Causal localization of neural function: the Shapley value method
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Causal localization of neural function: the Shapley value method. / Keinan, Alon; Hilgetag, Claus C.; Meilijson, Isaac; Ruppin, Eytan.
in: NEUROCOMPUTING, Jahrgang 58-60, 01.06.2004, S. 215-222.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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TY - JOUR
T1 - Causal localization of neural function: the Shapley value method
AU - Keinan, Alon
AU - Hilgetag, Claus C.
AU - Meilijson, Isaac
AU - Ruppin, Eytan
PY - 2004/6/1
Y1 - 2004/6/1
N2 - Identifying the functional roles of elements of a neural network is one of the fundamental challenges in understanding neural information processing. Aiming at this goal, lesion studies have been used extensively in neuroscience. Most of these employ single lesions and hence, limited ability in revealing the significance of interacting elements. This paper presents the multi-perturbation Shapley value analysis (MSA), an axiomatic, scalable and rigorous method, addressing the challenge of determining the contributions of network elements from a data set of multi-lesions or other perturbations. The successful workings of the MSA are demonstrated on artificial and biological data. MSA is a novel method for causal function localization, with a wide range of potential applications for the analysis of reversible deactivation experiments and TMS-induced “virtual lesions”.
AB - Identifying the functional roles of elements of a neural network is one of the fundamental challenges in understanding neural information processing. Aiming at this goal, lesion studies have been used extensively in neuroscience. Most of these employ single lesions and hence, limited ability in revealing the significance of interacting elements. This paper presents the multi-perturbation Shapley value analysis (MSA), an axiomatic, scalable and rigorous method, addressing the challenge of determining the contributions of network elements from a data set of multi-lesions or other perturbations. The successful workings of the MSA are demonstrated on artificial and biological data. MSA is a novel method for causal function localization, with a wide range of potential applications for the analysis of reversible deactivation experiments and TMS-induced “virtual lesions”.
U2 - 10.1016/j.neucom.2004.01.046
DO - 10.1016/j.neucom.2004.01.046
M3 - SCORING: Journal article
VL - 58-60
SP - 215
EP - 222
JO - NEUROCOMPUTING
JF - NEUROCOMPUTING
SN - 0925-2312
ER -