Frontiers in Systems Neuroscience Systems Neuroscience

Abstract

, analysis of these spontaneous fluctuations usually involves the identification of correlations between remote brain areas, commonly referred to as functional connectivity. The term " functional connectivity " has been used in both resting-state and task-state studies and can refer to correlations across subjects, runs, blocks, trials, or individual BOLD time points, an ambiguity which can become confusing (Friston et al. We will therefore use the term resting state functional connectivity MRI (fcMRI) for added specificity, and this will be the focus of the present article. The two most popular techniques for performing resting state fcMRI are seed-based correlations and independent components analysis (ICA). In the seed-based technique signal is extracted from a specific region of interest, and a map is created by computing the correlation between this extracted signal and all other brain voxels (Biswal et al., 1995; Fox and Raichle, 2007). In contrast, ICA considers all voxels at once and uses a mathematical algorithm to separate a dataset into distinct systems or networks that are correlated in their spontaneous fluctuations but also maximally independent, Regardless of the technique, a consistent observation is that regions with similar functional properties, such as the left and right somatomotor cortices, exhibit coherent BOLD fluctuations even in the absence of movement under resting conditions (Biswal et al., and a frontal opercular network that has been related to stimulus salience