期刊
JOURNAL OF NEUROPHYSIOLOGY
卷 118, 期 2, 页码 1329-1343出版社
AMER PHYSIOLOGICAL SOC
DOI: 10.1152/jn.00070.2017
关键词
brain-machine interface; spikes; LFP; ECoG; epidural signals; stability; longevity
资金
- National Institutes of Health Grants [K08NS060223, R01NS094748]
- Defense Advanced Research Projects Agency Grant [N66001121-4023]
- Brain Research Foundation Grant [BRF SG 2009-14]
- Northwestern Memorial Foundation Dixon Translational Research Grant Program (NIH Grant) [UL1RR025741]
- Paralyzed Veterans of America [2728]
- Doris Duke Charitable Foundation Clinical Scientist Development Award [2011039]
- Craig H. Neilsen Foundation
Brain-machine interfaces (BMIs), also called brain-computer interfaces (BCIs), decode neural signals and use them to control some type of external device. Despite many experimental successes and terrific demonstrations in animals and humans, a high-performance, clinically viable device has not yet been developed for widespread usage. There are many factors that impact clinical viability and BMI performance. Arguably, the first of these is the selection of brain signals used to control BMIs. In this review, we summarize the physiological characteristics and performance-including movement-related information, longevity, and stability-of multiple types of input signals that have been used in invasive BMIs to date. These include intracortical spikes as well as field potentials obtained inside the cortex, at the surface of the cortex (electrocorticography), and at the surface of the dura mater (epidural signals). We also discuss the potential for future enhancements in input signal performance, both by improving hardware and by leveraging the knowledge of the physiological characteristics of these signals to improve decoding and stability.
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