Increased intra-individual reaction time variability in attention-deficit/hyperactivity disorder across response inhibition tasks with different cognitive demands

This study investigates the nature of intra-individual reaction time variability (ISV) in children with ADHD. While increased ISV is a consistent behavioral marker of ADHD, it remains unclear whether this variability is a stable trait or if it fluctuates based on task difficulty. The researchers compared 57 children with ADHD and 83 typically developing controls using two Go/No-go tasks: a simple version with minimal cognitive load and a complex version requiring working memory to guide inhibitory responses. The authors employed ex-Gaussian distribution modeling—which separates reaction times into normal (Gaussian) and infrequent slow (exponential) components—and Fast Fourier Transform (FFT) to analyze the periodicity of these responses.

Children with ADHD demonstrated significantly higher ISV than controls across both tasks. Ex-Gaussian analysis revealed that this variability was not limited to occasional 'lapses in attention' (the exponential 'tau' component) but also involved the normal 'sigma' component, indicating broader inefficiencies in response preparation. Notably, this increased variability was robust and did not worsen significantly with the added cognitive load of the complex task. FFT analysis further showed that the periodicity of these attention lapses is task-dependent; children with ADHD exhibited a specific pattern of increased power in the 0.027–0.074 Hz frequency band during the simple task, suggesting a predictable, intermittent inefficiency in neural processing.

The findings suggest that increased ISV is a stable, core feature of ADHD that reflects fundamental deficits in neural mechanisms for response preparation, rather than just a failure of executive control under high demand. By demonstrating that this variability persists across different cognitive contexts, the study supports the use of ISV as a reliable intermediate endophenotype for ADHD. This provides a clearer target for future genetic and neurobiological research, moving beyond simple error rates to understand the underlying temporal dynamics of the disorder.