Whole-cell patch-clamp electrophysiology of neurons is a gold-standard technique for high-fidelity analysis of the biophysical mechanisms of neural computation and pathology, but it requires great skill to perform. We have developed a robot that automatically performs patch clamping in vivo, algorithmically detecting cells by analyzing the temporal sequence of electrode impedance changes. We demonstrate good yield, throughput and quality of automated intracellular recording in mouse cortex and hippocampus.
Bibliographical noteFunding Information:
We would like to acknowledge electronic switch design by G. Holst at Georgia Tech. E.S.B. acknowledges funding by the US National Institutes of Health (NIH) Director′s New Innovator Award (DP2OD002002) and the NIH EUREKA Award program (1R01NS075421) and other NIH grants, the New York Stem Cell Foundation Robertson Neuroscience Award, the National Science Foundation (NSF) CAREER award (CBET 1053233) and other NSF grants, Jerry and Marge Burnett, Google, Human Frontiers Science Program, MIT McGovern Institute and McGovern Institute Neurotechnology Award Program, MIT Media Lab, NARSAD, Paul Allen Distinguished Investigator Award, Alfred P. Sloan Foundation and Wallace H. Coulter Foundation. C.R.F. acknowledges funding by the NSF (CISE 1110947, EHR 0965945) as well as the American Heart Association (10GRNT4430029), Georgia Economic Development Association, Wallace H. Coulter Foundation, Center for Disease Control and NSF National Nanotechnology Infrastructure Network (NNIN) and from the Georgia Tech Institute for BioEngineering and BioSciences Junior Faculty Award, Technology Fee Fund, Invention Studio and George W. Woodruff School of Mechanical Engineering.