Multi-kernel change detection for dynamic functional connectivity graphs

Georgios Vasileios Karanikolas; Olaf Sporns; Georgios B Giannakis

doi:10.1109/ACSSC.2017.8335618

Multi-kernel change detection for dynamic functional connectivity graphs

Georgios Vasileios Karanikolas, Olaf Sporns, Georgios B Giannakis

Electrical and Computer Engineering

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

5 Scopus citations

Abstract

Dynamic functional connectivity (dFC) analyses of fMRI time-courses are typically performed using sliding-window based schemes. Such approaches not only inherently confine analysis to a single time-scale, but also do not generally lend themselves to accurate change-time estimates of the dynamically evolving graph topology. Change point detection methods on the other hand, offer the potential to overcome both limitations. However, the approaches employed so far in the dFC context are limited to detecting changes in linear relationships among time-courses corresponding to distinct regions of the brain. The present work puts forth a novel multi-kernel change point detection approach with the goal of capturing changes in the generally nonlinear relationships among time-courses, and thus in the topologies of the corresponding dynamically evolving FC graphs. The approach is tested on dynamic causal model (DCM) based synthetic resting-state fMRI data.

Original language	English (US)
Title of host publication	Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
Editors	Michael B. Matthews
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1555-1559
Number of pages	5
ISBN (Electronic)	9781538618233
DOIs	https://doi.org/10.1109/ACSSC.2017.8335618
State	Published - Jul 2 2017
Event	51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017 - Pacific Grove, United States Duration: Oct 29 2017 → Nov 1 2017

Publication series

Name	Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
Volume	2017-October

Other

Other	51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
Country/Territory	United States
City	Pacific Grove
Period	10/29/17 → 11/1/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

change detection
fMRI
kernel-based regression
multiple kernel learning

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10.1109/ACSSC.2017.8335618

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Karanikolas, G. V., Sporns, O., & Giannakis, G. B. (2017). Multi-kernel change detection for dynamic functional connectivity graphs. In M. B. Matthews (Ed.), Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017 (pp. 1555-1559). (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017; Vol. 2017-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACSSC.2017.8335618

Multi-kernel change detection for dynamic functional connectivity graphs. / Karanikolas, Georgios Vasileios; Sporns, Olaf; Giannakis, Georgios B.
Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. ed. / Michael B. Matthews. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1555-1559 (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017; Vol. 2017-October).

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

Karanikolas, GV, Sporns, O & Giannakis, GB 2017, Multi-kernel change detection for dynamic functional connectivity graphs. in MB Matthews (ed.), Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017, vol. 2017-October, Institute of Electrical and Electronics Engineers Inc., pp. 1555-1559, 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017, Pacific Grove, United States, 10/29/17. https://doi.org/10.1109/ACSSC.2017.8335618

Karanikolas GV, Sporns O, Giannakis GB. Multi-kernel change detection for dynamic functional connectivity graphs. In Matthews MB, editor, Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1555-1559. (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017). doi: 10.1109/ACSSC.2017.8335618

Karanikolas, Georgios Vasileios ; Sporns, Olaf ; Giannakis, Georgios B. / Multi-kernel change detection for dynamic functional connectivity graphs. Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. editor / Michael B. Matthews. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1555-1559 (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017).

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Multi-kernel change detection for dynamic functional connectivity graphs

Abstract

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Keywords

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