title: Comparison of network analysis approaches on EEG connectivity in beta during Visual Short-term Memory binding tasks.
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.
authors.forename: Keith
authors.initials: K
authors.lastname: Smith
authors.forename: Hamed
authors.initials: H
authors.lastname: Azami
authors.forename: Javier
authors.initials: J
authors.lastname: Escudero
authors.forename: Mario A
authors.initials: MA
authors.lastname: Parra
authors.forename: John M
authors.initials: JM
authors.lastname: Starr
mesh_terms: D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008570:Memory, Short-Term / Q000502:physiology*; D033281:Nontherapeutic Human Experimentation; D012815:Signal Processing, Computer-Assisted; D014796:Visual Perception