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Effective Brain Connectivity for fNIRS with Fuzzy Cognitive Maps in Neuroergonomics

Kiani, Mehrin and Andreu-Perez, Javier and Hagras, Hani and Papageorgiou, Elpiniki I and Prasad, Mukesh and Lin, Chin-Teng (2019) 'Effective Brain Connectivity for fNIRS with Fuzzy Cognitive Maps in Neuroergonomics.' IEEE Transactions on Cognitive and Developmental Systems. ISSN 2379-8939 (In Press)

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Abstract

Effective connectivity (EC) amongst functional near-infrared spectroscopy (fNIRS) signals is a quantitative measure of the strength of influence between brain activity associated with different regions of the brain. Evidently, accurate deciphering of EC gives further insight into the understanding of the intricately complex nature of neuronal interactions in the human brain. This work presents a novel approach to estimate EC in the human brain signals using enhanced fuzzy cognitive maps (FCMs). The proposed method presents a regularized methodology of FCMs, called effective FCMs (E-FCMs), with improved accuracy for predicting EC between real, and synthetic fNIRS signals. Essentially, the revisions made in the FCM methodology include a more powerful prediction formula for FCM combined with independent tuning of the transformation function parameter. A comparison of EC in fNIRS signals obtained from E-FCM with that obtained from standard FCM, general linear model (GLM) parameters that power Dynamic Causal Modelling (DCM), and Granger Causality (GC) manifests the greater prowess of the proposed E-FCM over the aforementioned methods. For real fNIRS data, an empirical investigation is also made to gain an insight into the role of oxyhemoglobin and deoxyhemoglobin (oxy-Hb, deoxy-Hb) in representing the cognitive activity. We believe this work has profound implications for neuroergonomics research communities.

Item Type: Article
Uncontrolled Keywords: neuroscience, Functional near-infrared spectroscopy, brain connectivity, effective connectivity
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 02 Dec 2019 10:53
Last Modified: 02 Dec 2019 11:15
URI: http://repository.essex.ac.uk/id/eprint/26131

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