计算机科学
频道(广播)
信号(编程语言)
电生理学
电极阵列
计算机硬件
模式识别(心理学)
人工智能
电极
神经科学
电信
物理
量子力学
生物
程序设计语言
作者
Taro Kaiju,Masato Inoue,Masayuki Hirata,Takafumi Suzuki
出处
期刊:Journal of Neural Engineering
[IOP Publishing]
日期:2021-02-03
卷期号:18 (3): 036025-036025
被引量:29
标识
DOI:10.1088/1741-2552/abe245
摘要
Objective.Advances in brain-machine interfaces (BMIs) are expected to support patients with movement disorders. Electrocorticogram (ECoG) measures electrophysiological activities over a large area using a low-invasive flexible sheet placed on the cortex. ECoG has been considered as a feasible signal source of the clinical BMI device. To capture neural activities more precisely, the feasibility of higher-density arrays has been investigated. However, currently, the number of electrodes is limited to approximately 300 due to wiring difficulties, device size, and system costs.Approach.We developed a high-density recording system with a large coverage (14 × 7 mm2) and using 1152 electrodes by directly integrating dedicated flexible arrays with the neural-recording application-specific integrated circuits and their interposers.Main results.Comparative experiments with a 128-channel array demonstrated that the proposed device could delineate the entire digit representation of a nonhuman primate. Subsampling analysis revealed that higher-amplitude signals can be measured using higher-density arrays.Significance.We expect that the proposed system that simultaneously establishes large-scale sampling, high temporal-precision of electrophysiology, and high spatial resolution comparable to optical imaging will be suitable for next-generation brain-sensing technology.
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