FMRI phase synchronization as a measure of dynamic functional connectivity.

Brain Connect. 2012 May 4;

Authors: Glerean E, Salmi J, Lahnakoski JM, Jääskeläinen IP, Sams M

Abstract
Functional brain activity and connectivity have been studied by calculating intersubject and seed-based correlations of hemodynamic data acquired with functional magnetic resonance imaging (fMRI). To inspect temporal dynamics, these correlation measures have been calculated over sliding time windows with necessary restrictions on the length of the temporal window that compromises the temporal resolution. Here, we show that it is possible to increase temporal resolution by using instantaneous phase synchronization (PS) as a measure of dynamic (time-varying) functional connectivity. We applied PS on a fMRI dataset obtained while 12 healthy volunteers watched a feature film. Narrow frequency band (0.04 - 0.07 Hz) was used in the PS analysis to avoid artefactual results. We defined three metrics for computing time-varying functional connectivity and time-varying intersubject reliability based on estimation of instantaneous PS across the subjects: i) Seed-Based Phase Synchronization (SBPS), ii) Intersubject Phase Synchronization (IPS), and iii) Intersubject Seed-Based Phase Synchronization (ISBPS). Our findings show that these PS-based metrics yield results consistent with both seed-based correlation and intersubject correlation methods when inspected over the whole time series, but provide an important advantage of maximal single-TR temporal resolution. These metrics can be applied both in studies with complex naturalistic stimuli (e.g., watching a movie or listening to music in the MRI scanner) and more controlled (e.g., event-related or blocked design) paradigms. A Matlab toolbox - FUNPSY, http://becs.aalto.fi/bml/software.html is openly available for using these metrics in fMRI data analysis.

PMID: 22559794 [PubMed - as supplied by publisher]