Majority of type 2 diabetes mellitus(T2DM)patients are highly susceptible to several forms of cognitive impairments,particularly dementia.However,the underlying neural mechanism of these cognitive impairments remains ...Majority of type 2 diabetes mellitus(T2DM)patients are highly susceptible to several forms of cognitive impairments,particularly dementia.However,the underlying neural mechanism of these cognitive impairments remains unclear.We aimed to investigate the correlation between whole brain resting state functional connections(RSFCs)and the cognitive status in 95 patients with T2DM.We constructed an elastic net model to estimate the Montreal Cognitive Assessment(MoCA)scores,which served as an index of the cognitive status of the patients,and to select the RSFCs for further prediction.Subsequently,we utilized a machine learning technique to evaluate the discriminative ability of the connectivity pattern associated with the selected RSFCs.The estimated and chronological MoCA scores were significantly correlated with R=0.81 and the mean absolute error(MAE)=1.20.Additionally,cognitive impairments of patients with T2DM can be identified using the RSFC pattern with classification accuracy of 90.54%and the area under the receiver operating characteristic(ROC)curve(AUC)of 0.9737.This connectivity pattern not only included the connections between regions within the default mode network(DMN),but also the functional connectivity between the task-positive networks and the DMN,as well as those within the task-positive networks.The results suggest that an RSFC pattern could be regarded as a potential biomarker to identify the cognitive status of patients with T2DM.展开更多
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
基金supported by the National Natural Science Foundation of China(Grant Nos.81772012,81227901,61673051,81641168,31470047,81271565,81527805,and61231004)the National Key R&D Program of China(Grant No.2017YFA0205200)the Youth Innovation Promotion Association,Chinese Academy of Sciences(Grant No.2019136)
文摘Majority of type 2 diabetes mellitus(T2DM)patients are highly susceptible to several forms of cognitive impairments,particularly dementia.However,the underlying neural mechanism of these cognitive impairments remains unclear.We aimed to investigate the correlation between whole brain resting state functional connections(RSFCs)and the cognitive status in 95 patients with T2DM.We constructed an elastic net model to estimate the Montreal Cognitive Assessment(MoCA)scores,which served as an index of the cognitive status of the patients,and to select the RSFCs for further prediction.Subsequently,we utilized a machine learning technique to evaluate the discriminative ability of the connectivity pattern associated with the selected RSFCs.The estimated and chronological MoCA scores were significantly correlated with R=0.81 and the mean absolute error(MAE)=1.20.Additionally,cognitive impairments of patients with T2DM can be identified using the RSFC pattern with classification accuracy of 90.54%and the area under the receiver operating characteristic(ROC)curve(AUC)of 0.9737.This connectivity pattern not only included the connections between regions within the default mode network(DMN),but also the functional connectivity between the task-positive networks and the DMN,as well as those within the task-positive networks.The results suggest that an RSFC pattern could be regarded as a potential biomarker to identify the cognitive status of patients with T2DM.
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.
