Comparison of Network Analysis Approaches on EEG Connectivity in Beta during Visual Short-Term Memory Binding Tasks

Keith Smith, Hamed Azami, Javier Escudero, Mario A. Parra, John M. Starr

Research output: Contribution to conferencePaperpeer-review

Abstract

We analyse the electroencephalogram signals in the beta band of working memory representation recorded from young healthy volunteers performing several different Visual Short-Term Memory (VSTM) tasks which have proven useful in the assessment of clinical and preclinical Alzheimer’s disease. We compare network analysis using Maximum Spanning Trees (MSTs) with network analysis obtained using 20% and 25% connection thresholds on the VSTM data. MSTs are a promising method of network analysis negating the more classical use of thresholds which are so far chosen arbitrarily. However, we find that the threshold analyses outperforms MSTs for detection of functional network differences. Particularly, MSTs fail to find any significant differences. Further, the thresholds detect significant differences between shape and shape-colour binding tasks when these are tested in the left side of the display screen, but no such differences are detected when these tasks are tested for in the right side of the display screen. This provides evidence that contralateral activity is a significant factor in sensitivity for detection of cognitive task differences.
Original languageEnglish
Pages2207-2210
Number of pages4
Publication statusPublished - 26 Aug 2015
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - MiCo, Milan, Italy
Duration: 26 Aug 201529 Aug 2015

Conference

Conference37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Country/TerritoryItaly
CityMilan
Period26/08/1529/08/15

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