2022 Fiscal Year Final Research Report

Investigating the neural mechanisms underlying neurodevelopmental disorder-related panic state using event-related potential and pupillometry

Research Project

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Project/Area Number	20K07928
Research Category	Grant-in-Aid for Scientific Research (C)
Allocation Type	Multi-year Fund
Section	一般
Review Section	Basic Section 52030:Psychiatry-related
Research Institution	Showa University
Principal Investigator	Toda Shigenobu 昭和大学, 医学部, 准教授 (00323006)
Co-Investigator(Kenkyū-buntansha)	高橋哲也金沢大学, 子どものこころの発達研究センター, 協力研究員 (00377459) 白間綾国立研究開発法人国立精神・神経医療研究センター, 精神保健研究所児童・予防精神医学研究部, 室長 (50738127) 信川創千葉工業大学, 情報科学部, 教授 (70724558) 住吉太幹国立研究開発法人国立精神・神経医療研究センター, 精神保健研究所児童・予防精神医学研究部, 部長 (80286062)
Project Period (FY)	2020-04-01 – 2023-03-31
Keywords	ADHD / pupillometry / attention / eye blink / noradrenaline / nonliner analysis
Outline of Final Research Achievements	Unfortunately, the recent covid-19 pandemic severely hampered our original research plan. Alternatively, we compared the sizes of pupils between typically developed (TD) and the patients with ADHD in adults during an attention-requiring continuous performance task. As a result, we demonstrated a significant increase in tonic and a significant decrease in phasic components of pupil size and have published these results. Next, we proved that the combination of tonic pupil size, the sample entropy of pupil size, and the transfer entropy that represents the difference between right- and left-pupil sizes was highly beneficial to diagnose ADHD using a machine learning algorism precisely. Based on the results, we applied for a patent and published an article. Finally, we confirmed that the pupil sizes on the left and the sample entropy of the right-left difference in the pupil sizes were significantly different in ADHD compared to TD, and, we have published a report about these findings.
Free Research Field	精神医学
Academic Significance and Societal Importance of the Research Achievements	ADHDの症状に関する教育が進んだ結果、患者数は増加の一途を辿っている。一方、同障害の簡便な診断は未だに困難で、専門的知識と十分な経験を要する。また、その病態はよくわかっていない。本研究では瞳孔径の発火頻度がノルアドレナリン神経核の発火頻度と同期する原理を利用し、pupillometryを用いて、成人ADHDと定型発達者の瞳孔径変動の違いを世界で初めて明らかにした。さらに瞳孔径変動の非線形的性質に着目し、複雑系解析の指標を用いることで、同障害の機械学習的診断の精度が大きく向上することを示し、実用化を目指して特許申請を行った。瞬目活動からも病態生理に迫りつつあり、将来の応用発展が期待される。