Thye Melissa D, Ammons Carla J, Murdaugh Donna L, Kana Rajesh K
Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA.
Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL, USA.
Behav Brain Res. 2018 Jul 16;347:385-393. doi: 10.1016/j.bbr.2018.03.041. Epub 2018 Mar 28.
Social neuroscience research has focused on an identified network of brain regions primarily associated with processing Theory of Mind (ToM). However, ToM is a broad cognitive process, which encompasses several sub-processes, such as mental state detection and intentional attribution, and the connectivity of brain regions underlying the broader ToM network in response to paradigms assessing these sub-processes requires further characterization. Standard fMRI analyses which focus only on brain activity cannot capture information about ToM processing at a network level. An alternative method, independent component analysis (ICA), is a data-driven technique used to isolate intrinsic connectivity networks, and this approach provides insight into network-level regional recruitment. In this fMRI study, three complementary, but distinct ToM tasks assessing mental state detection (e.g. RMIE: Reading the Mind in the Eyes; RMIV: Reading the Mind in the Voice) and intentional attribution (Causality task) were each analyzed using ICA in order to separately characterize the recruitment and functional connectivity of core nodes in the ToM network in response to the sub-processes of ToM. Based on visual comparison of the derived networks for each task, the spatiotemporal network patterns were similar between the RMIE and RMIV tasks, which elicited mentalizing about the mental states of others, and these networks differed from the network derived for the Causality task, which elicited mentalizing about goal-directed actions. The medial prefrontal cortex, precuneus, and right inferior frontal gyrus were seen in the components with the highest correlation with the task condition for each of the tasks highlighting the role of these regions in general ToM processing. Using a data-driven approach, the current study captured the differences in task-related brain response to ToM in three distinct ToM paradigms. The findings of this study further elucidate the neural mechanisms associated with mental state detection and causal attribution, which represent possible sub-processes of the complex construct of ToM processing.
社会神经科学研究主要聚焦于一个已确定的大脑区域网络,该网络主要与心理理论(ToM)的处理相关。然而,心理理论是一个广泛的认知过程,它包含几个子过程,如心理状态检测和意图归因,并且在应对评估这些子过程的范式时,更广泛的心理理论网络背后的大脑区域连接性需要进一步表征。仅关注大脑活动的标准功能磁共振成像(fMRI)分析无法在网络层面捕捉到有关心理理论处理的信息。另一种方法,即独立成分分析(ICA),是一种数据驱动技术,用于分离内在连接网络,这种方法能深入了解网络层面的区域招募情况。在这项功能磁共振成像研究中,使用独立成分分析分别对三个互补但不同的心理理论任务进行了分析,这些任务评估心理状态检测(如“从眼睛中读懂心思”任务:RMIE;“从声音中读懂心思”任务:RMIV)和意图归因(因果关系任务),以便分别表征心理理论网络中核心节点在应对心理理论子过程时的招募情况和功能连接性。基于对每个任务所导出网络的视觉比较,“从眼睛中读懂心思”任务和“从声音中读懂心思”任务之间的时空网络模式相似,这两个任务引发了对他人心理状态的心智化,并且这些网络与为因果关系任务所导出的网络不同,因果关系任务引发了对目标导向行动的心智化。在与每个任务的任务条件相关性最高的成分中都观察到了内侧前额叶皮质、楔前叶和右下额叶回,这突出了这些区域在一般心理理论处理中的作用。本研究采用数据驱动方法,捕捉了三种不同心理理论范式中与心理理论任务相关的大脑反应差异。这项研究的结果进一步阐明了与心理状态检测和因果归因相关的神经机制,这些机制代表了心理理论处理这一复杂结构可能的子过程。