Dynamic time warping outperforms Pearson correlation in detecting atypical functional connectivity in autism spectrum disorders

• Published in: NeuroImage (Orlando, Fla.) Fla.), 2020-12, Vol.223, p.117383-117383, Article 117383
• Main Authors: Linke, A.C., Mash, L.E., Fong, C.H., Kinnear, M.K., Kohli, J.S., Wilkinson, M., Tung, R., Jao Keehn, R.J., Carper, R.A., Fishman, I., Müller, R.-.A.
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Autism; Autism spectrum disorder; Autism Spectrum Disorder - diagnostic imaging; Autism Spectrum Disorder - physiopathology; Biomarkers; Brain; Brain - diagnostic imaging; Brain - physiopathology; Brain mapping; Brain Mapping - methods; Child; Data Interpretation, Statistical; Dynamic time warping; Estimates; Executive function; Female; Functional connectivity; Functional magnetic resonance imaging; Functional MRI; Hemodynamics; Humans; Image Processing, Computer-Assisted - methods; Magnetic Resonance Imaging; Male; Methods; Neural networks; Neural Pathways - diagnostic imaging; Neural Pathways - physiopathology; Noise; Nonlinear Dynamics; Resting state; Time series; Timeseries analysis; Young Adult
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2020.117383

Resting state fMRI (rsfMRI) is frequently used to study brain function, including in clinical populations. Similarity of blood-oxygen-level-dependent (BOLD) fluctuations during rsfMRI between brain regions is thought to reflect intrinsic functional connectivity (FC), potentially due to history of coactivation. To quantify similarity, studies have almost exclusively relied on Pearson correlation, which assumes linearity and can therefore underestimate FC if the hemodynamic response function differs regionally or there is BOLD signal lag between timeseries. Here we show in three cohorts of children, adolescents and adults, with and without autism spectrum disorders (ASDs), that measuring the similarity of BOLD signal fluctuations using non-linear dynamic time warping (DTW) is more robust to global signal regression (GSR), has higher test-retest reliability and is more sensitive to task-related changes in FC. Additionally, when comparing FC between individuals with ASDs and typical controls, more group differences are detected using DTW. DTW estimates are also more related to ASD symptom severity and executive function, while Pearson correlation estimates of FC are more strongly associated with respiration during rsfMRI. Together these findings suggest that non-linear methods such as DTW improve estimation of resting state FC, particularly when studying clinical populations whose hemodynamics or neurovascular coupling may be altered compared to typical controls.