Altered longitudinal trajectory of default mode network connectivity in healthy youth with subclinical depressive and posttraumatic stress symptoms

The default mode network (DMN) plays a crucial role in internal self-processing, rumination, and social functions. Disruptions to DMN connectivity have been linked with early adversity and the emergence of psychopathology in adolescence and early adulthood. Herein, we investigate how subclinical psychiatric symptoms can impact DMN functional connectivity during the pubertal transition. Resting-state fMRI data were collected annually from 190 typically-developing youth (9–15 years-old) at three timepoints and within-network DMN connectivity was computed. We used latent growth curve modeling to determine how self-reported depressive and posttraumatic stress symptoms predicted rates of change in DMN connectivity over the three-year period. In the baseline model without predictors, we found no systematic changes in DMN connectivity over time. However, significant modulation emerged after adding psychopathology predictors; greater depressive symptomatology was associated with significant decreases in connectivity over time, whereas posttraumatic stress symptoms were associated with significant increases in connectivity over time. Follow-up analyses revealed that these effects were driven by connectivity changes involving the dorsal medial prefrontal cortex subnetwork. In conclusion, these data suggest that subclinical depressive and posttraumatic symptoms alter the trajectory of DMN connectivity, which may indicate that this network is a nexus of clinical significance in mental health disorders.     

颞叶内侧癫痫并抑郁病人脑功能连接密度的静息态功能磁共振成像研究

目的 探讨颞叶内侧癫痫伴抑郁（MTLEWD）病人在静息态功能磁共振成像（rs-fMRI）中功能活动异常的脑区的特点。方法 纳入2021年1—12月在海南医学院第一附属医院神经内科门诊符合国际抗癫痫联盟（ILAE）诊断分类标准的颞叶内侧癫痫病人，根据HAMD评分将病人分为MTLEWD组和颞叶内侧癫痫不伴抑郁组（MTLE组），同时纳入与病人性别、年龄相匹配的对照组。使用GE Discovery MR7503.0T设备根据预先设定参数行磁共振扫描，获取静息态功能磁共振数据。采用SPSS 22.0统计分析软件对一般人口学资料进行分析。基于MATLAB 2018平台采用DPABI软件对磁共振数据进行预处理，使用功能连接密度（FCD）分析指标对三组被试者行ANOVA分析差异有统计学意义的脑区，然后行组间两样本的t检验，根据高斯随机场（GRF）理论满足体素显著性<0.001、连续体素数量≥23，团块显著性<0.05的区域被认为差异有统计学意义。结果 共纳入MTLE组病人20例，MTLEWD组病人21例，对照组25例，三组病人一般资料（年龄、性别）差异无统计学意义（P>0.05）。三...     

SD-CNN: A static-dynamic convolutional neural network for functional brain networks

Static functional connections (sFCs) and dynamic functional connections (dFCs) have been widely used in the resting-state functional MRI (rs-fMRI) analysis. sFCs, calculated based on entire rs-fMRI scans, can accurately describe the static topology of the brain network. dFCs, estimated by dividing rs-fMRI scans into a series of short sliding windows, are used to reveal time-varying changes in FC patterns. Currently, how to jointly use sFCs and dFCs to identify brain diseases under the framework of deep learning is still a hot issue. To this end, we propose a static-dynamic convolutional neural network for functional brain networks, which involves a static pathway and a dynamic pathway for taking full advantages of sFCs and dFCs. Specifically, the static pathway, using high-resolution convolution filters (i.e., convolution filters with a high number of channels) at a single adjacency matrix of sFCs, is performed to capture static FC patterns. The dynamic pathway, using low-resolution convolution filters at each adjacency matrix of dFCs, is performed to capture time-varying FC patterns. Two types of diffusion connections are used in this model for encouraging the transfer of information between the static pathway and the dynamic pathway, which can make the learned features more discriminative. Furthermore, a static and dynamic combination classifier is introduced to combine features from two pathways for identifying brain diseases. Experiments on two real datasets demonstrate the effectiveness and advantages of our proposed method.     

轻微型肝性脑病患者后扣带回与双侧海马间功能连接静息态功能MRI研究

目的：探讨轻微型肝性脑病（MHE）患者静息态下后扣带回（PCC）与双侧海马间功能连接（FC）的改变情况。方法：采用静息态功能磁共振成像（rs-fMRI）技术，分析17例 MHE患者（MHE组）和17例健康对照者（HC组）静息态下脑功能活动，观察 MHE患者静息态下PCC与双侧海马间的功能连接情况，并与数字-符号试验（DST）和数字连接试验-A （NCT-A）评分进行相关分析。结果：与 HC组相比，MHE组 PCC 与右侧海马间 FC 减低（P＜0．05，K≥10体素）；MHE组PCC和右侧海马FC分数与DST评分呈显著正相关，与NCT-A评分呈显著负相关（P＜0．05，K≥体素）。结论：MHE患者脑功能存在损伤，海马与后扣带回间连接强度可以提示 MH E患者的认知功能状态。     

The development of functional connectivity within the dorsal striatum from early childhood to adulthood

Dorsal striatum, principally comprising of caudate and putamen, is well-known to support motor function but also various higher-order cognitive functions. This is enabled by developing short- and long-range connections to distributed cortical regions throughout the life span, but few studies have examined developmental changes from young children to adults in the same cohort. Here we investigated the development of dorsal-striatal network in a large (n = 476), single-site sample of healthy subjects 3–42 years of age in three groups (children, adolescence, adults). The results showed that the connectivity within the striatum and to sensorimotor regions was established at an early stage of life and remained strong in adolescence, supporting that sensory-seeking behaviours and habit formation are important learning mechanisms during the developmental periods. This connectivity diminished with age, as many behaviours become more efficient and automated. Adolescence demonstrated a remarkable transition phase where the connectivity to dorsolateral prefrontal cortex emerged but connectivity to the dorsomedial prefrontal and posterior brain, which belong to the ventral attentional and default mode networks, was only seen in adults. This prolonged maturation in between-network integration may explain the behavioural characteristics of adolescents in that they exhibit elaborated cognitive performance but also demonstrate high risk-taking behaviours.     

基于三重网络模型的酒精使用障碍患者静息态fMRI研究

目的:基于静息态功能磁共振(rs-fMRI)的独立成分分析(ICA)方法探讨酒精使用障碍(AUD)患者静息状态下三重网络模型(默认网络、突显网络及中央执行网络)功能网络连接(FNC)改变.方法:搜集2019年9月-2020年6月本院32例酒精使用障碍者和21例健康志愿者(正常对照组)的临床和MRI资料.所有被试行颅脑常...