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Micromachines 2016, 7(9), 157;

Neural Circuits on a Chip

Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, PA 18015, USA
Bioengineering Program, Lehigh University, Bethlehem, PA 18015, USA
Author to whom correspondence should be addressed.
Academic Editor: Nikos Chronis
Received: 22 July 2016 / Revised: 20 August 2016 / Accepted: 29 August 2016 / Published: 5 September 2016
(This article belongs to the Special Issue MEMS/NEMS for Neuroscience)
Full-Text   |   PDF [10234 KB, uploaded 5 September 2016]   |  


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. View Full-Text
Keywords: neuron; culture; multiple electrode array (MEA); microstamping; optogenetic; microchannel; axon; circuit neuron; culture; multiple electrode array (MEA); microstamping; optogenetic; microchannel; axon; circuit

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Hasan, M.F.; Berdichevsky, Y. Neural Circuits on a Chip. Micromachines 2016, 7, 157.

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