A study of neural network alterations in autism using nonlinear neuroimaging approach

2015 Fiscal Year Final Research Report

• Project/Area Number: 25461755
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Psychiatric science
• Research Institution: Kanazawa University (2014-2015); University of Fukui (2013)
• Principal Investigator: Takahashi Tetsuya 金沢大学, 子どものこころの発達研究センター, 准教授 (00377459)
• Co-Investigator(Kenkyū-buntansha): Kawatani Masao 福井大学, 医学部付属病院, 講師 (10362047) ; Ueno Kanji 福井大学, 医学部付属病院, 医員 (50600152) ; Okazaki Ryoko 福井大学, 医学部付属病院, 医員 (90647778)
• Co-Investigator(Renkei-kenkyūsha): Ishitobi Makoto 国立精神神経センター, 室長 (50464053)
• Project Period (FY): 2013-04-01 – 2016-03-31
• Keywords: 自閉性障害 / 神経ネットワーク / 脳波・脳磁図 / 非線形理論 / グラフ理論

Outline of Final Research Achievements

Aberrant neural network lies at the heart of autism spectrum disorders (ASD). Nonlinear theory and graph theory approaches to EEG and MEG data have provided a useful framework to study functional neural networks architecture. Regarding these two theories, we aimed to characterize the neural network alterations in ASD.
Results suggested that evaluation of EEG complexity offers a useful therapeutic assessment of ASD (Okazaki et al., 2015). Additionally, enhanced brain development (MEG signal variability) (Takahashi et al., 2016) and hyper-efficiency (higher small-worldness) (Takahashi et al., Submitted) were observed in children with ASD.

Free Research Field

精神医学