Graduate School of System Engineering, Kochi University of Technology, Kochi, Japan.
School of Systems Engineering, Kochi University of Technology, Kochi, Japan.
Comput Intell Neurosci. 2022 Dec 20;2022:3999223. doi: 10.1155/2022/3999223. eCollection 2022.
It is essential to understand the neural mechanisms underlying human decision-making. Several studies using traditional analysis have attempted to explain the neural mechanisms associated with decision-making based on abstract rewards. However, brain-decoding research that utilizes the multivoxel pattern analysis (MVPA) method, especially research focusing on decision-making, remains limited. In brain analysis, decoding strategies for multivoxels are required for various decision-making evaluation criteria. This is because in daily life, the human decision-making process makes use of many evaluation criteria. In the present study, we investigated the representation of evaluation criterion categories in a decision-making process using functional magnetic resonance imaging and MVPA. Participants performed a decision-making task that involved choosing a smartphone by referring to four types of evaluation criteria. The regions of interest (ROIs) were the ventromedial prefrontal cortex (vmPFC), nucleus accumbens (NAcc), and insula. Each combination of the four evaluation criteria was analyzed based on a binary classification using MVPA. From the binary classification accuracy obtained from MVPA, the regions that reflected differences in the evaluation criteria among the ROIs were evaluated. The results of the binary classification in the vmPFC and NAcc indicated that these regions can express evaluation criteria in decision-making processes.
理解人类决策背后的神经机制至关重要。一些使用传统分析方法的研究试图基于抽象奖励来解释与决策相关的神经机制。然而,利用多体素模式分析(MVPA)方法的大脑解码研究仍然有限,特别是针对决策的研究。在大脑分析中,需要针对各种决策评估标准的多体素解码策略。这是因为在日常生活中,人类的决策过程会使用多种评估标准。在本研究中,我们使用功能磁共振成像和 MVPA 研究了决策过程中评估标准类别的表示。参与者执行了一项决策任务,通过参考四种类型的评估标准来选择智能手机。感兴趣区域(ROI)是腹内侧前额叶皮层(vmPFC)、伏隔核(NAcc)和脑岛。使用 MVPA 对四种评估标准的每种组合进行了基于二进制分类的分析。从 MVPA 获得的二进制分类准确性中,评估了 ROI 之间评估标准差异的区域。vmPFC 和 NAcc 中的二进制分类结果表明,这些区域可以在决策过程中表达评估标准。