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Multi-neuron intracellular recording in vivo via interacting autopatching robots

Authors :
Institute for Medical Engineering and Science
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Media Laboratory
McGovern Institute for Brain Research at MIT
Picower Institute for Learning and Memory
Kodandaramaiah, Suhasa Bangalore
Flores Plaza, Francisco Javier
Singer, Annabelle
Brown, Emery Neal
Boyden, Edward
Holst, Gregory L
Han, Xue
Forest, Craig R
Institute for Medical Engineering and Science
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Media Laboratory
McGovern Institute for Brain Research at MIT
Picower Institute for Learning and Memory
Kodandaramaiah, Suhasa Bangalore
Flores Plaza, Francisco Javier
Singer, Annabelle
Brown, Emery Neal
Boyden, Edward
Holst, Gregory L
Han, Xue
Forest, Craig R
Source :
eLife
Publication Year :
2018

Abstract

The activities of groups of neurons in a circuit or brain region are important for neuronal computations that contribute to behaviors and disease states. Traditional extracellular recordings have been powerful and scalable, but much less is known about the intracellular processes that lead to spiking activity. We present a robotic system, the multipatcher, capable of automatically obtaining blind whole-cell patch clamp recordings from multiple neurons simultaneously. The multipatcher significantly extends automated patch clamping, or ’autopatching’, to guide four interacting electrodes in a coordinated fashion, avoiding mechanical coupling in the brain. We demonstrate its performance in the cortex of anesthetized and awake mice. A multipatcher with four electrodes took an average of 10 min to obtain dual or triple recordings in 29% of trials in anesthetized mice, and in 18% of the trials in awake mice, thus illustrating practical yield and throughput to obtain multiple, simultaneous whole-cell recordings in vivo.

Details

Database :
OAIster
Journal :
eLife
Notes :
application/pdf
Publication Type :
Electronic Resource
Accession number :
edsoai.on1141886911
Document Type :
Electronic Resource