Automated patch clamp electrophysiology of neurons in the living brain

Whole-cell patch clamp electrophysiology of neurons in vivo enables the recording of electrical events in cells with great precision, and supports a wide diversity of cellular morphological and molecular analysis experiments. However, high levels of skill are required in order to perform in vivo patching, and the process is time-consuming and painstaking. An automated in vivo patching robot would not only empower a great number of neuroscientists to perform such experiments, but would also open up fundamentally new kinds of experiment enabled by the resultant high throughput. We discovered that...

Whole-cell patch clamp electrophysiology of neurons in vivo enables the recording of electrical events in cells with great precision, and supports a wide diversity of cellular morphological and molecular analysis experiments. However, high levels of skill are required in order to perform in vivo patching, and the process is time-consuming and painstaking. An automated in vivo patching robot would not only empower a great number of neuroscientists to perform such experiments, but would also open up fundamentally new kinds of experiment enabled by the resultant high throughput. We discovered that in vivo blind whole cell patch clamp electrophysiology could be implemented as a straightforward algorithm, and developed an automated robotic system capable of performing this algorithm. We validated the performance of our robot in both the cortex and hippocampus of anesthetized and awake mice. Our robot achieves yields, cell recording qualities, and operational speeds that are comparable to, or exceed, those of experienced human investigators, and is simple and inexpensive to implement.  Recent developments include coupling "autopatching" to optogenetics, recording multiple neurons simultaneously, and patching deep structures including mouse brain stem.

Event Details

Date/Time:

  • Date: 
    Wednesday, October 16, 2013 - 11:00am

Location:
IBB Room 1128