Causal localization of neural function: The Shapley value method

Alon Keinan*, Claus C. Hilgetag, Isaac Meilijson, Eytan Ruppin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

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".

Original languageEnglish
Pages (from-to)215-222
Number of pages8
JournalNeurocomputing
Volume58-60
DOIs
StatePublished - Jun 2004

Funding

FundersFunder number
Israel Academy of Sciences and Humanities
Israel Science Foundation
Tel Aviv University

    Keywords

    • Contributions analysis
    • Interactions
    • Localization of function
    • Multi-lesions
    • Multi-perturbations
    • Shapley value

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