精神分裂症认知功能障碍的脑网络组研究(英文)

Impaired cognitive function,along with positive and negative symptoms,is a core clinical feature of schizophrenia.Earlier studies suggest that impaired cognitive functioning should be assessed from the perspective of brain networks.The recently developed brainnetome approach to evaluating brain networks-an approach that was initially developed by Chinese scientists-provides a new methodology for studying this issue.In this paper we first introduce the concept of brainnetome.We then review recent progress in developing a brainnetome of impaired cognitive function in people with schizophrenia.The models of the relevant brain networks considered were created using data obtained from functional and anatomical brain imaging technologies at different levels of analysis:networks centered on regions of interest,networks related to specific cognitive functions,whole brain networks,and the attributes of brain networks.Finally,we discuss the current challenges and potential new directions for research about brainnetome.

A review of functional magnetic resonance imaging for Brainnetome

The functional brain network using blood-oxygen-level-dependent（BOLD） functional magnetic resonance imaging（fMRI） has revealed the potentials for probing brain architecture,as well as for identifying clinical biomarkers for brain diseases.In the general context of Brainnetome,this review focuses on the development of approaches for modeling and analyzing functional brain networks with BOLD fMRI.The prospects for these approaches are also discussed.

The long rather than the short allele of 5-HTTLPR predisposes Han Chinese to anxiety and reduced connectivity between prefrontal cortex and amygdala

The short allele of the serotonin-transporter gene is associated with higher risk for anxiety and depression in Caucasians, but this association is still unclear in Asians. Here, we addressed this issue using behavioral and multi-modal MRI approaches in a large group of healthy Han Chinese participants （n = 233）. In contrast to findings in Caucasians, we found that long-allele （L） carriers had higher anxiety scores. In another group （n = 64） experiencing significant levels of depression or anxiety, the L-allele frequency was also significantly higher. In healthy participants, L-carriers had reduced functional and anatomical connectivity between the amygdala and prefrontal cortex （PFC）, which was correlated with anxiety or depression scores. Our findings demonstrated that in Chinese Han participants, in contrast to Caucasians, the L-allele confers vulnerability to anxiety or depression and weakens top-down emotional control between the PFC and amygdala. Therefore, ethnic background should be taken into account in gene-related studies and their potential clinical applications.

Abnormal Degree Centrality of Bilateral Putamen and Left Superior Frontal Gyrus in Schizophrenia with Auditory Hallucinations： A Resting-state Functional Magnetic Resonance Imaging Study

Background： Dysconnectivity hypothesis of schizophrenia has been increasingly emphasized. Recent researches showed that this dysconnectivity might be related to occurrence of auditory hallucination （AH）. However, there is still no consistent conclusion. This study aimed to explore intrinsic dysconnectivity pattern of whole-brain functional networks at voxel level in schizophrenic with AH. Methods： Auditory hallucinated patients group （n = 42 APG）, no hallucinated patients group （n = 42 NPG） and normal controls （n = 84 NCs） were analyzed by resting-state functional magnetic resonance imaging. The functional connectivity metrics index （degree centrality [DC]） across the entire brain networks was calculated and evaluated among three groups. Results： DC decreased in the bilateral putamen and increased in the left superior frontal gyrus in all the patients. However, in APG. the changes of DC were more obvious compared with NPG. Symptomology scores were negatively correlated with the DC of bilateral putamen in all patients. AH score of APG positively correlated with the DC in left superior frontal gyrus but negatively correlated with the DC in bilateral putamen. Conclusion： Our findings corroborated that schizophrenia was characterized by functional dysconnectivity, and the abnormal DC in bilateral putamen and left superior frontal gyrus might be crucial in the occurrence of AH.

Compromised small-world efficiency of structural brain networks in schizophrenic patients and their unaffected parents

Several lines of evidence suggest that efficient information integration between brain regions is disrupted in schizophrenia. Abnormalities in white matter tracts that interconnect brain regions may be directly relevant to this pathophysiological process. As a complex mental disorder with high heritability, mapping abnormalities in patients and their first- degree relatives may help to disentangle the risk factors for schizophrenia. We established a weighted network model of white matter connections using diffusion tensor imaging in 25 nuclear families with schizophrenic probands （19 patients and 41 unaffected parents） and two unrelated groups of normal controls （24 controls matched with patients and 26 controls matched with relatives）. The patient group showed lower global efficiency and local efficiency. The decreased regional efficiency was localized in hubs such as the bilateral frontal cortices, bilateral anterior cingulate cortices, and left precuneus. The global efficiency was negatively correlated with cognition scores derived from a 5-factor model of schizophrenic psychopathology.We also found that unaffected parents displayed decreased regional efficiency in the right temporal cortices, left supplementary motor area, left superior temporal pole, and left thalamus. The global efficiency tended to be lower in unaffected parents. Our data suggest that （1） the global efficiency loss in neuroanatomical networks may be associated with the cognitive disturbances in schizophrenia; and （2） genetic vulnerability to schizophrenia may influence the anatomical organization of an individual＇s brain networks.

Feature-reduction and semi-simulated data in functional connectivity-based cortical parcellation

Recently, restingstate functional magnetic resonance imaging has been used to parcellate the brain into functionally distinct regions based on the information available in functional connectivity maps. However, brain voxels are not independent units and adjacent voxels are always highly correlated, so functional connectivity maps contain redundant information, which not only impairs the computational efficiency during clustering, but also reduces the accuracy of clustering results. The aim of this study was to propose featurereduction approaches to reduce the redundancy and to develop semisimulated data with defined ground truth to evaluate these approaches. We proposed a featurereduction approach based on the Affinity Propagation Algorithm （APA） and compared it with the classic feature reduction approach based on Principal Component Analysis （PCA）. We tested the two approaches to the parcellation of both semisimulated and real seed regions using the Kmeans algorithm and designed two experiments to evaluate their noise resistance. We found that all functional connectivitymaps （with/without feature reduction） provided correct information for the parcellation of the semi simulated seed region and the computational efficiency was greatly improved by both feature reduction approaches. Meanwhile, the APAbased featurereduction approach outperformed the PCA based approach in noiseresistance. The results suggested that functional connectivity maps can provide correct information for cortical parcellation, and featurereduction does not significantly change the information. Considering the improvement in computational efficiency and the noiseresistance, featurereduction of functional connectivity maps before cortical parcellation is both feasible and necessary.