Functional Magnetic Resonance Imaging Phase Synchronization as a Measure of Dynamic Functional Connectivity

By Enrico Glerean, Juha Salmi, Juha M. Lahnakoski, Iiro P. Jääskeläinen, Mikko Sams. Brain Connectivity, 2012

336 citations recorded by the source corpus.

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 an 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 artifactual 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: (1) seed-based PS, (2) intersubject PS, and (3) intersubject seed-based PS. 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.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/66832277e26adc97a935e69bfc692baffa6c2164

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In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Generation and Evaluation of a Cortical Area Parcellation from Resting-State Correlations. (2016, background): “2012), functional connectivity dynamics (Glerean et al. 2012), task control processes (Cole et al.”
The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core (2016, neutral): “This frequency band has been mapped to the gray matter and it has been shown to be more reliable and functionally relevant than other frequency bands 63–66 .”
Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: Models and mechanisms (2017, positive): “For instance, Coherence Connectivity (CC) consists in computing the phase coherence between time series at each recording frame (Glerean et al., 2012, Ponce-Alvarez et al., 2015, Deco and Kringelbach, 2016).”
Aperiodic parameters of the fMRI power spectrum associate with preterm birth and neonatal age (2026, unknown): “For a summary on frequency range selection in earlier studies on BOLD signal, see Glerean et al. 97 .”