Department of Rehabilitation Science, Graduate School of Health Sciences, Life and Medical Sciences Area, Kobe University, Hyogo, Japan.
Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology (NICT), Osaka University, Osaka, Japan.
Appl Neuropsychol Adult. 2022 Sep-Oct;29(5):1122-1130. doi: 10.1080/23279095.2020.1852565. Epub 2020 Dec 5.
Brain functional connectivity in the resting-state represents intrinsic functional states and correlates with cognitive performance. In patients with schizophrenia, reports on the relationships between forms of functional disconnectivity in local areas and cognitive disability have used resting-state functional magnetic resonance imaging data. Meanwhile, cognitive deficits in relation to inter-network forms of functional connectivity on a large scale are not well understood. This study examines cognitive functions in relation to the number of resting-state inter-network forms of functional connectivity focusing on task-positive networks (fronto-parietal network [FPN] and cingulo-opercular network [CON]) and task-negative network (default mode network [DMN]). We compare patients with schizophrenia (SCH group) and healthy controls (HC group). We conducted a functional network analysis by applying graph theory and evaluated cognitive functions using the . The number of forms of functional connectivity between FPN and DMN and between CON and DMN were significantly higher in SCH group than in HC group, and those in SCH group were also weakly correlated with their attention scores. It is suggested that fewer than typical functional segregations between task-positive and task-negative networks in SCH group relate to inefficient distribution of cognitive resources and low attentional abilities.
静息态脑功能连接代表内在功能状态,与认知表现相关。在精神分裂症患者中,有关局部区域功能失连接形式与认知障碍之间关系的报告使用了静息态功能磁共振成像数据。然而,关于大尺度网络间功能连接形式与认知功能的关系尚不清楚。本研究关注任务正激活网络(额顶网络[FPN]和扣带回-顶叶网络[CON])和任务负激活网络(默认模式网络[DMN])之间静息态网络间功能连接的数量,以此探讨认知功能。我们将精神分裂症患者(SCH 组)与健康对照组(HC 组)进行了比较。我们通过应用图论进行了功能网络分析,并使用. 评估了认知功能。与 HC 组相比,SCH 组 FPN 与 DMN 之间以及 CON 与 DMN 之间的功能连接形式数量明显更高,而 SCH 组的这些功能连接形式也与他们的注意力评分呈弱相关。这表明,SCH 组中任务正激活和任务负激活网络之间的功能分离少于典型情况,这与认知资源分配效率低下和注意力能力低下有关。