A low-cost, multiplexed electrophysiology system for chronic μECoG recordings in rodents.

Published

Journal Article

Micro-Electrocorticography (μECoG) offers a minimally invasive, high resolution interface with large areas of cortex. However, large arrays of electrodes with many contacts that are individually wired to external recording systems are cumbersome and make chronic recording in freely behaving small animals challenging. Multiplexed headstages overcome this limitation by combining the signals from many electrodes to a smaller number of connections directly on the animal's head. Commercially available multiplexed headstages provide high performance integrated amplification, multiplexing and analog to digital conversion. However, the cost of these systems can be prohibitive for small labs or for experiments that require a large number of animals to be continuously recorded at the same time. Here we have developed a multiplexed 60-channel headstage amplifier optimized to chronically record electrophysiological signals from high-density μECoG electrode arrays. A single, ultraflexible (2 mm thickness) microHDMI cable provided the data interface. Using low cost components, we have reduced the cost of the multiplexed headstage to ~$125. Paired with a custom interface printed circuit board (PCB) and a general purpose data acquisition system (M-series DAQ, National Instruments), an inexpensive and customizable electrophysiology system is assembled. Open source LabVIEW software that we have previously released controlled the system. It can also be used with other open source neural data acquisition packages. Combined, we have presented a scalable, low-cost platform for high-channel count electrophysiology.

Full Text

Duke Authors

Cited Authors

  • Wang, J; Trumpis, M; Insanally, M; Froemke, R; Viventi, J

Published Date

  • January 2014

Published In

Volume / Issue

  • 2014 /

Start / End Page

  • 5256 - 5259

PubMed ID

  • 25571179

Pubmed Central ID

  • 25571179

International Standard Serial Number (ISSN)

  • 1557-170X

Digital Object Identifier (DOI)

  • 10.1109/EMBC.2014.6944811

Language

  • eng