Gonuguntla V, Shafiq G, Wang Y, Veluvolu K C
Annu Int Conf IEEE Eng Med Biol Soc. 2015 Aug;2015:2896-9. doi: 10.1109/EMBC.2015.7318997.
The brain functional network perspective forms the basis to relate mechanisms of brain functions. This work analyzes the network mechanisms related to human emotion based on synchronization measure - phase-locking value in EEG to formulate the emotion specific brain functional network. Based on network dissimilarities between emotion and rest tasks, most reactive channel pairs and the reactive band corresponding to emotions are identified. With the identified most reactive pairs, the subject-specific functional network is formed. The identified subject-specific and emotion-specific dynamic network pattern show significant synchrony variation in line with the experiment protocol. The same network pattern are then employed for classification of emotions. With the study conducted on the 4 subjects, an average classification accuracy of 62 % was obtained with the proposed technique.
脑功能网络视角构成了关联脑功能机制的基础。这项工作基于同步测量——脑电图中的锁相值，分析与人类情绪相关的网络机制，以构建特定情绪的脑功能网络。基于情绪任务和静息任务之间的网络差异，识别出对情绪反应最强烈的通道对以及对应的反应频段。利用识别出的最具反应性的通道对，形成个体特异性功能网络。所识别出的个体特异性和情绪特异性动态网络模式显示出与实验方案一致的显著同步变化。然后将相同的网络模式用于情绪分类。通过对4名受试者进行的研究，所提出的技术获得了平均62%的分类准确率。
