A brain-computer interface based on self-regulation of gamma-oscillations in the superior parietal cortex

被引:26
作者
Grosse-Wentrup, Moritz [1 ]
Schoelkopf, Bernhard [1 ]
机构
[1] Max Planck Inst Intelligent Syst, Dept Empir Inference, D-72076 Tubingen, Germany
关键词
brain-computer interface; brain-machine interface; ALS; locked-in; gamma-oscillations; neurofeedback; PEOPLE; EEG; COMMUNICATION; ATTENTION; PATTERNS; SIGNALS; STATE;
D O I
10.1088/1741-2560/11/5/056015
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Objective. Brain-computer interface (BCI) systems are often based on motor- and/or sensory processes that are known to be impaired in late stages of amyotrophic lateral sclerosis (ALS). We propose a novel BCI designed for patients in late stages of ALS that only requires high-level cognitive processes to transmit information from the user to the BCI. Approach. We trained subjects via EEG-based neurofeedback to self-regulate the amplitude of gamma-oscillations in the superior parietal cortex (SPC). We argue that parietal gamma-oscillations are likely to be associated with high-level attentional processes, thereby providing a communication channel that does not rely on the integrity of sensory- and/or motor-pathways impaired in late stages of ALS. Main results. Healthy subjects quickly learned to self-regulate gamma-power in the SPC by alternating between states of focused attention and relaxed wakefulness, resulting in an average decoding accuracy of 70.2%. One locked-in ALS patient (ALS-FRS-R score of zero) achieved an average decoding accuracy significantly above chance-level though insufficient for communication (55.8%). Significance. Self-regulation of gamma-power in the SPC is a feasible paradigm for brain-computer interfacing and may be preserved in late stages of ALS. This provides a novel approach to testing whether completely locked-in ALS patients retain the capacity for goal-directed thinking.
引用
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页数:13
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