Back close

Minimum connected component – A novel approach to detection of cognitive load induced changes in functional brain networks

Publication Type : Journal Article

Publisher : Elsevier

Source : Neurocomputing

Url : https://doi.org/10.1016/j.neucom.2015.03.092.

Campus : Coimbatore

School : School of Physical Sciences

Department : Mathematics

Year : 2015

Abstract : Recent advances in computational neuroscience have enabled trans-disciplinary researchers to address challenging tasks such as the identification and characterization of cognitive function in the brain. The application of graph theory has contributed to the modelling and understanding the brain dynamics. This paper presents a new approach based on a special graph theoretic concept called minimum connected component (MCC) to detect cognitive load induced changes in functional brain networks using EEG data. The results presented in this paper clearly demonstrate that the MCC based analysis of the functional brain networks derived from multi-channel EEG data is able to detect and quantify changes across the scalp in response to specific cognitive tasks. The MCC, due to its sensitivity to cognitive load, has the potential to be used as a tool not only to measure cognitive activity quantitatively, but also to detect cognitive impairment.

Cite this Research Publication : R. Vijayalakshmi, D. Nandagopal, N. Dasari, B. Cocks, N. Dahal, M. Thilaga, Minimum connected component – A novel approach to detection of cognitive load induced changes in functional brain networks, Neurocomputing, Vol. 170, 2015, 15-31, ISSN 0925-2312, https://doi.org/10.1016/j.neucom.2015.03.092.

Admissions Apply Now