Network Control Insights into Psychopathology and Sex Differences in Youth
Poster No:
514
Submission Type:
Abstract Submission
Authors:
Marie Hedo1, Louisa Schilling2, S. Parker Singleton3, Keith Jamison4, Amy Kuceyeski1
Institutions:
1Cornell, Ithaca, NY, 2Weill Cornell Medicine, new york, NY, 3University of Pennsylvania, Philadelphia, PA, 4Weill Cornell Medicine, New York, NY
First Author:
Co-Author(s):
Introduction:
Adolescence is a critical developmental period characterized by profound environmental, social, and neurological changes, along with an increased vulnerability to psychopathology. Recent shifts in clinical and research paradigms have embraced a dimensional approach to psychopathology. The Hierarchical Taxonomy of Psychopathology (HiTOP) proposes a hierarchical framework, with a general susceptibility to psychiatric disorders at the top, branching into progressively specific dimensions (Kotov et al., 2017). While previous research has identified structural and functional brain differences associated with psychopathology dimensions, much remains unclear, hindering the development of effective intervention and prevention strategies (Royer et al., 2024; Voldsbekk et al., 2023). Moreover, studies examining sex-specific neural correlates of psychopathology are limited. While most research has focused separately on structural and functional MRI data, emerging evidence underscores the importance of structure-function coupling in understanding brain-behavior relationships.
In this study, we investigated the associations between functional brain activity dynamics and childhood psychopathology in boys and girls using multimodal imaging data and network control theory (NCT) tools. Our objectives were to (1) determine whether network and regional transition energies (TEs) are associated with different psychopathology dimensions and (2) explore sex-specific differences in these associations.
In this study, we investigated the associations between functional brain activity dynamics and childhood psychopathology in boys and girls using multimodal imaging data and network control theory (NCT) tools. Our objectives were to (1) determine whether network and regional transition energies (TEs) are associated with different psychopathology dimensions and (2) explore sex-specific differences in these associations.
Methods:
We utilized baseline imaging and behavioral data from the Adolescent Brain Cognitive Development (ABCD) study, including 1,227 girls and 1,073 boys. Resting-state fMRI data were parcellated into 86 regions using the Desikan-Killiany atlas combined with subcortical structures. Brain states were identified using k-means clustering, and an average structural connectome was reconstructed using diffusion-weighted imaging and probabilistic tractography. NCT was applied to compute regional TEs for transitions between the identified brain states. Principal component analysis (PCA) on the five DSM-V-oriented scales of the Child Behavior Checklist (CBCL) yielded three components, representing different aspects of psychopathology: (1) general susceptibility to disorders (PC1), (2) a contrast between internalizing and externalizing symptoms (PC2), and (3) ADHD-related symptoms (PC3).
Linear mixed-effects models (LMEM) were used to assess associations between TEs, sex, and psychopathology dimensions, adjusting for covariates including age, handedness, income-to-needs ratio, and framewise displacement, with imaging site as a random effect. Significant disorder-by-sex interactions were further analyzed using post hoc two-sample t-tests.
Linear mixed-effects models (LMEM) were used to assess associations between TEs, sex, and psychopathology dimensions, adjusting for covariates including age, handedness, income-to-needs ratio, and framewise displacement, with imaging site as a random effect. Significant disorder-by-sex interactions were further analyzed using post hoc two-sample t-tests.
Results:
Our findings revealed that higher externalizing symptoms (PC2) were associated with increased TEs in the somatomotor network, while internalizing symptoms (PC2 × sex interaction) were linked to lower TEs in the limbic network, but only in girls. General psychopathology (PC1) was associated with increased TEs in parietal and temporal regions. Internalizing symptoms were positively associated with TEs in subcortical, temporal, and parietal regions, whereas ADHD-related symptoms (PC3) were linked to increased TEs in the inferior parietal and cingulate cortices.
Conclusions:
These results highlight that structure-function coupling is altered across psychopathology dimensions in childhood and emphasize the influence of sex on these relationships. Our findings underscore the importance of incorporating sex-specific analyses to better understand the neural correlates of childhood psychopathology.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Lifespan Development:
Early life, Adolescence, Aging
Novel Imaging Acquisition Methods:
Multi-Modal Imaging 2
Keywords:
Development
DISORDERS
FUNCTIONAL MRI
Modeling
Psychiatric
Psychiatric Disorders
Tractography
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - youth
1|2Indicates the priority used for review
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2. Michelini, G., Barch, D. M., Tian, Y., Watson, D., Klein, D. N., & Kotov, R. (2019). Delineating and validating higher-order dimensions of psychopathology in the Adolescent Brain Cognitive Development (ABCD) study. Translational Psychiatry, 9(1). https://doi.org/10.1038/s41398-019-0593-4
3. Royer, J., Kebets, V., Piguet, C., Chen, J., Ooi, L. Q. R., Kirschner, M., Siffredi, V., Misic, B., Yeo, B. T., & Bernhardt, B. C. (2023). Multimodal neural correlates of childhood psychopathology. bioRxiv (Cold Spring Harbor Laboratory). https://doi.org/10.1101/2023.03.02.530821
4. Voldsbekk, I., Kjelkenes, R., Dahl, A., Holm, M. C., Lund, M. J., Kaufmann, T., Tamnes, C. K., Andreassen, O. A., Westlye, L. T., & Alnæs, D. (2023). Delineating disorder-general and disorder-specific dimensions of psychopathology from functional brain networks in a developmental clinical sample. Developmental Cognitive Neuroscience, 62, 101271. https://doi.org/10.1016/j.dcn.2023.101271