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A Novel 3D-Printed Multi-Drive System for Synchronous Electrophysiological Recording in Multiple Brain Regions.
Ma, Jun; Zhao, Zifang; Cui, Shuang; Liu, Feng-Yu; Yi, Ming; Wan, You.
Affiliation
  • Ma J; Neuroscience Research Institute, Peking University, Beijing, China.
  • Zhao Z; Neuroscience Research Institute, Peking University, Beijing, China.
  • Cui S; Neuroscience Research Institute, Peking University, Beijing, China.
  • Liu FY; Neuroscience Research Institute, Peking University, Beijing, China.
  • Yi M; Neuroscience Research Institute, Peking University, Beijing, China.
  • Wan Y; Neuroscience Research Institute, Peking University, Beijing, China.
Front Neurosci ; 13: 1322, 2019.
Article in En | MEDLINE | ID: mdl-31920492
ABSTRACT
Extracellular electrophysiology has been widely applied in neural network studies. Local field potentials and single-unit activities can be recorded with high-density electrodes, which facilitate the decoding of neural codes. However, the chronic multi-regional recording is still a challenging task for achieving high placement accuracy and long-term stability. Here, we present a novel electrode design with low-cost 3D-printed parts and custom printed circuits boards. This new design could facilitate precise electrode placement in multiple brain regions simultaneously and reduce the working time for surgical procedures as well. In this paper, the design and fabrication of the 3D printed multi-channel microdrive are explained in detail. We also show the result of high-quality electrophysiological recordings in eight pain-related areas from rats and the electrode placement accuracy. This novel 3D-printed multi-drive system could achieve synchronous electrophysiological recording in multiple brain regions and facilitate future neural network research.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Neurosci Year: 2019 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Neurosci Year: 2019 Document type: Article