The Olin Neuropsychiatry Research Center, Hartford, CT, USA.
Neuroimage. 2010 Feb 15;49(4):3373-84. doi: 10.1016/j.neuroimage.2009.11.034. Epub 2009 Dec 4.
Previous studies have reported learning and navigation impairments in schizophrenia patients during virtual reality allocentric learning tasks. The neural bases of these deficits have not been explored using functional MRI despite well-explored anatomic characterization of these paradigms in non-human animals. Our objective was to characterize the differential distributed neural circuits involved in virtual Morris water task performance using independent component analysis (ICA) in schizophrenia patients and controls. Additionally, we present behavioral data in order to derive relationships between brain function and performance, and we have included a general linear model-based analysis in order to exemplify the incremental and differential results afforded by ICA. Thirty-four individuals with schizophrenia and twenty-eight healthy controls underwent fMRI scanning during a block design virtual Morris water task using hidden and visible platform conditions. Independent components analysis was used to deconstruct neural contributions to hidden and visible platform conditions for patients and controls. We also examined performance variables, voxel-based morphometry and hippocampal subparcellation, and regional BOLD signal variation. Independent component analysis identified five neural circuits. Mesial temporal lobe regions, including the hippocampus, were consistently task-related across conditions and groups. Frontal, striatal, and parietal circuits were recruited preferentially during the visible condition for patients, while frontal and temporal lobe regions were more saliently recruited by controls during the hidden platform condition. Gray matter concentrations and BOLD signal in hippocampal subregions were associated with task performance in controls but not patients. Patients exhibited impaired performance on the hidden and visible conditions of the task, related to negative symptom severity. While controls showed coupling between neural circuits, regional neuroanatomy, and behavior, patients activated different task-related neural circuits, not associated with appropriate regional neuroanatomy. GLM analysis elucidated several comparable regions, with the exception of the hippocampus. Inefficient allocentric learning and memory in patients may be related to an inability to recruit appropriate task-dependent neural circuits.
先前的研究报告称，精神分裂症患者在虚拟现实的环境中进行空间学习任务时，存在学习和导航障碍。尽管在非人类动物中对这些范式进行了广泛的解剖学描述，但尚未使用功能磁共振成像（fMRI）来探索这些缺陷的神经基础。我们的目标是使用独立成分分析（ICA）来描述精神分裂症患者和对照组在执行虚拟 Morris 水迷宫任务时涉及的差异分布的神经回路。此外，我们还提供了行为数据，以便得出大脑功能与表现之间的关系，并包括基于一般线性模型的分析，以举例说明 ICA 提供的增量和差异结果。34 名精神分裂症患者和 28 名健康对照组在使用隐藏和可见平台条件的块设计虚拟 Morris 水迷宫任务中进行 fMRI 扫描。使用独立成分分析对患者和对照组的隐藏和可见平台条件的神经贡献进行解构。我们还检查了性能变量、体素形态计量学和海马亚区划分以及区域 BOLD 信号变化。独立成分分析确定了五个神经回路。内侧颞叶区域，包括海马体，在所有条件和组中都是与任务相关的。对于患者，额叶、纹状体和顶叶回路在可见条件下优先被募集，而对于对照组，在隐藏平台条件下，额叶和颞叶区域则更为显著地被募集。海马亚区的灰质浓度和 BOLD 信号与对照组的任务表现相关，但与患者无关。患者在任务的隐藏和可见条件下表现出受损的表现，与阴性症状的严重程度有关。虽然对照组显示出神经回路、区域神经解剖学和行为之间的耦合，但患者激活了不同的与任务相关的神经回路，与适当的区域神经解剖学无关。GLM 分析阐明了几个可比的区域，除了海马体。患者的非定向学习和记忆能力受损可能与无法募集适当的任务相关的神经回路有关。
