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

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 min). Consequently, connectivity patterns for two different portions of the same scan can differ drastically. To better characteri...

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Bibliographic Details
Published in:	Frontiers in neuroscience Vol. 8; p. 138
Main Authors:	Gonzalez-Castillo, Javier, Handwerker, Daniel A, Robinson, Meghan E, Hoy, Colin Weir, Buchanan, Laura C, Saad, Ziad S, Bandettini, Peter A
Format:	Journal Article
Language:	English
Published:	Switzerland Frontiers Research Foundation 11-06-2014 Frontiers Media S.A
Subjects:	Alzheimer's disease Biomarkers Brain research Cerebrospinal fluid Cognitive ability Connectivity Dynamics Cortex (frontal) fMRI Functional magnetic resonance imaging Information processing Mental health Neural networks Neuroscience NMR Nuclear magnetic resonance Occipital lobe Polarity Rest Sliding Window Analysis stability Studies Temporal cortex United States > US fMRI rest connectivity dynamics sliding window analysis stability
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Summary:	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 min). 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 min, at a temporal resolution of 1 s, while they rested inside the scanner. We then computed connectivity matrices between functionally-defined regions of interest for non-overlapping 1 min 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 state 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 min to optimize within-subject reproducibility of connectivity patterns across the entire brain, rather than a few predefined networks.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 Edited by: Christopher W. Tyler, Smith-Kettlewell Eye Research Institute, USA Reviewed by: Xi-Nian Zuo, Chinese Academy of Sciences, China; R. Matthew Hutchison, Western University, Canada This article was submitted to Brain Imaging Methods, a section of the journal Frontiers in Neuroscience.
ISSN:	1662-4548 1662-453X 1662-453X
DOI:	10.3389/fnins.2014.00138