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  Connectome-wide structure-function coupling models implicate polysynaptic alterations in autism

Park, B.-y., Benkarim, O., Weber, C. F., Kebets, V., Fett, S., Yoo, S., et al. (2024). Connectome-wide structure-function coupling models implicate polysynaptic alterations in autism. NeuroImage, 285: 120481. doi:10.1016/j.neuroimage.2023.120481.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000E-038B-2 Version Permalink: https://hdl.handle.net/21.11116/0000-000F-17B5-B
Genre: Journal Article

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 Creators:
Park, Bo-yong1, 2, 3, 4, Author
Benkarim, Oualid1, Author
Weber, Clara F.1, Author
Kebets, Valeria1, Author
Fett, Serena1, Author
Yoo, Seulki5, Author
Martino, Adriana Di6, Author
Milham, Michael P.6, Author
Misic, Bratislav1, Author
Valk, Sofie L.7, Author                 
Hong, Seok-Jun1, 4, 6, 8, Author
Bernhardt, Boris C.1, Author
Affiliations:
1McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, QC, Canada, ou_persistent22              
2Department of Data Science, Inha University, Incheon, Republic of Korea, ou_persistent22              
3Department of Statistics and Data Science, Inha University, Incheon, Republic of Korea, ou_persistent22              
4Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea, ou_persistent22              
5Convergence Research Institute, Sungkyunkwan University, Suwon, Republic of Korea, ou_persistent22              
6Center for the Developing Brain, Child Mind Institute, New York, NY, USA, ou_persistent22              
7Otto Hahn Group Cognitive Neurogenetics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_3222264              
8Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea, ou_persistent22              

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Free keywords: Autism; Diffusion time; Structure-function coupling; Synaptic communication
 Abstract: Autism spectrum disorder (ASD) is one of the most common neurodevelopmental diagnoses. Although incompletely understood, structural and functional network alterations are increasingly recognized to be at the core of the condition. We utilized multimodal imaging and connectivity modeling to study structure-function coupling in ASD and probed mono- and polysynaptic mechanisms on structurally-governed network function. We examined multimodal magnetic resonance imaging data in 80 ASD and 61 neurotypical controls from the Autism Brain Imaging Data Exchange (ABIDE) II initiative. We predicted intrinsic functional connectivity from structural connectivity data in each participant using a Riemannian optimization procedure that varies the times that simulated signals can unfold along tractography-derived personalized connectomes. In both ASD and neurotypical controls, we observed improved structure-function prediction at longer diffusion time scales, indicating better modeling of brain function when polysynaptic mechanisms are accounted for. Prediction accuracy differences (∆prediction accuracy) were marked in transmodal association systems, such as the default mode network, in both neurotypical controls and ASD. Differences were, however, lower in ASD in a polysynaptic regime at higher simulated diffusion times. We compared regional differences in ∆prediction accuracy between both groups to assess the impact of polysynaptic communication on structure-function coupling. This analysis revealed that between-group differences in ∆prediction accuracy followed a sensory-to-transmodal cortical hierarchy, with an increased gap between controls and ASD in transmodal compared to sensory/motor systems. Multivariate associative techniques revealed that structure-function differences reflected inter-individual differences in autistic symptoms and verbal as well as non-verbal intelligence. Our network modeling approach sheds light on atypical structure-function coupling in autism, and suggests that polysynaptic network mechanisms are implicated in the condition and that these can help explain its wide range of associated symptoms.

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Language(s): eng - English
 Dates: 2023-11-292023-05-202023-12-012023-12-022024-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.neuroimage.2023.120481
Other: epub 2023
PMID: 38043839
 Degree: -

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Project name : -
Grant ID : NRF-2021R1F1A1052303; NRF-2022R1A5A7033499
Funding program : -
Funding organization : National Research Foundation of Korea (NRF)
Project name : Institute for Information and Communications Technology Planning and Evaluation (IITP)
Grant ID : 2022–0–00448; RS-2022–00155915; 2021–0–02068
Funding program : -
Funding organization : Korea Government (MSIT)
Project name : -
Grant ID : IBS-R015-D1
Funding program : -
Funding organization : Institute for Basic Science
Project name : -
Grant ID : NSERC Discovery-1304413
Funding program : -
Funding organization : National Science and Engineering Research Council of Canada (NSERC)
Project name : -
Grant ID : FDN-154298
Funding program : -
Funding organization : Canadian Institutes of Health Research (CIHR)
Project name : -
Grant ID : NI17–039
Funding program : -
Funding organization : SickKids Foundation

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 285 Sequence Number: 120481 Start / End Page: - Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166