Raatikainen, V., Korhonen, V., Borchardt, V., Huotari, N., Helakari, H., Kananen, J., Raitamaa, L., Joskitt, L., Loukusa, S., Hurtig, T., Ebeling, H., Uddin, L.Q. and Kiviniemi, V. (2020), Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder. Autism Research, 13: 244-258. doi:10.1002/aur.2218
Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder
|Author:||Raatikainen, Ville1,2; Korhonen, Vesa1,2; Borchardt, Viola1,2;|
1Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
2Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
3Clinic of Child Psychiatry, Oulu University Hospital, Oulu, Finland
4Research Unit of Logopedics, Faculty of Humanities, University of Oulu, Oulu, Finland
5Department of Psychology, University of Miami, Coral Gables, Florida
|Online Access:||PDF Full Text (PDF, 2.9 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202002256469
John Wiley & Sons,
|Publish Date:|| 2020-02-25
This study investigated whole‐brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting‐state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P‐value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default‐mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large‐scale functional brain networks may contribute to the ASD phenotype.
|Pages:||244 - 258|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
3124 Neurology and psychiatry
520 Other social sciences
This study was financially supported by Academy of Finland Grant 275352 (MREG Analysis of Neuronal Avalanches), JAES grant, and MRC Oulu grant. Additional thanks to Instrumentarium Science Foundation, Finnish Epilepsy Association (FEA), Walter Ahlström Foundation, Finnish Foundation for Technology Promotion, and Tauno Tönning Foundation who supported this research by personal grant (V.R.). L.Q.U. is supported by the National Institute of Mental Health (R01MH107549).
|Academy of Finland Grant Number:||
275352 (Academy of Finland Funding decision)
© 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.