Weak Mutual Information between Functional Domains in Schizophrenia

Mustafa S. Salman; Victor M. Vergara; Eswar Damaraju; Vince D. Calhoun

doi:10.1109/ACSSC.2018.8645233

Weak Mutual Information between Functional Domains in Schizophrenia

Mustafa S. Salman, Victor M. Vergara, Eswar Damaraju, Vince D. Calhoun

School of Medicine

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

Abstract

Recently whole brain dynamic functional network connectivity (dFNC) has become an area of increasing focus in functional magnetic resonance imaging (fMRI) studies. Dynamic functional domain connectivity (dFDC) is a novel information theoretic framework which measures information flow between subsets of the whole brain dFNC. The information shared between domains can potentially shine light on brain disorders. Here we employ this framework to analyze an fMRI dataset containing 163 healthy controls (HCs) and 151 schizophrenia patients (SZs). We measured the entropy within each dFDC and the cross domain mutual information (CDMI) between pairs of dFDC. We performed linear regression on transformed entropy and CDMI to find significant group differences. Results indicate that SZs show significantly higher (transformed) entropy than HCs in subcortical (SC)-SC, default mode (DMN)-SC, cerebellar (CB)auditory (AUD), and CB-attention (ATTN) dFDC. They also demonstrate lower (transformed) CDMI than HCs between SC-visual (VIS) and SC-AUD, AUD-AUD and SC-AUD, AUD-sensorimotor (SM) and AUD-AUD, SM-ATTN and AUD-ATTN, SM-frontal (FRN) and AUD-FRN, VIS-ATTN and SM-ATTN as well as VIS-FRN and SM-FRN dFDC pairs. This implies that different dFDC pairs share lower mutual information in SZs compared to HCs. This in turn corroborates the notion that SZs demonstrate reduced connectivity dynamism in fMRI.

Original language	English (US)
Title of host publication	Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
Editors	Michael B. Matthews
Publisher	IEEE Computer Society
Pages	1362-1366
Number of pages	5
ISBN (Electronic)	9781538692189
DOIs	https://doi.org/10.1109/ACSSC.2018.8645233
State	Published - Jul 2 2018
Event	52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 - Pacific Grove, United States Duration: Oct 28 2018 → Oct 31 2018

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
Volume	2018-October
ISSN (Print)	1058-6393

Conference

Conference	52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
Country/Territory	United States
City	Pacific Grove
Period	10/28/18 → 10/31/18

Keywords

JMRI
connectivity
domain
dynamic
entropy
functional network
information theory
mutual information
schizophrenia

ASJC Scopus subject areas

Signal Processing
Computer Networks and Communications

Access to Document

10.1109/ACSSC.2018.8645233

Cite this

Salman, M. S., Vergara, V. M., Damaraju, E., & Calhoun, V. D. (2018). Weak Mutual Information between Functional Domains in Schizophrenia. In M. B. Matthews (Ed.), Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 (pp. 1362-1366). Article 8645233 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2018-October). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2018.8645233

Weak Mutual Information between Functional Domains in Schizophrenia. / Salman, Mustafa S.; Vergara, Victor M.; Damaraju, Eswar et al.
Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018. ed. / Michael B. Matthews. IEEE Computer Society, 2018. p. 1362-1366 8645233 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2018-October).

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

Salman, MS, Vergara, VM, Damaraju, E & Calhoun, VD 2018, Weak Mutual Information between Functional Domains in Schizophrenia. in MB Matthews (ed.), Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018., 8645233, Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2018-October, IEEE Computer Society, pp. 1362-1366, 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018, Pacific Grove, United States, 10/28/18. https://doi.org/10.1109/ACSSC.2018.8645233

Salman MS, Vergara VM, Damaraju E, Calhoun VD. Weak Mutual Information between Functional Domains in Schizophrenia. In Matthews MB, editor, Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018. IEEE Computer Society. 2018. p. 1362-1366. 8645233. (Conference Record - Asilomar Conference on Signals, Systems and Computers). doi: 10.1109/ACSSC.2018.8645233

Salman, Mustafa S. ; Vergara, Victor M. ; Damaraju, Eswar et al. / Weak Mutual Information between Functional Domains in Schizophrenia. Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018. editor / Michael B. Matthews. IEEE Computer Society, 2018. pp. 1362-1366 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

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N2 - Recently whole brain dynamic functional network connectivity (dFNC) has become an area of increasing focus in functional magnetic resonance imaging (fMRI) studies. Dynamic functional domain connectivity (dFDC) is a novel information theoretic framework which measures information flow between subsets of the whole brain dFNC. The information shared between domains can potentially shine light on brain disorders. Here we employ this framework to analyze an fMRI dataset containing 163 healthy controls (HCs) and 151 schizophrenia patients (SZs). We measured the entropy within each dFDC and the cross domain mutual information (CDMI) between pairs of dFDC. We performed linear regression on transformed entropy and CDMI to find significant group differences. Results indicate that SZs show significantly higher (transformed) entropy than HCs in subcortical (SC)-SC, default mode (DMN)-SC, cerebellar (CB)auditory (AUD), and CB-attention (ATTN) dFDC. They also demonstrate lower (transformed) CDMI than HCs between SC-visual (VIS) and SC-AUD, AUD-AUD and SC-AUD, AUD-sensorimotor (SM) and AUD-AUD, SM-ATTN and AUD-ATTN, SM-frontal (FRN) and AUD-FRN, VIS-ATTN and SM-ATTN as well as VIS-FRN and SM-FRN dFDC pairs. This implies that different dFDC pairs share lower mutual information in SZs compared to HCs. This in turn corroborates the notion that SZs demonstrate reduced connectivity dynamism in fMRI.

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Weak Mutual Information between Functional Domains in Schizophrenia

Abstract

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Keywords

ASJC Scopus subject areas

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