报告人简介：张栌博士现为上海复旦大学类脑智能科学与技术研究院的博士后。张栌博士2012年毕业于华东师范大学脑功能基因组学重点实验室和德国哥廷根大学认知神经实验室的联合培养博士项目，其后在法国巴黎的皮埃尔和玛丽居里大学Cerebellum Navigation and Memory实验室做博后，2015年回国在复旦工作，目前承担中国人脑连接组计划（Human Connectome Project）中共享的精神疾病相关数据的数据挖掘、建模等工作。张博士擅长认知神经科学领域的多种数据处理和编程技术，尤其是目前国际热门的机器学习方法。张栌博士的主要研究方向为：神经科学和精神疾病的信号分析；使用机器学习理论对生物和精神疾病数据进行建模和分析（PCA, community clustering, 贝叶斯网络等）；精神分裂症、睡眠和情绪研究。
题目：Causal analysis of brain-wide dysconnectivity in Schizophrenia patients identifies the frontal cortex as the primary source
摘要：Schizophrenia is characterized by widespread dysconnection in neural circuitry across many brain regions which contributes to its complex and often severe behavioral symptoms. A key unresolved question is whether these extensive neural changes are driven by specific core regions or occur independently. In this study, we first carried out a whole brain meta-analysis of resting-state functional magnetic resonance imaging (rs-fMRI) data including 469 schizophrenia (SZ) patients and 512 healthy controls. We identified 117 altered (p < 0.001) functional connections (FC), primarily involving the cerebellum, thalamus, motor cortex and frontal cortex and these were clustered by covariation analysis into four community-based groups. Principal component analysis identified the most influential networks in each community. Bayesian network analysis then revealed two frontal-based cortical networks as the primary drivers with a medial frontal network linked to thalamus, motor cortex and cerebellum strongly associated with negative symptom severity (p <0.01) and an inferior frontal gyrus-medial temporal gyrus-based network strongly associated with positive symptom severity (p < 0.01). The former involved cognitive and emotional control centers and their links with sensorimotor processing, and the latter involved primarily language processing networks. Overall we suggest that the kinds of causal approach we have used here to elucidate the key neural circuitry which contribute to the wide-ranging and complex changes which occur in the schizophrenic brain offer a promising basis upon which to target future therapeutic intervention. Such approach could be furtherly applied to other psychiatric studies.