# Differences in Executive Functioning Performance and Cortical Activation Between Autistic and Non-Autistic Youth During an fNIRS Flanker Task: A Pilot Study

## TL;DR

This pilot study explores how autistic and non-autistic youth differ in brain activation and reaction time during a task measuring executive functioning.

## Contribution

The study identifies unique neural activation patterns in autistic youth during executive functioning tasks using fNIRS.

## Key findings

- Autistic youth showed greater reaction time variability and higher BRIEF scores, indicating EF challenges.
- Autistic youth exhibited lower left IPL activation and non-lateralized brain activity during the task.
- Right-hemispheric activation in autistic youth correlated with better EF performance, suggesting compensation.

## Abstract

Background/Objectives: Autism spectrum disorder is associated with executive functioning (EF) challenges, yet the neural correlates of EF challenges in autistic youth remain unclear. This study aimed to examine EF performance and cortical activation in autistic versus non-autistic youth, using functional near-infrared spectroscopy (fNIRS) during a modified Flanker task. Methods: Thirty age-matched (11.6 ± 0.8 years) autistic (N = 15) and non-autistic youth (N = 15) completed congruent and incongruent conditions of a modified Flanker task while cortical activation in prefrontal, parietal, and temporal regions was recorded using fNIRS. The Behavior Rating Inventory of Executive Function (BRIEF) was used to assess general EF impairments. Behavioral data (i.e., Flanker task mean reaction time/accuracy, and reaction time variability) and cortical activation were analyzed using ANCOVAs. Pearson correlations were used to determine the relationship between cortical activation, EF performance, and clinical measures. The significance level was set at p < 0.05, with FDR corrections for multiple comparisons. Results: While mean reaction time and accuracy were comparable across groups, autistic youth exhibited greater reaction time variability (autistic youth = 34.8 ± 10.36; controls = 26.4 ± 1.94, p = 0.02, Hedges’ g = 0.85) and higher BRIEF index scores compared to controls (ps < 0.001, Hedges’ gs > 1.3; e.g., Global Executive Composite Score for autistic youth = 71.3 ± 3.7; controls = 47.8 ± 2.4), indicative of delayed EF development. During the incongruent condition, compared to non-autistic controls, autistic youth showed lower left inferior parietal lobe (IPL) activation (Mean HbO2 in autistic youth = −0.02 ± 0.006 mmol.mm; controls = 0.01 ± 0.006 mmol.mm, ps < 0.001, Hedges’ g = 0.5) and a lack of left-lateralized activation (e.g., left vs. right STS activation, p < 0.001, Hedges’ g = 0.41 in the non-autistic youth). In the ASD group, lower activation in the left STS was associated with lower EF performance (r = −0.28, p = 0.007), whereas greater activation in various right-hemispheric ROIs was associated with better EF performance (r = −0.31 to −0.35, ps < 0.005), suggesting potential compensatory activation. Conclusions: The findings revealed ASD-specific differences in the neural correlates of EF performance and possible alternative compensatory activation patterns. These potential neural correlates of EF performance highlight the utility of fNIRS-based neural measures to better understand the neural bases of EF differences in autism. Study Registration: This study was approved by the Institutional Review Board (IRB) at the University of Delaware (Protocol #: 1947455) on 4 October 2022.