Poster #18 - Parsing Heterogeneity of Childhood Executive Function: A Latent Profile Analysis and Event-Related Potential (ERP) Study

• In Event: Poster Session 13

Abstract

Executive function (EF) is thought to be impaired in children with neurodevelopmental disorders (NDD), but recent data-driven work suggests EF may not fractionate by diagnosis and that, instead, EF reflects dimensional skill level with neural underpinnings across typical and atypical development. Two studies examining EF in children with typical development (TD) and autism spectrum disorder (ASD) have reported latent profile analyses (LPA) yielding differential proportions of children with ASD versus TD across all three EF levels (below average, average, and above average) (Baez et al., 2020; Dajani et al., 2016). This heterogeneity in EF ability calls into question longstanding theories from case-control designs about impaired EF in NDD. However, it remains unknown whether (1) three EF classes are identified from a wider range of NDD including ASD, attention-deficit hyperactivity disorder (ADHD), and co-occurring ASD+ADHD and (2) EF classes are more closely aligned with neural differences in the N2 event-related potential (ERP) component than diagnostic category. Children (N=186) aged 7-12 years-old with TD (n=76), ASD (n=42), ADHD (n=28), and co-occurring ASD+ADHD (n=40) completed two ERP tasks that assessed N2 amplitude and latency: the Attention Network Task (ANT) and the Go/No-Go Task (GnG). Four ERP variables derived from the electrophysiological data were analyzed (N2 amplitude and latency from ANT and GnG tasks). Parents completed the Behavior Rating Inventory of Executive Function (BRIEF), a questionnaire measuring real-world EF. First, LPA identified subgroups based on different patterns of EF ability as assessed by the BRIEF. We found a three latent class solution best fit the EF data (AIC=10752.71, BIC=10862.38) and reflected “above average” (class 1), “average” (class 2), and “below average” (class 3) EF latent groups (Figure 1). Proportions of diagnostic group differed by latent class (Figure 2): Class 1 (ADHD n=0, ASD n=1, ASD+ADHD n=0, TD n=23), Class 2 (ADHD n=8, ASD n=29, ASD+ADHD n=10, TD n=48), and Class 3 (ADHD n=20, ASD n=12, ASD+ADHD n=30, TD n=5). Second, ANCOVAs showed EF profile was associated with N2 amplitude on the ANT (p=.008, F=7.3), while diagnosis was not associated with N2 amplitude or latency on either the ANT or GnG tasks. Based on the proportions of diagnosis assigned to each EF group, the link between diagnosis and EF ability appears weak. Though prior literature suggests children with ASD, ADHD, and ADHD+ASD would be below average and children with TD would be above average in their EF ability, our results suggest instead that TD, ASD, ADHD, and ASD+ADHD are distributed across average and below average classes. The significant proportion of children with ASD, ADHD, or ASD+ADHD (49.47%) in the “average” EF class supports the idea that EF ability does not fractionate by diagnosis, which contradicts the longstanding theory from case-control designs that diagnosis predicts atypical EF development. Taken together, the present study uses behavioral and neural measures of EF to suggest that EF does not always fractionate by diagnosis and, instead, that data-driven modeling and conceptualization of EF as a dimensional construct may best elucidate heterogeneity in EF development among children.

Authors

• Melody Rose Altschuler, University of Minnesota - Twin Cities
  Presenting Author

• Tessa Clarkson

• Gabrielle MacNaughton, University of California - Los Angeles

• Julia I Nikolaeva, Northwestern University

• Laura Nelson Darling

• Susan Faja, Boston Children's Hospital