Liu Yuchao, Zhang Yin, Jiang Zhongyi, Kong Wanzeng, Zou Ling
School of Computer and Artificial Intelligence, Changzhou University, Changzhou 213164, China.
School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China.
Brain Sci. 2023 Mar 13;13(3):485. doi: 10.3390/brainsci13030485.
It is crucial to understand the neural feedback mechanisms and the cognitive decision-making of the brain during the processing of rewards. Here, we report the first attempt for a simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) study in a gambling task by utilizing tensor decomposition.
First, the single-subject EEG data are represented as a third-order spectrogram tensor to extract frequency features. Next, the EEG and fMRI data are jointly decomposed into a superposition of multiple sources characterized by space-time-frequency profiles using coupled matrix tensor factorization (CMTF). Finally, graph-structured clustering is used to select the most appropriate model according to four quantitative indices.
The results clearly show that not only are the regions of interest (ROIs) found in other literature activated, but also the olfactory cortex and fusiform gyrus which are usually ignored. It is found that regions including the orbitofrontal cortex and insula are activated for both winning and losing stimuli. Meanwhile, regions such as the superior orbital frontal gyrus and anterior cingulate cortex are activated upon winning stimuli, whereas the inferior frontal gyrus, cingulate cortex, and medial superior frontal gyrus are activated upon losing stimuli.
This work sheds light on the reward-processing progress, provides a deeper understanding of brain function, and opens a new avenue in the investigation of neurovascular coupling via CMTF.
了解大脑在奖励处理过程中的神经反馈机制和认知决策至关重要。在此，我们报告了首次尝试通过张量分解在赌博任务中进行同步脑电图（EEG）-功能磁共振成像（fMRI）研究。
首先，将单受试者的EEG数据表示为三阶频谱图张量以提取频率特征。接下来，使用耦合矩阵张量分解（CMTF）将EEG和fMRI数据联合分解为多个以时空频率分布为特征的源的叠加。最后，使用图结构聚类根据四个定量指标选择最合适的模型。
结果清楚地表明，不仅激活了其他文献中发现的感兴趣区域（ROI），还激活了通常被忽视的嗅觉皮层和梭状回。研究发现，包括眶额皮层和岛叶在内的区域在赢和输的刺激下均被激活。同时，眶额上回和前扣带回皮层等区域在赢的刺激下被激活，而额下回、扣带回皮层和额上内侧回在输的刺激下被激活。
这项工作揭示了奖励处理过程，加深了对脑功能的理解，并通过CMTF为神经血管耦合的研究开辟了一条新途径。
