Task-Independent Mental Workload Classification Based Upon Common Multiband EEG Cortical Connectivity
Task-Independent Mental Workload Classification Based Upon Common Multiband EEG Cortical Connectivity
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DOI：
10.1109/tnsre.2017.2701002
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发表时间：
2017-11-01
影响因子：
4.9
通讯作者：
Sun, Yu
中科院分区：
文献类型：
--
作者：
Dimitrakopoulos, Georgios N.;Kakkos, Ioannis;Sun, Yu
心理负荷的有效分类是神经科学中的一个重要问题，目前仅限于单个任务，而跨任务分类仍然是一个挑战。此外，网络方法已经成为研究大脑复杂组织的一个有前途的方向，使各种精神状态的解释变得更容易。在本文中，使用两个心理任务（N-back和心算），我们提出了一个框架，跨以及任务内的工作量歧视，利用多波段脑电图（EEG）皮层脑连接。具体地说，我们在不同频段的脑电源空间中构建了功能网络，并将各个功能连接作为分类特征，基于序贯特征选择算法识别出显著特征子集。这些连接子集能够提供87%的跨任务，88%的N-back任务和86%的心算任务的准确性。总之，我们的方法实现了检测少量的大脑区域之间的歧视性相互作用，导致高精度的任务内和跨任务分类。此外，所确定的功能连接功能，其中大部分是在额叶区的θ和β频段检测，有助于描绘共享以及不同的神经机制的两个心理任务。
Efficient classification of mental workload, an important issue in neuroscience, is limited, so far to single task, while cross-task classification remains a challenge. Furthermore, network approaches have emerged as a promising direction for studying the complex organization of the brain, enabling easier interpretation of various mental states. In this paper, using two mental tasks (N-back and mental arithmetic), we present a framework for cross-as well as within-task workload discrimination by utilizing multi-band electroencephalography (EEG) cortical brain connectivity. In detail, we constructed functional networks in EEG source space in different frequency bands and considering the individual functional connections as classification features, we identified salient feature subsets based on a sequential feature selection algorithm. These connectivity subsets were able to provide accuracy of 87% for cross-task, 88% for N-back task, and 86% for mental arithmetic task. In conclusion, our method achieved to detect a small number of discriminative interactions among brain areas, leading to high accuracy in both within-task and cross-task classifications. In addition, the identified functional connectivity features, the majority of which were detected in frontal areas in theta and beta frequency bands, helped delineate the shared as well as the distinct neural mechanisms of the two mental tasks.