Abstract：
BACKGROUND: Psychomotor disturbances are observed across psychiatric disorders and often manifest as psychomotor slowing, agitation, disorganized behavior, or catatonia. Psychomotor function includes both cognitive and motor components, but the neural circuits driving these subprocesses and how they relate to symptoms have remained elusive for centuries.
METHODS: We analyzed data from the HCP-EP (Human Connectome Project for Early Psychosis), a multisite study of 125 participants with early psychosis and 58 healthy participants with resting-state functional magnetic resonance imaging and clinical characterization. Psychomotor function was assessed using the 9-hole pegboard task, a timed motor task that engages mechanical and psychomotor components of action, and tasks assessing processing speed and task switching. We used multivariate pattern analysis of whole-connectome data to identify brain correlates of psychomotor function.
RESULTS: We identified discrete brain circuits driving the cognitive and motor components of psychomotor function. In our combined sample of participants with psychosis (n = 89) and healthy control participants (n = 52), the strongest correlates of psychomotor function (pegboard performance) (p < .005) were between a midline cerebellar region and left frontal region and presupplementary motor area. Psychomotor function was correlated with both cerebellar-frontal connectivity (r = 0.33) and cerebellar-presupplementary motor area connectivity (r = 0.27). However, the cognitive component of psychomotor performance (task switching) was correlated only with cerebellar-frontal connectivity (r = 0.19), whereas the motor component (processing speed) was correlated only with cerebellar-presupplementary motor area connectivity (r = 0.15), suggesting distinct circuits driving unique subprocesses of psychomotor function.
CONCLUSIONS: We identified cerebellar-cortical circuits that drive distinct subprocesses of psychomotor function. Future studies should probe relationships between cerebellar connectivity and psychomotor performance using neuromodulation.
METHODS: We analyzed data from the HCP-EP (Human Connectome Project for Early Psychosis), a multisite study of 125 participants with early psychosis and 58 healthy participants with resting-state functional magnetic resonance imaging and clinical characterization. Psychomotor function was assessed using the 9-hole pegboard task, a timed motor task that engages mechanical and psychomotor components of action, and tasks assessing processing speed and task switching. We used multivariate pattern analysis of whole-connectome data to identify brain correlates of psychomotor function.
RESULTS: We identified discrete brain circuits driving the cognitive and motor components of psychomotor function. In our combined sample of participants with psychosis (n = 89) and healthy control participants (n = 52), the strongest correlates of psychomotor function (pegboard performance) (p < .005) were between a midline cerebellar region and left frontal region and presupplementary motor area. Psychomotor function was correlated with both cerebellar-frontal connectivity (r = 0.33) and cerebellar-presupplementary motor area connectivity (r = 0.27). However, the cognitive component of psychomotor performance (task switching) was correlated only with cerebellar-frontal connectivity (r = 0.19), whereas the motor component (processing speed) was correlated only with cerebellar-presupplementary motor area connectivity (r = 0.15), suggesting distinct circuits driving unique subprocesses of psychomotor function.
CONCLUSIONS: We identified cerebellar-cortical circuits that drive distinct subprocesses of psychomotor function. Future studies should probe relationships between cerebellar connectivity and psychomotor performance using neuromodulation.
摘要：
背景：精神运动障碍在精神疾病中观察到，通常表现为精神运动减慢，激动,杂乱无章的行为，或者紧张症.精神运动功能包括认知和运动成分，但是驱动这些子过程的神经回路以及它们如何与症状相关，几个世纪以来一直难以捉摸。
方法：我们分析了人类连接组项目早期精神病的数据，一项对125名早期精神病患者和58名健康参与者进行静息状态功能磁共振成像和临床特征的多部位研究。使用9孔Pegboard任务评估精神运动功能，定时运动任务，涉及动作的机械和精神运动部分，和任务评估处理速度和任务切换。我们使用全连接体数据的多变量模式分析来识别精神运动功能的大脑相关性。
结果：我们确定了驱动精神运动功能的认知和运动成分的离散大脑回路。在我们的精神病患者（n=89）和非精神病对照（n=52）的组合样本中，精神运动功能(pegboard表现)(p<.005)最强的相关性在小脑中线区与(1)左额叶区和(2)补充前运动区(preSMA)之间.精神运动功能与小脑-额叶连接（r=0.33）和小脑-前SMA连接（r=0.27）相关。然而,精神运动表现（任务转换）的认知成分仅与小脑-额叶连通性相关（r=0.19），而运动分量（处理速度）仅与小脑-前SMA连接相关（r=0.15），提示不同的电路驱动精神运动功能的独特子过程。
结论：我们确定了驱动不同精神运动功能亚过程的小脑-皮质回路。未来的研究应该使用神经调节来探索小脑连通性与精神运动表现之间的关系。
方法：我们分析了人类连接组项目早期精神病的数据，一项对125名早期精神病患者和58名健康参与者进行静息状态功能磁共振成像和临床特征的多部位研究。使用9孔Pegboard任务评估精神运动功能，定时运动任务，涉及动作的机械和精神运动部分，和任务评估处理速度和任务切换。我们使用全连接体数据的多变量模式分析来识别精神运动功能的大脑相关性。
结果：我们确定了驱动精神运动功能的认知和运动成分的离散大脑回路。在我们的精神病患者（n=89）和非精神病对照（n=52）的组合样本中，精神运动功能(pegboard表现)(p<.005)最强的相关性在小脑中线区与(1)左额叶区和(2)补充前运动区(preSMA)之间.精神运动功能与小脑-额叶连接（r=0.33）和小脑-前SMA连接（r=0.27）相关。然而,精神运动表现（任务转换）的认知成分仅与小脑-额叶连通性相关（r=0.19），而运动分量（处理速度）仅与小脑-前SMA连接相关（r=0.15），提示不同的电路驱动精神运动功能的独特子过程。
结论：我们确定了驱动不同精神运动功能亚过程的小脑-皮质回路。未来的研究应该使用神经调节来探索小脑连通性与精神运动表现之间的关系。
