Mesh electronics: a new paradigm for tissue-like brain probes.
Mesh electronics: a new paradigm for tissue-like brain probes.
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DOI：
10.1016/j.conb.2017.11.007
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发表时间：
2018-06
影响因子：
5.7
通讯作者：
Lieber CM
中科院分区：
文献类型：
--
作者：
Hong G;Yang X;Zhou T;Lieber CM
现有的用于理解大脑和治疗神经系统疾病的植入式神经技术具有固有的特性，限制了它们以单神经元时空分辨率实现长期稳定的大脑接口的能力。这些限制反映了活体脑组织和非活体神经探针的结构和机械特性之间的二分法。为了弥合神经网络和电子网络之间的差距，我们引入了网状电子探针的新概念，其设计具有结构和机械特性，使植入物开始像神经组织一样“看起来和表现”。注射器植入的网状电子器件实现了具有神经吸引力且不受慢性免疫反应影响的探针，并且能够在单神经元水平上稳定地长期映射和调节大脑活动。这篇综述通过强调网状电子器件的组织样设计、注射器辅助输送、无缝神经组织集成和单神经元水平长期记录稳定性，提供了网状电子器件 10 年发展的历史概述。我们还提供有关神经科学和神经病学的独特近期机会和未来方向的见解，这些机会和未来方向现在可用于或预期可用于网状电子神经技术。
Existing implantable neurotechnologies for understanding the brain and treating neurological diseases have intrinsic properties that have limited their capability to achieve chronically-stable brain interfaces with single-neuron spatiotemporal resolution. These limitations reflect what has been dichotomy between the structure and mechanical properties of living brain tissue and non-living neural probes. To bridge the gap between neural and electronic networks, we have introduced the new concept of mesh electronics probes designed with structural and mechanical properties such that the implant begins to ‘look and behave’ like neural tissue. Syringe-implanted mesh electronics have led to the realization of probes that are neuro-attractive and free of the chronic immune response, as well as capable of stable long-term mapping and modulation of brain activity at the single-neuron level. This review provides a historical overview of a 10-year development of mesh electronics by highlighting the tissue-like design, syringe-assisted delivery, seamless neural tissue integration, and single-neuron level chronic recording stability of mesh electronics. We also offer insights on unique near-term opportunities and future directions for neuroscience and neurology that now are available or expected for mesh electronics neurotechnologies.
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影响因子：
38.3
作者：
通讯作者：
--
影响因子：
38.3
作者：
Liu J;Fu TM;Cheng Z;Hong G;Zhou T;Jin L;Duvvuri M;Jiang Z;Kruskal P;Xie C;Suo Z;Fang Y;Lieber CM
通讯作者：
Lieber CM
影响因子：
38.3
作者：
通讯作者：
--
提高神经元群体记录的数据质量。
影响因子：
25
作者：
Harris KD;Quiroga RQ;Freeman J;Smith SL
通讯作者：
Smith SL
影响因子：
3
作者：
Heffer, Leon F.;Fallon, James B.
通讯作者：
Fallon, James B.