Literature DB >> 31730872

Effects of motion related outliers in dynamic functional connectivity using the sliding window method.

Antonis D Savva1, Michalis Kassinopoulos2, Nikolaos Smyrnis3, George K Matsopoulos4, Georgios D Mitsis5.   

Abstract

BACKGROUND: It has been suggested that the use of window functions, other than the rectangular, in the sliding window method, may be beneficial for reducing the effects of motion-related outliers in the time-series, when assessing dynamic functional connectivity (dFC) in resting-state fMRI (rs-fMRI).
METHODOLOGY: Ten window functions for a wide range of window lengths (20-150 s) combined with Pearson and Kendall correlation metrics, were investigated. One hundred high quality rs-fMRI datasets from healthy controls, were used to systematically assess the effect of varying the window function and length on dFC assessment. To this end, two approaches were implemented: a) simulated outliers were added to the experimental data and b) the experimental data were divided into low and high motion subgroups.
RESULTS: The presence of experimental motion-noise tended to inflate the number of dynamic connections for longer (≥100 s) wide-shaped windows, while shorter (20-30 s) narrow-shaped windows exhibited increased sensitivity in the presence of simulated outliers. Moreover, window sizes from 60 s to 90 s were mildly affected by motion-related effects. In most cases, the number of dynamic connections increased, and gradually lower frequencies were captured, with an increasing window size.
CONCLUSIONS: Subject motion considerably affects the obtained dFC patterns; thus, it is preferable to perform motion artefact removal in the pre-processing stage rather than using alternative window functions to mitigate their effects. Provided that motion-noise is not excessive, the choice of a rectangular window is adequate. Finally, low frequency oscillations in functional connectivity seem to play an important role in the context of dFC assessment.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Default mode network; Motion; Outliers; Resting-state fMRI; Weighted Kendall correlation; Weighted Pearson correlation

Mesh:

Year:  2019        PMID: 31730872     DOI: 10.1016/j.jneumeth.2019.108519

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  7 in total

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Authors:  Nima Asadi; Ingrid R Olson; Zoran Obradovic
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7.  Abnormal Dynamic Functional Connectivity of the Left Rostral Hippocampus in Predicting Antidepressant Efficacy in Major Depressive Disorder.

Authors:  Shao-Wei Xue; Changxiao Kuai; Yang Xiao; Lei Zhao; Zhihui Lan
Journal:  Psychiatry Investig       Date:  2022-07-21       Impact factor: 3.202

  7 in total

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