物理化学学报 >> 2020, Vol. 36 >> Issue (12): 2007004.doi: 10.3866/PKU.WHXB202007004

所属专题: 神经界面

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植入式神经电极阵列器件与材料的研究进展

都展宏(), 鲁艺, 蔚鹏飞, 邓春山, 李骁健()   

  • 收稿日期:2020-07-01 录用日期:2020-08-11 发布日期:2020-08-17
  • 通讯作者: 都展宏,李骁健 E-mail:zh.du@siat.ac.cn;xj.li@siat.ac.cn
  • 作者简介:都展宏,生于1988年。本科毕业于中国科学技术大学,现在中国科学院深圳先进技术研究院担任副研究员,主要研究脑机接口界面材料、电化学神经递质释放与检测、神经信号处理及计算建模方法|李骁健,生于1978年。本科毕业于西北大学,博士毕业于中国科学院生物物理研究所。现在中国科学院深圳先进技术研究院任正高级工程师。主要研究植入式脑机接口技术,纳米神经调控技术以及神经拟态工程
  • 基金资助:
    广东省重点领域研发计划(2018B030331001);广东省重点领域研发计划(2018B030338001);国家重点研发计划(2018YFA0701400);国家重点研发计划(2017YFC1310503);国家自然科学基金(31700936);广东省博士启动项目(2017A030310496)

Progress in Devices and Materials for Implantable Multielectrode Arrays

Zhanhong Du(), Yi Lu, Pengfei Wei, Chunshan Deng, Xiaojian Li()   

  • Received:2020-07-01 Accepted:2020-08-11 Published:2020-08-17
  • Contact: Zhanhong Du,Xiaojian Li E-mail:zh.du@siat.ac.cn;xj.li@siat.ac.cn
  • Supported by:
    the Key-Area Research and Development Program of Guangdong Province(2018B030331001);the Key-Area Research and Development Program of Guangdong Province(2018B030338001);the National Key R & D Program of China(2018YFA0701400);the National Key R & D Program of China(2017YFC1310503);the National Nature Science Foundation of China(31700936);the Doctoral Initiation Project of the Guangdong Province(2017A030310496)

摘要:

人脑与电脑通过连续高通量的信息交互来实现深度融合是神经工程领域的重要发展愿景。脑机融合技术不但可以大幅提升运动残障、精神疾病、感知觉缺失能等多种疾病患者的治疗效果,更可以将电子计算机系统中存储的海量信息以及高速数值计算能力直接传递给人脑,从而赋予个人“超能力”。植入式神经电极阵列是发展宽带脑机融合智能系统所不可或缺的关键界面器件。一方面,植入式电极阵列可以同时保证大范围和高精度地记录神经元动作电位的精确发放时间和波形,为充分抽提神经信息,解读脑神经网络的活动奠定坚实基础。另一方面,借助植入式电极阵列对神经元进行高时空精度地信息写入,不但可以向脑内直接传入新信息,也可能改变神经精神疾病(例如帕金森氏症、癫痫和重度抑郁等)患者的异常神经网络活动,从而缓解症状或治疗疾病。电极阵列的微纳加工工艺、电极的理化特征及其与神经组织的界面效应是目前脑机接口技术前端研究的重要方向,而纳米材料和纳米器件等新技术在神经电子界面优化方面的重要作用也愈发明显。

关键词: 脑机接口, 生物电子医疗, 多电极阵列, 在体电生理, 纳米材料

Abstract:

The human brain comprises over 100 billion neurons that communicate with each other via electrical activities called action potentials. Sensory perception, cognition, and behavior all emerge from these activities. Neuroengineering is a developing interdisciplinary field that employs knowledge from neurobiology, electrical and electronic engineering, materials science and engineering, computer science, and many others. Neuroengineering aims to develop tools for understanding the mechanism of brain function at the circuit level, and to further the development of neuromodulation strategy and neuroprosthetics for motor, sensory, and mental rehabilitation from disabilities and illnesses.

For high spatial and temporal resolution interfacing with neurons in the brain, implantable multielectrode arrays (MEAs) are a key member of the family of neuroengineering devices, which are designed and fabricated for in vivo electrophysiology, deep brain stimulation, and brain-computer interfaces (BCIs). On the one hand, action potential recording from MEAs can indicate the subject's mental state and movement intentions, thus enabling the BCI technology to control external motor restoration devices such as robotic arms. On the other hand, neural stimulation electrodes can modulate abnormal neural activity and treat disorders like Parkinson's disease, epilepsy, and depression. The physical and chemical properties of the electrodes, nanofabrication of arrays, and electrode–tissue interface materials are all important research subjects in translational neuroscience studies, and the utilization of nanomaterials and nanodevices continuously improves neural electrode technologies.

At present, neural interface technology is confronting numerous challenges and opportunities, especially for in vivo neural circuit analysis, neuroelectronic medicine, and functional neuromodulation. The development of neural interface devices eagerly demands super-high-density, mesoscopic recording, minimal invasion, biosignal stability, and wireless interfacing. Achievement of these next-generation neural interface technology capabilities requires collaboration between neuroscientists, neurosurgeons, material scientists, microelectronic engineers, and many others.

Key words: Brain-computer interface, Bioelectronic medicine, Multielectrode array, In vivo electrophysiology, Nanomaterial

MSC2000: 

  • O649