Quasi-periodic patterns of intrinsic brain activity in individuals and their relationship to global signal
Quasiperiodic patterns (QPPs) as reported by Majeed et al., 2011 are prominent features of the brain's intrinsic activity that involve important large-scale networks (default mode, DMN; task positive, TPN) and are likely to be major contributors to widely used measures of functional connectivit...
Gespeichert in:
Veröffentlicht in: | NeuroImage (Orlando, Fla.) Fla.), 2018-02, Vol.167, p.297-308 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Quasiperiodic patterns (QPPs) as reported by Majeed et al., 2011 are prominent features of the brain's intrinsic activity that involve important large-scale networks (default mode, DMN; task positive, TPN) and are likely to be major contributors to widely used measures of functional connectivity. We examined the variability of these patterns in 470 individuals from the Human Connectome Project resting state functional MRI dataset. The QPPs from individuals can be coarsely categorized into two types: one where strong anti-correlation between the DMN and TPN is present, and another where most areas are strongly correlated. QPP type could be predicted by an individual's global signal, with lower global signal corresponding to QPPs with strong anti-correlation. After regression of global signal, all QPPs showed strong anti-correlation between DMN and TPN. QPP occurrence and type was similar between a subgroup of individuals with extremely low motion and the rest of the sample, which shows that motion is not a major contributor to the QPPs. After regression of estimates of slow respiratory and cardiac induced signal fluctuations, more QPPs showed strong anti-correlation between DMN and TPN, an indication that while physiological noise influences the QPP type, it is not the primary source of the QPP itself. QPPs were more similar for the same subjects scanned on different days than for different subjects. These results provide the first assessment of the variability in individual QPPs and their relationship to physiological parameters.
•Quasiperiodic patterns from individuals can be coarsely categorized into two types, and the type can be predicted by an individual’s global signal.•After global signal regression, QPPs become remarkably similar in their spatial extent of strong positive or negative correlation, strength and timing across individuals.•Motion and slow physiological fluctuations are not a major contributor to the QPPs.•QPPs are more similar for the same individuals scanned on different days than for different individuals. |
---|---|
ISSN: | 1053-8119 1095-9572 |
DOI: | 10.1016/j.neuroimage.2017.11.043 |