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Characterizing the developmental trajectory of functional hierarchy in autistic children

Poster No:

383 

Submission Type:

Abstract Submission 

Authors:

Sunghun Kim1, Jong-eun Lee2, Hyunjin Park3

Institutions:

1Sungkyunkwan university, Suwon-si, Gyeonggi-do, 2Sungkyunkwan University, Suwon-si, Gyeonggi-do, 3Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Kyeonggi-do

First Author:

Sunghun Kim  
Sungkyunkwan university
Suwon-si, Gyeonggi-do

Co-Author(s):

Jong-eun Lee  
Sungkyunkwan University
Suwon-si, Gyeonggi-do
Hyunjin Park  
Center for Neuroscience Imaging Research, Institute for Basic Science
Suwon, Kyeonggi-do

Introduction:

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by a wide range of symptoms and abilities, significantly affecting socio-cognitive behaviors. Despite the high biological and clinical heterogeneity observed among individuals with ASD, considerable efforts have been made to understand this condition through neuroimaging biomarkers. Previous research has suggested that functional connectome gradients delineate the axis of connectivity variation between unimodal and transmodal networks and the phenotypical patterns in ASD are associated with a disruption in the macroscale cortical hierarchy. However, the persistent issue of heterogeneity in developing individuals remains and the maturational process of functional hierarchy is poorly understood. To address this gap, we utilized a normative modeling approach to analyze the biological trajectories in ASD, focusing on how cortical hierarchies mature across different developmental stages in children.

Methods:

We constructed cortex-wide functional connectomes using the Schaefer atlas with 200 parcels and estimated the low-dimensional eigenvectors (i.e., gradients). First, a parcellation-level normative model of functional gradients was developed using generalized additive models for location scale and shape (GAMLSS), employing samples from the independent human connectome project development (HCP-D, n = 652) cross-sectional database of typically developing (TD) individuals. We used multi-parameter Sinh-Arcsinh (SHASH) distribution modeling with age and sex as regressors. Second, we estimated individual functional gradients of 503 ASD and 527 TD using the autism brain imaging data exchange (ABIDE) dataset. We then calculated the functional hierarchy score for each individual, defined by the dot-product between the normative gradients curve and the individual gradients. This score reflects the maturity of individual hierarchical organization. The functional hierarchy score was compared between two groups and was used to analyze the groups' developmental rates.
Supporting Image: network_fit.png
   ·Functional network-wise GAMLSS curves using HCP-D dataset.
 

Results:

Our findings reveal that with increasing age during the developmental stages, the macroscale segregation of functional hierarchy gradually became evident. Notably, the sensorimotor and association areas at both ends became increasingly distinct with age. However, individuals with ASD demonstrated a less-segregated functional hierarchy compared to TD individuals, with a significant difference (p-value < 0.001). Furthermore, we observed that the cortical hierarchy evolves in synchrony with age in both groups.

Conclusions:

Developmental changes drive the hierarchical organization of the cortex. Given the high heterogeneity among individuals with ASD, the brain development of individuals with ASD may deviate from standard developmental pathways. These findings support the notion that individuals with ASD possess distinct and individualized brain development trajectories.

This research was supported by the National Research Foundation (NRF-2020M3E5D2A01084892), Institute for Basic Science (IBS-R015-D1), IITP grant funded by the AI Graduate School Support Program (2019-0-00421), and ICT Creative Consilience program (IITP-2020-0-01821).

Disorders of the Nervous System:

Neurodevelopmental/ Early Life (eg. ADHD, autism) 1

Lifespan Development:

Early life, Adolescence, Aging 2

Keywords:

Autism
Development

1|2Indicates the priority used for review

Provide references using author date format

1. Margulies, D.S., et al., Situating the default-mode network along a principal gradient of macroscale cortical organization. Proceedings of the National Academy of Sciences, 2016. 113(44): p. 12574-12579.
2. Hong, S.-J., et al., Atypical functional connectome hierarchy in autism. Nature communications, 2019. 10(1): p. 1022.
3. Schaefer, A., et al., Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI. Cerebral cortex, 2018. 28(9): p. 3095-3114.
4. Rigby, R.A. and D.M. Stasinopoulos, Generalized additive models for location, scale and shape. Journal of the Royal Statistical Society Series C: Applied Statistics, 2005. 54(3): p. 507-554.
5. Somerville, L.H., et al., The Lifespan Human Connectome Project in Development: A large-scale study of brain connectivity development in 5–21 year olds. Neuroimage, 2018. 183: p. 456-468.
6. Di Martino, A., et al., The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular psychiatry, 2014. 19(6): p. 659-667.