Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario.
Department of Psychiatry, Maryland Psychiatric Research Center, Catonsville, Maryland.
Biol Psychiatry. 2018 Nov 1;84(9):665-674. doi: 10.1016/j.biopsych.2018.03.013. Epub 2018 Apr 13.
Deficits in neurocognition and social cognition are drivers of reduced functioning in schizophrenia spectrum disorders, with potentially shared neurobiological underpinnings. Many studies have sought to identify brain-based biomarkers of these clinical variables using a priori dichotomies (e.g., good vs. poor cognition, deficit vs. nondeficit syndrome).
We evaluated a fully data-driven approach to do the same by building and validating a brain connectivity-based biomarker of social cognitive and neurocognitive performance in a sample using resting-state and task-based functional magnetic resonance imaging (n = 74 healthy control participants, n = 114 persons with schizophrenia spectrum disorder, 188 total). We used canonical correlation analysis followed by clustering to identify a functional connectivity signature of normal and poor social cognitive and neurocognitive performance.
Persons with poor social cognitive and neurocognitive performance were differentiated from those with normal performance by greater resting-state connectivity in the mirror neuron and mentalizing systems. We validated our findings by showing that poor performers also scored lower on functional outcome measures not included in the original analysis and by demonstrating neuroanatomical differences between the normal and poorly performing groups. We used a support vector machine classifier to demonstrate that functional connectivity alone is enough to distinguish normal and poorly performing participants, and we replicated our findings in an independent sample (n = 75).
A brief functional magnetic resonance imaging scan may ultimately be useful in future studies aimed at characterizing long-term illness trajectories and treatments that target specific brain circuitry in those with impaired cognition and function.
神经认知和社会认知缺陷是精神分裂症谱系障碍功能下降的驱动因素,其潜在的神经生物学基础可能是相同的。许多研究试图使用先验二分法(例如,认知良好与认知不佳、有缺陷与非缺陷综合征)来确定这些临床变量的基于大脑的生物标志物。
我们通过构建和验证基于大脑连接的社会认知和神经认知表现的生物标志物,评估了一种完全数据驱动的方法,该方法使用静息态和任务态功能磁共振成像(n = 74 名健康对照参与者,n = 114 名精神分裂症谱系障碍患者,共 188 名)。我们使用典型相关分析和聚类来确定正常和认知表现不佳的社会认知和神经认知的功能连接特征。
与认知表现正常的人相比,认知表现不佳的人在镜像神经元和心理化系统的静息状态连接上更大。我们通过证明表现不佳的人在原始分析中未包含的功能结果测量上的得分也较低,以及通过显示正常和表现不佳的组之间的神经解剖学差异,验证了我们的发现。我们使用支持向量机分类器来证明仅功能连接就足以区分认知表现正常和表现不佳的参与者,并且在独立样本(n = 75)中复制了我们的发现。
简短的功能磁共振成像扫描最终可能有助于未来的研究,旨在描述认知和功能受损患者的长期疾病轨迹和针对特定大脑回路的治疗。