Age-related Unstable Transient States and Imbalanced Activation Proportion of Brain Networks in People with Autism Spectrum Disorder: A Resting-state FMRI Study Using Coactivation Pattern Analyses

Overview

Journal Netw Neurosci

Publisher MIT Press

Specialty Neurology

Date 2024 Dec 30

PMID 39735491

Authors

Yunge Zhang

Lin Lin

Dongyue Zhou

Yang Song

Abigail Stein

Shuqin Zhou

Huashuai Xu

Wei Zhao

Fengyu Cong

Jin Sun

Huanjie Li

Fei Du

Affiliations

Soon will be listed here.

Abstract

The atypical static brain functions related to the executive control network (ECN), default mode network (DMN), and salience network (SN) in people with autism spectrum disorder (ASD) has been widely reported. However, their transient functions in ASD are not clear. We aim to identify transient network states (TNSs) using coactivation pattern (CAP) analysis to characterize the age-related atypical transient functions in ASD. CAP analysis was performed on a resting-state fMRI dataset (78 ASD and 78 healthy control (CON) juveniles, 54 ASD and 54 CON adults). Six TNSs were divided into the DMN-TNSs, ECN-TNSs, and SN-TNSs. The DMN-TNSs were major states with the highest stability and proportion, and the ECN-TNSs and SN-TNSs were minor states. Age-related abnormalities on spatial stability and TNS proportion were found in ASD. The spatial stability of DMN-TNSs was found increasing with age in CON, but was not found in ASD. A lower proportion of DMN-TNSs was found in ASD compared with CON of the same age, and ASD juveniles had a higher proportion of SN-TNSs while ASD adults had a higher proportion of ECN-TNSs. The abnormalities on spatial stability and TNS proportion were related to social deficits. Our results provided new evidence for atypical transient brain functions in people with ASD.

References

Vergara V, Mayer A, Damaraju E, Calhoun V . The effect of preprocessing in dynamic functional network connectivity used to classify mild traumatic brain injury. Brain Behav. 2017; 7(10):e00809. PMC: 5651393. DOI: 10.1002/brb3.809. View

Urchs S, Tam A, Orban P, Moreau C, Benhajali Y, Nguyen H . Functional connectivity subtypes associate robustly with ASD diagnosis. Elife. 2022; 11. PMC: 9708070. DOI: 10.7554/eLife.56257. View

Amso D, Haas S, Tenenbaum E, Markant J, Sheinkopf S . Bottom-up attention orienting in young children with autism. J Autism Dev Disord. 2013; 44(3):664-73. PMC: 4089391. DOI: 10.1007/s10803-013-1925-5. View

Menon V . Large-scale brain networks and psychopathology: a unifying triple network model. Trends Cogn Sci. 2011; 15(10):483-506. DOI: 10.1016/j.tics.2011.08.003. View

Fedorenko E, Duncan J, Kanwisher N . Broad domain generality in focal regions of frontal and parietal cortex. Proc Natl Acad Sci U S A. 2013; 110(41):16616-21. PMC: 3799302. DOI: 10.1073/pnas.1315235110. View

Hong S, Vos de Wael R, Bethlehem R, Lariviere S, Paquola C, Valk S . Atypical functional connectome hierarchy in autism. Nat Commun. 2019; 10(1):1022. PMC: 6399265. DOI: 10.1038/s41467-019-08944-1. View

Liegeois R, Li J, Kong R, Orban C, Van De Ville D, Ge T . Resting brain dynamics at different timescales capture distinct aspects of human behavior. Nat Commun. 2019; 10(1):2317. PMC: 6534566. DOI: 10.1038/s41467-019-10317-7. View

Smith S, Jenkinson M, Woolrich M, Beckmann C, Behrens T, Johansen-Berg H . Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage. 2004; 23 Suppl 1:S208-19. DOI: 10.1016/j.neuroimage.2004.07.051. View

Bi X, Zhao J, Xu Q, Sun Q, Wang Z . Abnormal Functional Connectivity of Resting State Network Detection Based on Linear ICA Analysis in Autism Spectrum Disorder. Front Physiol. 2018; 9:475. PMC: 5952255. DOI: 10.3389/fphys.2018.00475. View

10.

Huang Z, Zhang J, Wu J, Mashour G, Hudetz A . Temporal circuit of macroscale dynamic brain activity supports human consciousness. Sci Adv. 2020; 6(11):eaaz0087. PMC: 7065875. DOI: 10.1126/sciadv.aaz0087. View

11.

Sharma S, Gonda X, Tarazi F . Autism Spectrum Disorder: Classification, diagnosis and therapy. Pharmacol Ther. 2018; 190:91-104. DOI: 10.1016/j.pharmthera.2018.05.007. View

12.

Xia Y, Xia M, Liu J, Liao X, Lei T, Liang X . Development of functional connectome gradients during childhood and adolescence. Sci Bull (Beijing). 2022; 67(10):1049-1061. DOI: 10.1016/j.scib.2022.01.002. View

13.

Kupis L, Romero C, Dirks B, Hoang S, Parlade M, Beaumont A . Evoked and intrinsic brain network dynamics in children with autism spectrum disorder. Neuroimage Clin. 2020; 28:102396. PMC: 7479441. DOI: 10.1016/j.nicl.2020.102396. View

14.

Yeo B, Krienen F, Sepulcre J, Sabuncu M, Lashkari D, Hollinshead M . The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol. 2011; 106(3):1125-65. PMC: 3174820. DOI: 10.1152/jn.00338.2011. View

15.

Liu X, Duyn J . Time-varying functional network information extracted from brief instances of spontaneous brain activity. Proc Natl Acad Sci U S A. 2013; 110(11):4392-7. PMC: 3600481. DOI: 10.1073/pnas.1216856110. View

16.

Uddin L . Salience processing and insular cortical function and dysfunction. Nat Rev Neurosci. 2014; 16(1):55-61. DOI: 10.1038/nrn3857. View

17.

Sapey-Triomphe L, Boets B, Van Eylen L, Noens I, Sunaert S, Steyaert J . Ventral stream hierarchy underlying perceptual organization in adolescents with autism. Neuroimage Clin. 2020; 25:102197. PMC: 6997624. DOI: 10.1016/j.nicl.2020.102197. View

18.

Caballero C, Mistry S, Torres E . Age-Dependent Statistical Changes of Involuntary Head Motion Signatures Across Autism and Controls of the ABIDE Repository. Front Integr Neurosci. 2020; 14:23. PMC: 7311771. DOI: 10.3389/fnint.2020.00023. View

19.

Liang X, Zou Q, He Y, Yang Y . Topologically Reorganized Connectivity Architecture of Default-Mode, Executive-Control, and Salience Networks across Working Memory Task Loads. Cereb Cortex. 2015; 26(4):1501-1511. PMC: 4785946. DOI: 10.1093/cercor/bhu316. View

20.

Janes A, Peechatka A, Frederick B, Kaiser R . Dynamic functioning of transient resting-state coactivation networks in the Human Connectome Project. Hum Brain Mapp. 2019; 41(2):373-387. PMC: 7268046. DOI: 10.1002/hbm.24808. View