Differences in Performance of ASD and ADHD Subjects Facing Cognitive Loads in an Innovative Reasoning Experiment

Area of Science:

• Neuroscience
• Cognitive Science
• Biomedical Engineering

Background:

• Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are neurodevelopmental conditions with distinct cognitive and behavioral profiles.
• Understanding the underlying neural dynamics during cognitive tasks is crucial for differentiating these conditions and developing targeted interventions.
• Previous research has explored EEG differences in ASD and ADHD, but novel cognitive tasks and advanced analytical methods are needed to elucidate specific brain-behavior relationships.

Purpose of the Study:

• To investigate differences in EEG dynamics between adults with ASD, ADHD, and healthy controls during a cognitive task involving Aristotle's valid and invalid syllogisms.
• To correlate these EEG differences with specific brain regions and behavioral data using advanced analytical techniques.
• To explore the potential of multiscale entropy (MSE) and Partial Least Squares Correlation (PLSC) as tools for distinguishing between these groups.

Main Methods:

• Electroencephalography (EEG) was recorded from 14 scalp electrodes in 63 participants (21 ASD, 21 ADHD, 21 controls) performing a syllogism task.
• Multiscale Entropy (MSE) was computed to quantify EEG complexity across 14 brain regions.
• Behavior-Partial Least Squares Correlation (PLSC) and its variant -PLSC were used to analyze functional connectivity and correlate brain and behavioral measures.

Main Results:

• A significant interaction between brain region and group factor, and brain region and syllogism factor was observed.
• Significant differences in MSE (complexity) were found between ASD and ADHD groups, but not between these groups and controls.
• ASD participants showed increased brain region complexity when transitioning from valid to invalid syllogisms, unlike ADHD and control groups.

Conclusions:

• The type of syllogism (valid vs. invalid) significantly alters EEG complexity differently in ASD and ADHD individuals.
• Behavioral measures such as emotional state, confidence, and age significantly discriminate between ASD, ADHD, and control groups.
• Functional connectivity networks projected onto the Default Mode Network (DMN) showed significant structural changes distinguishing the three groups, suggesting potential diagnostic utility.