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Autonomous patch-clamp robot for functional characterization of neurons in vivo: development and application to mouse visual cortex.
Holst, Gregory L; Stoy, William; Yang, Bo; Kolb, Ilya; Kodandaramaiah, Suhasa B; Li, Lu; Knoblich, Ulf; Zeng, Hongkui; Haider, Bilal; Boyden, Edward S; Forest, Craig R.
Afiliación
  • Holst GL; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology , Atlanta, Georgia.
  • Stoy W; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology , Atlanta, Georgia.
  • Yang B; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology , Atlanta, Georgia.
  • Kolb I; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology , Atlanta, Georgia.
  • Kodandaramaiah SB; Department of Mechanical Engineering, University of Minnesota , Minneapolis, Minnesota.
  • Li L; Allen Institute for Brain Science , Seattle, Washington.
  • Knoblich U; Allen Institute for Brain Science , Seattle, Washington.
  • Zeng H; Allen Institute for Brain Science , Seattle, Washington.
  • Haider B; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology , Atlanta, Georgia.
  • Boyden ES; Media Arts and Sciences, Massachusetts Institute of Technology , Cambridge, Massachusetts.
  • Forest CR; McGovern Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts.
J Neurophysiol ; 121(6): 2341-2357, 2019 06 01.
Article en En | MEDLINE | ID: mdl-30969898
Patch clamping is the gold standard measurement technique for cell-type characterization in vivo, but it has low throughput, is difficult to scale, and requires highly skilled operation. We developed an autonomous robot that can acquire multiple consecutive patch-clamp recordings in vivo. In practice, 40 pipettes loaded into a carousel are sequentially filled and inserted into the brain, localized to a cell, used for patch clamping, and disposed. Automated visual stimulation and electrophysiology software enables functional cell-type classification of whole cell-patched cells, as we show for 37 cells in the anesthetized mouse in visual cortex (V1) layer 5. We achieved 9% yield, with 5.3 min per attempt over hundreds of trials. The highly variable and low-yield nature of in vivo patch-clamp recordings will benefit from such a standardized, automated, quantitative approach, allowing development of optimal algorithms and enabling scaling required for large-scale studies and integration with complementary techniques. NEW & NOTEWORTHY In vivo patch-clamp is the gold standard for intracellular recordings, but it is a very manual and highly skilled technique. The robot in this work demonstrates the most automated in vivo patch-clamp experiment to date, by enabling production of multiple, serial intracellular recordings without human intervention. The robot automates pipette filling, wire threading, pipette positioning, neuron hunting, break-in, delivering sensory stimulus, and recording quality control, enabling in vivo cell-type characterization.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Corteza Visual / Robótica / Técnicas de Placa-Clamp / Fenómenos Electrofisiológicos / Neuronas Tipo de estudio: Guideline Límite: Animals Idioma: En Revista: J Neurophysiol Año: 2019 Tipo del documento: Article País de afiliación: Georgia Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Corteza Visual / Robótica / Técnicas de Placa-Clamp / Fenómenos Electrofisiológicos / Neuronas Tipo de estudio: Guideline Límite: Animals Idioma: En Revista: J Neurophysiol Año: 2019 Tipo del documento: Article País de afiliación: Georgia Pais de publicación: Estados Unidos