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Novel Pattern Mining Approach for Identifying Cognitive Activity in EEG based Functional Brain Networks

Publication Type : Journal Article

Publisher : World Scientific 

Source : J Integr Neurosci

Url : https://pubmed.ncbi.nlm.nih.gov/27401999/

Campus : Coimbatore

School : School of Physical Sciences

Department : Mathematics

Year : 2016

Abstract : The complex nature of neuronal interactions of the human brain has posed many challenges to the research community. To explore the underlying mechanisms of neuronal activity of cohesive brain regions during different cognitive activities, many innovative mathematical and computational models are required. This paper presents a novel Common Functional Pattern Mining approach to demonstrate the similar patterns of interactions due to common behavior of certain brain regions. The electrode sites of EEG-based functional brain network are modeled as a set of transactions and node-based complex network measures as itemsets. These itemsets are transformed into a graph data structure called Functional Pattern Graph. By mining this Functional Pattern Graph, the common functional patterns due to specific brain functioning can be identified. The empirical analyses show the efficiency of the proposed approach in identifying the extent to which the electrode sites (transactions) are similar during various cognitive load states.

Cite this Research Publication : Thilaga M, Vijayalakshmi R, Nadarajan R, Nandagopal D. A novel pattern mining approach for identifying cognitive activity in EEG based functional brain networks. J Integr Neurosci. 2016 Jun;15(2):223-45. doi: 10.1142/S0219635216500151. Epub 2016 Jul 11. PMID: 27401999.

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