Cortico-amygdalar connectivity and externalizing/internalizing behavior in children with neurodevelopmental disorders

Abstract

Background Externalizing and internalizing behaviors contribute to clinical impairment in children with neurodevelopmental disorders (NDDs). Although associations between externalizing or internalizing behaviors and cortico-amygdalar connectivity have been found in clinical and non-clinical pediatric samples, no previous study has examined whether similar shared associations are present across children with different NDDs. Methods Multi-modal neuroimaging and behavioral data from the Province of Ontario Neurodevelopmental Disorders (POND) Network were used. POND participants aged 6–18 years with a primary diagnosis of autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) or obsessive–compulsive disorder (OCD), as well as typically developing children (TDC) with T1-weighted, resting-state fMRI or diffusion weighted imaging (DWI) and parent-report Child Behavioral Checklist (CBCL) data available, were analyzed (total n = 346). Associations between externalizing or internalizing behavior and cortico-amygdalar structural and functional connectivity indices were examined using linear regressions, controlling for age, gender, and image-modality specific covariates. Behavior-by-diagnosis interaction effects were also examined. Results No significant linear associations (or diagnosis-by-behavior interaction effects) were found between CBCL-measured externalizing or internalizing behaviors and any of the connectivity indices examined. Post-hoc bootstrapping analyses indicated stability and reliability of these null results. Conclusions The current study provides evidence towards an absence of a shared linear relationship between internalizing or externalizing behaviors and cortico-amygdalar connectivity properties across a transdiagnostic sample of children with different primary NDD diagnoses and TDC. Different methodological approaches, including incorporation of multi-dimensional behavioral data (e.g., task-based fMRI) or clustering approaches may be needed to clarify complex brain-behavior relationships relevant to externalizing/internalizing behaviors in heterogeneous clinical NDD populations.

Comparing the stability and reproducibility of brain-behavior relationships found using canonical correlation analysis and partial least squares within the ABCD sample

“…Studies that systematically compare different statistical approaches can help guide decisions around which approaches are most suitable for identifying stable and reproducible brain-behavior associations. Recent research has noted several advantages of multivariate approaches over univariate approaches ( Marek et al, 2022 ; Masouleh et al, 2019 ) likely due to the limited power and sensitivity of univariate methods when applied to complex brain-behavior data ( Mardia et al, 1979 ; McIntosh, 2021 ; Nakua et al, 2022 ).…”

Comparing the stability and reproducibility of brain-behaviour relationships found using Canonical Correlation Analysis and Partial Least Squares within the ABCD Sample

“…However, substantial methodological challenges remain, necessitating studies that can guide decisions around which statistical approaches are most suitable for identifying stable and reproducible brain-behaviour associations across studies. Brain-behaviour relationships have been often explored using univariate statistical approaches that assess one dependent variable per model, despite the limited power and sensitivity of this method when applied to complex brain-behaviour data (McIntosh, 2021; Mardia et al, 1979; Nakua et al, 2022). In contrast, multivariate approaches can examine relationships between several independent and dependent variables in a single analysis without requiring multiple comparison corrections, providing greater power to detect relationships between two variable sets (McIntosh, 2021; Marek et al, 2020).…”