Shared and Distinct Patterns of Functional Connectivity to Emotional Faces in Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder Children

Abstract

Impairments in emotional face processing are demonstrated by individuals with neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), which is associated with altered emotion processing networks. Despite accumulating evidence of high rates of diagnostic overlap and shared symptoms between ASD and ADHD, functional connectivity underpinning emotion processing across these two neurodevelopmental disorders, compared to typical developing peers, has rarely been examined. The current study used magnetoencephalography to investigate whole-brain functional connectivity during the presentation of happy and angry faces in 258 children (5–19 years), including ASD, ADHD and typically developing (TD) groups to determine possible differences in emotion processing. Data-driven clustering was also applied to determine whether the patterns of connectivity differed among diagnostic groups. We found reduced functional connectivity in the beta band in ASD compared to TD, and a further reduction in the ADHD group compared to the ASD and the TD groups, across emotions. A group-by-emotion interaction in the gamma frequency band was also observed. Greater connectivity to happy compared to angry faces was found in the ADHD and TD groups, while the opposite pattern was seen in ASD. Data-driven subgrouping identified two distinct subgroups: NDD-dominant and TD-dominant; these subgroups demonstrated emotion- and frequency-specific differences in connectivity. Atypicalities in specific brain networks were strongly correlated with the severity of diagnosis-specific symptoms. Functional connectivity strength in the beta network was negatively correlated with difficulties in attention; in the gamma network, functional connectivity strength to happy faces was positively correlated with adaptive behavioural functioning, but in contrast, negatively correlated to angry faces. Our findings establish atypical frequency- and emotion-specific patterns of functional connectivity between NDD and TD children. Data-driven clustering further highlights a high degree of comorbidity and symptom overlap between the ASD and ADHD children.

Identifying Replicable Subgroups in Neurodevelopmental Conditions Using Resting-State Functional Magnetic Resonance Imaging Data

“…With a mounting body of work challenging the reproducibility of brain-behavior relations and brain-based subtyping, replicating clustering results is essential to establish the robustness necessary to translate the groupings to clinical settings, particularly given the heterogeneity in both brain and behavior in neurodevelopmental conditions. While previous studies have established transdiagnostic subgroupings using neuroimaging, these results should be interpreted cautiously in the absence of replication. We explicitly address their shortcomings by evaluating subgroup replicability in 2 independent data sets.…”

“…To this end, several studies have used measures of brain function or structure to identify transdiagnostic subgroups of neurodevelopmental conditions, consistently demonstrating a misalignment between data-driven groupings and existing diagnostic categories. 9,10,12,27,28,[30][31][32] The first contribution of this article is to characterize the heterogeneity across neurodevelopmental conditions by identifying cross-diagnosis subgroups of children and adolescents with and without neurodevelopmental conditions using measures of integration and segregation of the functional connectome.…”

Delineating Transdiagnostic Subtypes in Neurodevelopmental Disorders via Contrastive Graph Machine Learning of Brain Connectivity Patterns

“…We also observed a subtype distinction on the Child Behaviour Checklist attention problems subscale (CBCL_6-18) where subtype 2 presented fewer anomalies than subtype 1. A similar study 63 conducted subtyping on a comorbid group of ADHD and ASD patients and found that healthy controls exhibited fewer attention problems relative to both diseases. No discernible difference was detected between the two diagnostic groups, lending further weight to the notion of shared patterns across these disorders.…”

Atypical oscillatory dynamics during emotional face processing in paediatric obsessive–compulsive disorder with MEG

“…For statistical analyses, a latency window of 200 to 400 ms following stimulus onset (i.e., active window) was chosen. The latency window was motivated based on previous research demonstrating between-group differences in functional connectivity during implicit emotion processing in individuals with NDDs compared to typical controls during this latency period ( Mennella et al, 2017 , Safar et al, 2022 , Safar et al, 2021 ). The relative change from baseline (-200 to 0 ms) was computed for the PLI values at each timepoint within the active window and then averaged.…”