People with schizophrenia exhibit impaired social cognitive functions, particularly emotion regulation. Abnormal activations of the ventral medial prefrontal cortex （vMPFC） during emotional tasks have been demonstra...People with schizophrenia exhibit impaired social cognitive functions, particularly emotion regulation. Abnormal activations of the ventral medial prefrontal cortex （vMPFC） during emotional tasks have been demonstrated in schizophrenia, suggesting its important role in emotion processing in patients. We used the resting-state functional connectivity approach, setting a functionally relevant region, the vMPFC, as a seed region to examine the intrinsic functional interactions and communication between the vMPFC and other brain regions in schizophrenic patients. We found hypo-connectivity between the vMPFC and the medial frontal cortex, right middle temporal lobe （MTL）, right hippocampus, parahippocampal cortex （PHC） and amygdala. Further, there was a decreased strength of the negative connectivity （or anticorrelation） between the vMPFC and the bilateral dorsal lateral prefrontal cortex （DLPFC） and pre-supplementary motor areas. Among these connectivity alterations, reduced vMPFC-DLPFC connectivity was positively correlated with positive symptoms on the Positive and Negative Syndrome Scale, while vMPFC-right MTL/PHC/amygdala functional connectivity was positively correlated with the performance of emotional regulation in patients. These findings imply that communication and coordination throughout the brain networks are disrupted in schizophrenia. The emotional correlates of vMPFC connectivity suggest a role of the hypo-connectivity between these regions in the neuropathology of abnormal social cognition in chronic schizophrenia.展开更多
Much like genomics, brain connectomics has rapidly become a core component of most national brain projects around the world. Beyond the ambitious aims of these projects, a fundamental challenge is the need for an effi...Much like genomics, brain connectomics has rapidly become a core component of most national brain projects around the world. Beyond the ambitious aims of these projects, a fundamental challenge is the need for an efficient, robust, reliable and easy-to-use pipeline to mine such large neuroscience datasets. Here, we introduce a computational pipeline--namely the Connectome Compu- tation System （CCS）-for discovery science of human brain connectomes at the macroscale with multimodal magnetic resonance imaging technologies. The CCS is designed with a three-level hierarchical structure that includes data cleaning and preprocessing, individual connectome mapping andconnectome mining, and knowledge discovery. Several functional modules are embedded into this hierarchy to implement quality control procedures, reliability analysis and connectome visualization. We demonstrate the utility of the CCS based upon a publicly available dataset, the NKI- Rockland Sample, to delineate the normative trajectories of well-known large-scale neural networks across the natural life span （6-85 years of age）. The CCS has been made freely available to the public via GitHub （https：//github.com/ zuoxinian/CCS） and our laboratory＇s Web site （http：//lfcd. psych.ac.cn/ccs.html） to facilitate progress in discovery science in the field of human brain connectomics.展开更多
基金supported by grants from the Beijing Municipal Science & Technology Commission(D0906001040191,D101107047810005,D101100050010051)the Beijing Natural Science Foundation(7102086)+3 种基金the Fund for Capital Medical Development and Research(2007-3059)the National Natural Science Foundation of China(81171409)Startup Foundation for Distinguished Research Professors of the Institute for Psychology(Y0CX492S03)Fund for Outstanding Talents in Beijing(2012D003034000003)
文摘People with schizophrenia exhibit impaired social cognitive functions, particularly emotion regulation. Abnormal activations of the ventral medial prefrontal cortex （vMPFC） during emotional tasks have been demonstrated in schizophrenia, suggesting its important role in emotion processing in patients. We used the resting-state functional connectivity approach, setting a functionally relevant region, the vMPFC, as a seed region to examine the intrinsic functional interactions and communication between the vMPFC and other brain regions in schizophrenic patients. We found hypo-connectivity between the vMPFC and the medial frontal cortex, right middle temporal lobe （MTL）, right hippocampus, parahippocampal cortex （PHC） and amygdala. Further, there was a decreased strength of the negative connectivity （or anticorrelation） between the vMPFC and the bilateral dorsal lateral prefrontal cortex （DLPFC） and pre-supplementary motor areas. Among these connectivity alterations, reduced vMPFC-DLPFC connectivity was positively correlated with positive symptoms on the Positive and Negative Syndrome Scale, while vMPFC-right MTL/PHC/amygdala functional connectivity was positively correlated with the performance of emotional regulation in patients. These findings imply that communication and coordination throughout the brain networks are disrupted in schizophrenia. The emotional correlates of vMPFC connectivity suggest a role of the hypo-connectivity between these regions in the neuropathology of abnormal social cognition in chronic schizophrenia.
基金partially supported by the National Basic Research Program (973) of China (2015CB351702)the National Natural Science Foundation of China (81220108014, 81471740, 81201153, 81171409, and 81270023)+4 种基金the Key Research Program (KSZD-EW-TZ-002)the Hundred Talents Program of the Chinese Academy of SciencesDr. Xiu-Xia Xing acknowledges the Beijing Higher Education Young Elite Teacher Project (No. YETP1593)Dr. Zhi Yang acknowledges the Foundation of Beijing Key Laboratory of Mental Disorders (2014JSJB03)the Outstanding Young Researcher Award from Institute of Psychology, Chinese Academy of Sciences (Y4CX062008)
文摘Much like genomics, brain connectomics has rapidly become a core component of most national brain projects around the world. Beyond the ambitious aims of these projects, a fundamental challenge is the need for an efficient, robust, reliable and easy-to-use pipeline to mine such large neuroscience datasets. Here, we introduce a computational pipeline--namely the Connectome Compu- tation System （CCS）-for discovery science of human brain connectomes at the macroscale with multimodal magnetic resonance imaging technologies. The CCS is designed with a three-level hierarchical structure that includes data cleaning and preprocessing, individual connectome mapping andconnectome mining, and knowledge discovery. Several functional modules are embedded into this hierarchy to implement quality control procedures, reliability analysis and connectome visualization. We demonstrate the utility of the CCS based upon a publicly available dataset, the NKI- Rockland Sample, to delineate the normative trajectories of well-known large-scale neural networks across the natural life span （6-85 years of age）. The CCS has been made freely available to the public via GitHub （https：//github.com/ zuoxinian/CCS） and our laboratory＇s Web site （http：//lfcd. psych.ac.cn/ccs.html） to facilitate progress in discovery science in the field of human brain connectomics.
