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Fair attribution of functional contribution in artificial and biological networks

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Fair attribution of functional contribution in artificial and biological networks. / Keinan, Alon; Sandbank, Ben; Hilgetag, Claus C; Meilijson, Isaac; Ruppin, Eytan.

in: NEURAL COMPUT, Jahrgang 16, Nr. 9, 09.2004, S. 1887-915.

Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung

Harvard

Keinan, A, Sandbank, B, Hilgetag, CC, Meilijson, I & Ruppin, E 2004, 'Fair attribution of functional contribution in artificial and biological networks', NEURAL COMPUT, Jg. 16, Nr. 9, S. 1887-915. https://doi.org/10.1162/0899766041336387

APA

Keinan, A., Sandbank, B., Hilgetag, C. C., Meilijson, I., & Ruppin, E. (2004). Fair attribution of functional contribution in artificial and biological networks. NEURAL COMPUT, 16(9), 1887-915. https://doi.org/10.1162/0899766041336387

Vancouver

Keinan A, Sandbank B, Hilgetag CC, Meilijson I, Ruppin E. Fair attribution of functional contribution in artificial and biological networks. NEURAL COMPUT. 2004 Sep;16(9):1887-915. https://doi.org/10.1162/0899766041336387

Bibtex

@article{3ace8a10bf7c465b816be3dbb94c5891,
title = "Fair attribution of functional contribution in artificial and biological networks",
abstract = "This letter presents the multi-perturbation Shapley value analysis (MSA), an axiomatic, scalable, and rigorous method for deducing causal function localization from multiple perturbations data. The MSA, based on fundamental concepts from game theory, accurately quantifies the contributions of network elements and their interactions, overcoming several shortcomings of previous function localization approaches. Its successful operation is demonstrated in both the analysis of a neurophysiological model and of reversible deactivation data. The MSA has a wide range of potential applications, including the analysis of reversible deactivation experiments, neuronal laser ablations, and transcranial magnetic stimulation {"}virtual lesions,{"} as well as in providing insight into the inner workings of computational models of neurophysiological systems.",
keywords = "Algorithms, Animals, Cluster Analysis, Computer Simulation, Functional Laterality, Humans, Lampreys, Models, Neurological, Neural Networks (Computer), Neural Pathways, Neurons, Social Perception, Comparative Study, Journal Article, Research Support, Non-U.S. Gov't",
author = "Alon Keinan and Ben Sandbank and Hilgetag, {Claus C} and Isaac Meilijson and Eytan Ruppin",
year = "2004",
month = sep,
doi = "10.1162/0899766041336387",
language = "English",
volume = "16",
pages = "1887--915",
journal = "NEURAL COMPUT",
issn = "0899-7667",
publisher = "MIT Press",
number = "9",

}

RIS

TY - JOUR

T1 - Fair attribution of functional contribution in artificial and biological networks

AU - Keinan, Alon

AU - Sandbank, Ben

AU - Hilgetag, Claus C

AU - Meilijson, Isaac

AU - Ruppin, Eytan

PY - 2004/9

Y1 - 2004/9

N2 - This letter presents the multi-perturbation Shapley value analysis (MSA), an axiomatic, scalable, and rigorous method for deducing causal function localization from multiple perturbations data. The MSA, based on fundamental concepts from game theory, accurately quantifies the contributions of network elements and their interactions, overcoming several shortcomings of previous function localization approaches. Its successful operation is demonstrated in both the analysis of a neurophysiological model and of reversible deactivation data. The MSA has a wide range of potential applications, including the analysis of reversible deactivation experiments, neuronal laser ablations, and transcranial magnetic stimulation "virtual lesions," as well as in providing insight into the inner workings of computational models of neurophysiological systems.

AB - This letter presents the multi-perturbation Shapley value analysis (MSA), an axiomatic, scalable, and rigorous method for deducing causal function localization from multiple perturbations data. The MSA, based on fundamental concepts from game theory, accurately quantifies the contributions of network elements and their interactions, overcoming several shortcomings of previous function localization approaches. Its successful operation is demonstrated in both the analysis of a neurophysiological model and of reversible deactivation data. The MSA has a wide range of potential applications, including the analysis of reversible deactivation experiments, neuronal laser ablations, and transcranial magnetic stimulation "virtual lesions," as well as in providing insight into the inner workings of computational models of neurophysiological systems.

KW - Algorithms

KW - Animals

KW - Cluster Analysis

KW - Computer Simulation

KW - Functional Laterality

KW - Humans

KW - Lampreys

KW - Models, Neurological

KW - Neural Networks (Computer)

KW - Neural Pathways

KW - Neurons

KW - Social Perception

KW - Comparative Study

KW - Journal Article

KW - Research Support, Non-U.S. Gov't

U2 - 10.1162/0899766041336387

DO - 10.1162/0899766041336387

M3 - SCORING: Journal article

C2 - 15265327

VL - 16

SP - 1887

EP - 1915

JO - NEURAL COMPUT

JF - NEURAL COMPUT

SN - 0899-7667

IS - 9

ER -