ADHD is a neurodevelopmental disorder affecting 3-4 of Canadian adults and 2.6% of adults worldwide. Its symptoms include inattention, hyperactivity and impulsivity. Tough ADHD is known to affect several brain functions and cognitive processes, little is known regarding its impact on perceptual oscillations. This study compared the temporal features of visual processing between ADHD and neurotypical individuals in a word recognition task. These features were sufficiently different across groups while at the same time sufficiently congruent across participants of the same group that a machine learning algorithm classified participants in their respective group with a 91.8% accuracy using only a small portion of the available features. Secondary findings showed that individuals with ADHD could be classified with high accuracy (91.3%) regarding their use of psychostimulant medication. These findings suggest the existence of a strong behavioral marker of ADHD as well as of regular medication usage on visual performance which can be uncovered by random temporal sampling.

The authors have declared no competing interest.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Comité d'éthique à la recherche en éducation et psychologie (CEREP) Université de Montréal CEREP-18-026-D Comité d'éthique à la recherche (CER) Collège Montmorency CÉR-2018-11

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The raw dataset in text format and relevant information will be made available on the Borealis repository (https://borealisdata.ca/fr/) upon publication.