このたび英国グラスゴー大学のPeter Uhlhaas教授をお招きして、セミナーを下記のとおり開催いたします。
Uhlhaas教授は統合失調症などの精神疾患の脳メカニズム研究で世界的に有名な先生であり、今回のご講演ではMEGを用いた神経オシレーション研究に加えて、MRSを用いた興奮/抑制ニューロンバランスについての最新研究についてもご紹介いただきます。
どなたでもご参加いただけますので、興味をお持ちの研究者・学生の皆さまのご参加をお待ちしております。
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日時： 2020年1月22日(水) 16:00-17:30
場所： 京都大学 本部構内 総合研究8号館3階 講義室4（338号室）
（アクセスはこちら：地図中の59番の建物）
演題：
E/I-balance and gamma-band oscillations across illness-stages in Schizophrenia: Using Magnetoencephalography to identify circuit dysfunctions and biomarkers
講演者：
Prof. Peter Uhlhaas (University of Glasgow, UK)
要旨：
A considerable body of work over the last 10 years combining non-invasive electrophysiology (electroencephalography/magnetoencephalography) in patient populations with preclinical research has contributed to the conceptualization of schizophrenia as a disorder associated with aberrant neural dynamics and disturbances in excitation/inhibition (E/I) balance parameters.
Specifically, I will propose that recent technological and analytic advances in MEG provide novel opportunities to address these fundamental questions as well as establish important links with translational research.
We have carried out several studies which have tested the importance of neural oscillations in the pathophysiology of schizophrenia through a combination of MEG-measurements in ScZ-patients and pharmacological manipulations in healthy volunteers which target the NMDA-receptor.
These results highlight a pronounced impairment in high-frequency activity in both chronic and unmedicated patients which could provide novel insights into basic circuit mechanisms underlying cognitive and perceptual dysfunctions. However, acute Ketamine only partly recreates abnormalities observed in both resting-state and task-related neural oscillations in ScZ, suggesting potentially shortcoming of this pharmacological model for capturing large-scale network dysfunctions.
Our recent work has employed MEG to develop a biomarker for early detection and diagnosis of ScZ. We have obtained MEG- and MRS-data from 125 participants meeting clinical high-risk criteria (CHR), 90 controls and 30 FEP-patients. We found marked changes in the synchrony of gamma-band oscillations in visual and auditory cortices during sensory processing which predicted clinical outcomes. In addition, CHR-participants were characterized by elevated broad-band gamma-band activity at rest which correlated with increased glutamate levels.
Together, these findings highlight the potential of MEG-based biomarkers for the early diagnosis of ScZ in at-risk populations.