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A robot for high yield electrophysiology and morphology of single neurons in vivo

Author

Listed:
  • Lu Li

    (Allen Institute for Brain Science)

  • Benjamin Ouellette

    (Allen Institute for Brain Science)

  • William A. Stoy

    (Wallace H. Coulter Department of Biomedical Engineering)

  • Emma J. Garren

    (Allen Institute for Brain Science)

  • Tanya L. Daigle

    (Allen Institute for Brain Science)

  • Craig R. Forest

    (Wallace H. Coulter Department of Biomedical Engineering
    George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

  • Christof Koch

    (Allen Institute for Brain Science)

  • Hongkui Zeng

    (Allen Institute for Brain Science)

Abstract

Single-cell characterization and perturbation of neurons provides knowledge critical to addressing fundamental neuroscience questions including the structure–function relationship and neuronal cell-type classification. Here we report a robot for efficiently performing in vivo single-cell experiments in deep brain tissues optically difficult to access. This robot automates blind (non-visually guided) single-cell electroporation (SCE) and extracellular electrophysiology, and can be used to characterize neuronal morphological and physiological properties of, and/or manipulate genetic/chemical contents via delivering extraneous materials (for example, genes) into single neurons in vivo. Tested in the mouse brain, our robot successfully reveals the full morphology of single-infragranular neurons recorded in multiple neocortical regions, as well as deep brain structures such as hippocampal CA3, with high efficiency. Our robot thus can greatly facilitate the study of in vivo full morphology and electrophysiology of single neurons in the brain.

Suggested Citation

  • Lu Li & Benjamin Ouellette & William A. Stoy & Emma J. Garren & Tanya L. Daigle & Craig R. Forest & Christof Koch & Hongkui Zeng, 2017. "A robot for high yield electrophysiology and morphology of single neurons in vivo," Nature Communications, Nature, vol. 8(1), pages 1-10, August.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms15604
    DOI: 10.1038/ncomms15604
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    Cited by:

    1. Meng Wang & Ke Liu & Junxia Pan & Jialin Li & Pei Sun & Yongsheng Zhang & Longhui Li & Wenyan Guo & Qianqian Xin & Zhikai Zhao & Yurong Liu & Zhenqiao Zhou & Jing Lyu & Ting Zheng & Yunyun Han & Chunq, 2022. "Brain-wide projection reconstruction of single functionally defined neurons," Nature Communications, Nature, vol. 13(1), pages 1-14, December.

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