
Issue number	3
DOIs	https://doi.org/10.1016/j.neuron.2019.12.002
State	Published - 5 Feb 2020
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2019 Elsevier Inc.

Keywords

evolution
experimental design
interpolation
learning
neural networks

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10.1016/j.neuron.2019.12.002

Cite this

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title = "Direct Fit to Nature: An Evolutionary Perspective on Biological and Artificial Neural Networks",

abstract = "To guide adaptive behavior and support predictions in real-life contexts, the brain may rely on opaque, over-parameterized models capable of directly fitting to the multidimensional world, while being blind—like evolution—to the underlying rules and causes.",

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year = "2020",

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doi = "10.1016/j.neuron.2019.12.002",

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AU - Goldstein, Ariel

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AB - To guide adaptive behavior and support predictions in real-life contexts, the brain may rely on opaque, over-parameterized models capable of directly fitting to the multidimensional world, while being blind—like evolution—to the underlying rules and causes.

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KW - experimental design

KW - interpolation

KW - learning

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Direct Fit to Nature: An Evolutionary Perspective on Biological and Artificial Neural Networks

Abstract

Bibliographical note

Keywords

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