Hasan Md Fayad, Berdichevsky Yevgeny
Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, PA 18015, USA.
Bioengineering Program, Lehigh University, Bethlehem, PA 18015, USA.
Micromachines (Basel). 2016 Sep 5;7(9):157. doi: 10.3390/mi7090157.
Neural circuits are responsible for the brain's ability to process and store information. Reductionist approaches to understanding the brain include isolation of individual neurons for detailed characterization. When maintained in vitro for several days or weeks, dissociated neurons self-assemble into randomly connected networks that produce synchronized activity and are capable of learning. This review focuses on efforts to control neuronal connectivity in vitro and construct living neural circuits of increasing complexity and precision. Microfabrication-based methods have been developed to guide network self-assembly, accomplishing control over in vitro circuit size and connectivity. The ability to control neural connectivity and synchronized activity led to the implementation of logic functions using living neurons. Techniques to construct and control three-dimensional circuits have also been established. Advances in multiple electrode arrays as well as genetically encoded, optical activity sensors and transducers enabled highly specific interfaces to circuits composed of thousands of neurons. Further advances in on-chip neural circuits may lead to better understanding of the brain.
神经回路负责大脑处理和存储信息的能力。理解大脑的还原论方法包括分离单个神经元以进行详细表征。解离的神经元在体外培养数天或数周后,会自组装成随机连接的网络,产生同步活动并具备学习能力。本综述聚焦于在体外控制神经元连接性以及构建复杂度和精度不断提高的活体神经回路的相关研究。基于微加工的方法已被开发出来以引导网络自组装,实现对体外回路大小和连接性的控制。控制神经连接性和同步活动的能力促使人们利用活体神经元实现逻辑功能。构建和控制三维回路的技术也已确立。多电极阵列以及基因编码的光学活性传感器和换能器的进展,使得能够与由数千个神经元组成的回路实现高度特异性的接口。片上神经回路的进一步进展可能会增进对大脑的理解。