一般口演（Oral）

Oral Autism & schizophrenia: neuroimaging 一般口演自閉症・統合失調症のニューロイメージング

7月28日（日）8:45～9:00　第10会場（万代島ビル　6F　会議室） 4O-10m1-1 Data-driven Subtype Discovery in Autism Spectrum Disorder using Human Resting-State Connectivity Amanda Buch（Buch Amanda），Conor Liston（Liston Conor） Weill Cornell Med, Cornell Univ, New York, USA Biomarkers have transformed our approach to diagnosing and managing a host of medical conditions, but they remain relatively elusive in psychiatry, due in part to the weak correspondence between diagnostic categories and their neurobiological substrates. This is especially true for autism spectrum disorder (ASD), a heterogeneous neurodevelopmental disorder that afflicts 1% of the world population, and whose core pathologies include deficits in social interaction, repetitive behaviors, and restricted interests, often accompanied by intellectual disability. Importantly, ASD is not a unitary disease entity and is likely linked to pathological functional connectivity distributed across brain networks. There is a weak correspondence between the ASD diagnosis and its biological substrates, which are not the same in all patients. Parsing ASD into subgroups that correspond to underlying neurobiological substrates has been a longstanding interest, but most studies have been limited to small and homogenous patient datasets, do not use a data-driven approach, and do not incorporate measures of intrinsic brain function. Converging evidence from task-based and resting state neuroimaging studies reveal that atypical functional connectivity are linked to ASD-associated behaviors such as social language ability, adaptive learning, and social cognition capacities. Here we leverage resting state fMRI measures from a large cohort of ASD and healthy individuals to develop a data-driven, computational diagnostic framework that stratifies ASD into clinically meaningful subtypes that have future potential to predict therapeutic responses to current and emerging treatment approaches. Our results underscore the potential for rsfMRI to advance our understanding of diagnostic heterogeneity in autism by defining one approach to identifying novel, neurophysiological subtypes.		7月28日（日）9:00～9:15　第10会場（万代島ビル　6F　会議室） 4O-10m1-2 自閉症の神経活動時間スケール Takamitsu Watanabe（渡部喬光）^1,2，Geraint Rees（Rees Geraint）²，Naoki Masuda（増田直紀）³ ¹理研CBS 高次認知機能動態 ²UCL Institute of Cognitive Neuroscience, London, UK ³University of Bristol, Bristol, UK Intrinsic neural timescale, or temporal receptive window, is considered to represent how long neural information is stored in a local brain area and known to be closely related to a wide range of cognitive activities including memory encoding, decision making, and stable perception. Its diversity is also thought to be an essential basis of functional hierarchy in the brains. Here, we investigated this fundamental property of local neural processing in autism by estimating the autocorrelation strength of intrinsic neural signals recorded from high-functioning adults with autism. First, we verified this analysis method using simultaneously-recorded EEG and fMRI datasets. Second, by applying it to resting-state fMRI datasets in a voxel-wise manner, we found atypically shorten neural timescales in the primary sensory and visual areas and an atypical increase in the caudate. These atypical neural timescales were significantly correlated with the severity of the symptoms of autism, and also seen during adolescence. Moreover, we identified these atypical local brain dynamics are supported by atypical local neuroanatomical structures evaluated by grey matter volume. Furthermore, we could reproduce these results in two independent datasets. The current findings suggest that functional and structural properties in local brain areas could have a critical influence on higher-order cognitive symptoms in autism and may provide a new perspective for the comprehensive biological understanding of the variety of autistic behaviours.

7月28日（日）9:30～9:45　第10会場（万代島ビル　6F　会議室） 4O-10m1-4 新規AMPA受容体標識PETプローブを用いた統合失調症患者の特性の検討 Waki Nakajima（中島和希）¹，Tomoyuki Miyazaki（宮崎智之）¹，Mai Hatano（波多野真依）¹，Yusuke Shibata（柴田裕介）¹，Tetsu Arisawa（有澤哲）¹，Susumu Jistuki（實木亨）¹，Yuichi Kimura（木村裕一）²，Hiroyuki Uchida（内田裕之）³，Takuya Takahashi（高橋琢哉）¹ ¹横浜市立大学医学部生理学 ²近畿大学生物理工学部システム生命科学科 ³慶應義塾大学医学部精神・神経科学教室 The glutamate α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) is one of the most important molecules controlling the neuronal activities. Dysfunction of AMPARs is believed to underlie some of neuropsychiatric disorders in animals and human (Gibbons et al., 2012, Duric et al., 2013). However, we are not currently able to visualize AMPAR in the living human brain. We developed a novel positron emission tomography (PET) tracer ([C11] K-2) for AMPAR. We imaged animals and human using [C11] K-2 PET and demonstrated that [C11] K-2 specifically bound to AMPARs. In this study, we investigated patients with schizophrenia using [C11] K-2 PET. In order to observe relative regional alteration of [11C] K-2 PET signal, we prepared the SUVR30-50 min images with the whole brain as a reference. The SUVR30-50 min image showed focal decrease of AMPARs in the limbic lobe in patients with schizophrenia. Voxel based analysis with statistical parametric mapping (SPM) exhibited a significant strong negative correlation (P<0.01) between the SUVR30-50 min of [11C]K-2 in the brain regions such as cingulate gyrus, left para-hippocampal gyrus, right hippocampus, right temporal pole, supplementary motor area and cuneus and the Positive and Negative Syndrome Scale (PANSS) total scores. We also detected a significant negative correlation between the SUVR30-50 min of [11C] K-2 PET scan in cingulate gyrus, para-hippocampal gyrus and PANSS positive scores. Further, we found no brain regions exhibiting the change of volume in significant correlation with PANSS total score. These finding indicated that the alteration of volume did not affect the [11C]K-2 PET signals. Thus, a novel PET tracer for AMPARs has a potential to elucidate molecular mechanism of schizophrenia.