Automated Intracellular Recording from Multiple Neurons in vivo
-
- Ota Keisuke
- RIKEN Brain Science Institute Japan Society for the Promotion of Science
-
- Matsumoto Takashi
- RIKEN Brain Science Institute
-
- Yazaki-Sugiyama Yoko
- OIST
-
- Suzuki Takayuki
- RIKEN Brain Science Institute
-
- Kamoshida Atsushi
- National Instruments Japan Corporation
-
- Murayama Masanori
- RIKEN Brain Science Institute
Bibliographic Information
- Other Title
-
- 多細胞からのIn vivo自動細胞内記録
- タサイボウ カラ ノ In vivo ジドウ サイボウ ナイキロク
Search this article
Abstract
Multiple in vivo intracellular recording is a useful technique for understanding how neurons and neural circuits function. However, this is formidable tasks for researchers. To overcome this difficulty, we developed an automated intracellular recording (AIR) system. The AIR system can automatically move an electrode in the brain, find a neuron, activate a brief high frequency current to penetrate the neuron and inject the optimal negative current to recovery from the penetration damage. We evaluated the performance of the AIR system in anesthetized head-restrained mice. The success rate for one electrode was 63% (n=11 electrodes). The average stable recording time was 56 min, and a maximum time was 193min. After stable intracellular recording from one neuron was finished, this system could continuously find another neuron and achieve the intracellular recording from it without changing the electrode. We could record from up to 4 neurons using 1 electrode. For multiple in vivo intracellular recording, we run 6 AIR systems in parallel and succeeded in simultaneous recording from 4 neurons; 2 neurons from the primary somatosensory and 2 neurons from the secondary motor area.
Journal
-
- IEEJ Transactions on Electronics, Information and Systems
-
IEEJ Transactions on Electronics, Information and Systems 134 (10), 1506-1514, 2014
The Institute of Electrical Engineers of Japan
- Tweet
Keywords
Details 詳細情報について
-
- CRID
- 1390282679585393664
-
- NII Article ID
- 130004694091
-
- NII Book ID
- AN10065950
-
- ISSN
- 13488155
- 03854221
-
- NDL BIB ID
- 025855016
-
- Text Lang
- ja
-
- Data Source
-
- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
-
- Abstract License Flag
- Disallowed