Identification of attention-deficit hyperactivity disorder based on the complexity and symmetricity of pupil diameter

• Published in: Scientific reports Vol. 11; no. 1; p. 8439
• Main Authors: Nobukawa, Sou, Shirama, Aya, Takahashi, Tetsuya, Takeda, Toshinobu, Ohta, Haruhisa, Kikuchi, Mitsuru, Iwanami, Akira, Kato, Nobumasa, Toda, Shigenobu
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 19.04.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114; 631/378; 692/53; Adult; Adults; Arousal; Attention Deficit Disorder with Hyperactivity - diagnosis; Attention Deficit Disorder with Hyperactivity - physiopathology; Attention deficit hyperactivity disorder; Biomarkers; Data Interpretation, Statistical; Diagnosis; Entropy; Female; Humanities and Social Sciences; Humans; Hyperactivity; Male; Mental disorders; Middle Aged; multidisciplinary; Pupil; Science; Science (multidisciplinary); Young Adult
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-88191-x

Adult attention-deficit/hyperactivity disorder (ADHD) frequently leads to psychological/social dysfunction if unaddressed. Identifying a reliable biomarker would assist the diagnosis of adult ADHD and ensure that adults with ADHD receive treatment. Pupil diameter can reflect inherent neural activity and deficits of attention or arousal characteristic of ADHD. Furthermore, distinct profiles of the complexity and symmetricity of neural activity are associated with some psychiatric disorders. We hypothesized that analysing the relationship between the size, complexity of temporal patterns, and asymmetricity of pupil diameters will help characterize the nervous systems of adults with ADHD and that an identification method combining these features would ease the diagnosis of adult ADHD. To validate this hypothesis, we evaluated the resting state hippus in adult participants with or without ADHD by examining the pupil diameter and its temporal complexity using sample entropy and the asymmetricity of the left and right pupils using transfer entropy. We found that large pupil diameters and low temporal complexity and symmetry were associated with ADHD. Moreover, the combination of these factors by the classifier enhanced the accuracy of ADHD identification. These findings may contribute to the development of tools to diagnose adult ADHD.