The spatial structure of resting state connectivity stability on the scale of minutes

• Main Authors: Javier eGonzalez-Castillo, Handwerker A Daniel, Meghan E. Robinson, Colin Weir Hoy, Laura Cathleen Buchanan, Ziad S Saad, Peter A Bandettini
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2014-06-01
• Series: Frontiers in Neuroscience
• Subjects: Rest; fMRI; stability; Connectivity Dynamics; Sliding Window Analysis
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00138/full

Resting state functional MRI (rsfMRI) connectivity patterns are not temporally stable, but fluctuate in time at scales shorter than most common rest scan durations (5 - 10 minutes). Consequently, connectivity patterns for two different portions of the same scan can differ drastically. To better characterize this temporal variability and understand how it is spatially distributed across the brain, we scanned subjects continuously for 60 minutes, at a temporal resolution of 1 second, while they rested inside the scanner. We then computed connectivity matrices between functionally-defined regions of interest for non-overlapping one minute windows, and classified connections according to their strength, polarity and variability. We found that the most stable connections correspond primarily to inter-hemispheric connections between left/right homologous ROIs. However, only 32% of all within-network connections were classified as most stable. This shows that resting stating networks have some long-term stability, but confirms the flexible configuration of these networks, particularly, those related to higher order cognitive functions. The most variable connections correspond primarily to inter-hemispheric across-network connections between non-homologous regions in occipital and frontal cortex. Finally we found a series of connections with negative average correlation, but further analyses revealed that such average negative correlations may be related to the removal of CSF signals during pre-processing. Using the same dataset, we also evaluated how similarity of within-subject whole-brain connectivity matrices changes as a function of window duration (used here as a proxy for scan duration). Our results suggest scanning for a minimum of 10 minutes to optimize within-subject reproducibility of connectivity patterns across the entire brain rather than a few predefined networks.