Open AccessCharacterizing instantaneous phase relationships in whole‐brain fMRI activation data
Author(s) -
Laird Angela R.,
Rogers Baxter P.,
Carew John D.,
Arfanakis Konstantinos,
Moritz Chad H.,
Meyerand M. Elizabeth
Publication year - 2002
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.10027
Subject(s) - phase synchronization , synchronization (alternating current) , voxel , computer science , nonparametric statistics , finger tapping , functional magnetic resonance imaging , pattern recognition (psychology) , statistical parametric mapping , time series , artificial intelligence , mathematics , psychology , channel (broadcasting) , neuroscience , machine learning , statistics , magnetic resonance imaging , medicine , computer network , audiology , radiology
Typically, fMRI data is processed in the time domain with linear methods such as regression and correlation analysis. We propose that the theory of phase synchronization may be used to more completely understand the dynamics of interacting systems, and can be applied to fMRI data as a novel method of detecting activation. Generalized synchronization is a phenomenon that occurs when there is a nonlinear functional relationship present between two or more coupled, oscillatory systems, whereas phase synchronization is defined as the locking of the phases while the amplitudes may vary. In this study, we developed an application of phase synchronization analysis that is appropriate for fMRI data, in which the phase locking condition is investigated between a voxel time series and the reference function of the task performed. A synchronization index is calculated to quantify the level of phase locking, and a nonparametric permutation test is used to determine the statistical significance of the results. We performed the phase synchronization analysis on the data from five volunteers for an event‐related finger‐tapping task. Functional maps were created that provide information on the interrelations between the instantaneous phases of the reference function and the voxel time series in a whole‐brain fMRI activation data set. We conclude that this method of analysis is useful for revealing additional information on the complex nature of the fMRI time series. Hum. Brain Mapping 16:71–80, 2002. © 2002 Wiley‐Liss, Inc.