白质
立体脑电图
脑电图
神经科学
解码方法
大脑定位
心理学
人工智能
计算机科学
磁共振成像
医学
电信
放射科
癫痫外科
作者
Guangye Li,Shize Jiang,Sivylla E. Paraskevopoulou,Guohong Chai,Zixuan Wei,Shengjie Liu,Meng Wang,Xu Yang,Zhen Fan,Zehan Wu,Liang Chen,Dingguo Zhang,Xiangyang Zhu
出处
期刊:Journal of Neural Engineering
[IOP Publishing]
日期:2021-07-20
卷期号:18 (4): 0460c6-0460c6
被引量:18
标识
DOI:10.1088/1741-2552/ac160e
摘要
Objective. White matter tissue takes up approximately 50% of the human brain volume and it is widely known as a messenger conducting information between areas of the central nervous system. However, the characteristics of white matter neural activity and whether white matter neural recordings can contribute to movement decoding are often ignored and still remain largely unknown. In this work, we make quantitative analyses to investigate these two important questions using invasive neural recordings. Approach. We recorded stereo-electroencephalography (SEEG) data from 32 human subjects during a visually-cued motor task, where SEEG recordings can tap into gray and white matter electrical activity simultaneously. Using the proximal tissue density method, we identified the location (i.e. gray or white matter) of each SEEG contact. Focusing on alpha oscillatory and high gamma activities, we compared the activation patterns between gray matter and white matter. Then, we evaluated the performance of such white matter activation in movement decoding. Main results. The results show that white matter also presents activation under the task, in a similar way with the gray matter but at a significantly lower amplitude. Additionally, this work also demonstrates that combing white matter neural activities together with that of gray matter significantly promotes the movement decoding accuracy than using gray matter signals only. Significance. Taking advantage of SEEG recordings from a large number of subjects, we reveal the response characteristics of white matter neural signals under the task and demonstrate its enhancing function in movement decoding. This study highlights the importance of taking white matter activities into consideration in further scientific research and translational applications.
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