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Neurorobots as a Means Toward Neuroethology and Explainable AI

Understanding why deep neural networks and machine learning algorithms act as they do is a difficult endeavor. Neuroscientists are faced with similar problems. One way biologists address this issue is by closely observing behavior while recording neurons or manipulating brain circuits. This has been...

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Autores principales: Chen, Kexin, Hwu, Tiffany, Kashyap, Hirak J., Krichmar, Jeffrey L., Stewart, Kenneth, Xing, Jinwei, Zou, Xinyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7604467/
https://www.ncbi.nlm.nih.gov/pubmed/33192435
http://dx.doi.org/10.3389/fnbot.2020.570308
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author Chen, Kexin
Hwu, Tiffany
Kashyap, Hirak J.
Krichmar, Jeffrey L.
Stewart, Kenneth
Xing, Jinwei
Zou, Xinyun
author_facet Chen, Kexin
Hwu, Tiffany
Kashyap, Hirak J.
Krichmar, Jeffrey L.
Stewart, Kenneth
Xing, Jinwei
Zou, Xinyun
author_sort Chen, Kexin
collection PubMed
description Understanding why deep neural networks and machine learning algorithms act as they do is a difficult endeavor. Neuroscientists are faced with similar problems. One way biologists address this issue is by closely observing behavior while recording neurons or manipulating brain circuits. This has been called neuroethology. In a similar way, neurorobotics can be used to explain how neural network activity leads to behavior. In real world settings, neurorobots have been shown to perform behaviors analogous to animals. Moreover, a neuroroboticist has total control over the network, and by analyzing different neural groups or studying the effect of network perturbations (e.g., simulated lesions), they may be able to explain how the robot's behavior arises from artificial brain activity. In this paper, we review neurorobot experiments by focusing on how the robot's behavior leads to a qualitative and quantitative explanation of neural activity, and vice versa, that is, how neural activity leads to behavior. We suggest that using neurorobots as a form of computational neuroethology can be a powerful methodology for understanding neuroscience, as well as for artificial intelligence and machine learning.
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spelling pubmed-76044672020-11-13 Neurorobots as a Means Toward Neuroethology and Explainable AI Chen, Kexin Hwu, Tiffany Kashyap, Hirak J. Krichmar, Jeffrey L. Stewart, Kenneth Xing, Jinwei Zou, Xinyun Front Neurorobot Neuroscience Understanding why deep neural networks and machine learning algorithms act as they do is a difficult endeavor. Neuroscientists are faced with similar problems. One way biologists address this issue is by closely observing behavior while recording neurons or manipulating brain circuits. This has been called neuroethology. In a similar way, neurorobotics can be used to explain how neural network activity leads to behavior. In real world settings, neurorobots have been shown to perform behaviors analogous to animals. Moreover, a neuroroboticist has total control over the network, and by analyzing different neural groups or studying the effect of network perturbations (e.g., simulated lesions), they may be able to explain how the robot's behavior arises from artificial brain activity. In this paper, we review neurorobot experiments by focusing on how the robot's behavior leads to a qualitative and quantitative explanation of neural activity, and vice versa, that is, how neural activity leads to behavior. We suggest that using neurorobots as a form of computational neuroethology can be a powerful methodology for understanding neuroscience, as well as for artificial intelligence and machine learning. Frontiers Media S.A. 2020-10-19 /pmc/articles/PMC7604467/ /pubmed/33192435 http://dx.doi.org/10.3389/fnbot.2020.570308 Text en Copyright © 2020 Chen, Hwu, Kashyap, Krichmar, Stewart, Xing and Zou. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Chen, Kexin
Hwu, Tiffany
Kashyap, Hirak J.
Krichmar, Jeffrey L.
Stewart, Kenneth
Xing, Jinwei
Zou, Xinyun
Neurorobots as a Means Toward Neuroethology and Explainable AI
title Neurorobots as a Means Toward Neuroethology and Explainable AI
title_full Neurorobots as a Means Toward Neuroethology and Explainable AI
title_fullStr Neurorobots as a Means Toward Neuroethology and Explainable AI
title_full_unstemmed Neurorobots as a Means Toward Neuroethology and Explainable AI
title_short Neurorobots as a Means Toward Neuroethology and Explainable AI
title_sort neurorobots as a means toward neuroethology and explainable ai
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7604467/
https://www.ncbi.nlm.nih.gov/pubmed/33192435
http://dx.doi.org/10.3389/fnbot.2020.570308
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