Good-enough brain model: Challenges, algorithms and discoveries in multi-subject experiments

Evangelos E. Papalexakis; Alona Fyshe; Nicholas D. Sidiropoulos; Partha Pratim Talukdar; Tom M. Mitchell; Christos Faloutsos

doi:10.1145/2623330.2623639

Good-enough brain model: Challenges, algorithms and discoveries in multi-subject experiments

Evangelos E. Papalexakis, Alona Fyshe, Nicholas D. Sidiropoulos, Partha Pratim Talukdar, Tom M. Mitchell, Christos Faloutsos

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

Given a simple noun such as apple, and a question such as "is it edible?", what processes take place in the human brain? More specifically, given the stimulus, what are the interactions between (groups of) neurons (also known as functional connectivity) and how can we automatically infer those interactions, given measurements of the brain activity? Furthermore, how does this connectivity differ across different human subjects? In this work we present a simple, novel good-enough brain model, or GeBM in short, and a novel algorithm Sparse-SysId, which are able to effectively model the dynamics of the neuron interactions and infer the functional connectivity. Moreover, GeBM is able to simulate basic psychological phenomena such as habituation and priming (whose definition we provide in the main text). We evaluate GeBM by using both synthetic and real brain data. Using the real data, GeBM produces brain activity patterns that are strikingly similar to the real ones, and the inferred functional connectivity is able to provide neuroscientific insights towards a better understanding of the way that neurons interact with each other, as well as detect regularities and outliers in multi-subject brain activity measurements.

Original language	English (US)
Title of host publication	KDD 2014 - Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Publisher	Association for Computing Machinery
Pages	95-104
Number of pages	10
ISBN (Print)	9781450329569
DOIs	https://doi.org/10.1145/2623330.2623639
State	Published - 2014
Event	20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2014 - New York, NY, United States Duration: Aug 24 2014 → Aug 27 2014

Publication series

Name	Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Other

Other	20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2014
Country	United States
City	New York, NY
Period	8/24/14 → 8/27/14

Keywords

brain activity analysis
brain functional connectivity
control theory
neuroscience
system identification

Access

10.1145/2623330.2623639

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Papalexakis, E. E., Fyshe, A., Sidiropoulos, N. D., Talukdar, P. P., Mitchell, T. M., & Faloutsos, C. (2014). Good-enough brain model: Challenges, algorithms and discoveries in multi-subject experiments. In KDD 2014 - Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 95-104). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). Association for Computing Machinery. https://doi.org/10.1145/2623330.2623639

Good-enough brain model : Challenges, algorithms and discoveries in multi-subject experiments. / Papalexakis, Evangelos E.; Fyshe, Alona; Sidiropoulos, Nicholas D.; Talukdar, Partha Pratim; Mitchell, Tom M.; Faloutsos, Christos.

KDD 2014 - Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, 2014. p. 95-104 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Papalexakis, EE, Fyshe, A, Sidiropoulos, ND, Talukdar, PP, Mitchell, TM & Faloutsos, C 2014, Good-enough brain model: Challenges, algorithms and discoveries in multi-subject experiments. in KDD 2014 - Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Association for Computing Machinery, pp. 95-104, 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2014, New York, NY, United States, 8/24/14. https://doi.org/10.1145/2623330.2623639

Papalexakis EE, Fyshe A, Sidiropoulos ND, Talukdar PP, Mitchell TM, Faloutsos C. Good-enough brain model: Challenges, algorithms and discoveries in multi-subject experiments. In KDD 2014 - Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery. 2014. p. 95-104. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). https://doi.org/10.1145/2623330.2623639

Papalexakis, Evangelos E. ; Fyshe, Alona ; Sidiropoulos, Nicholas D. ; Talukdar, Partha Pratim ; Mitchell, Tom M. ; Faloutsos, Christos. / Good-enough brain model : Challenges, algorithms and discoveries in multi-subject experiments. KDD 2014 - Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, 2014. pp. 95-104 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

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