Narendra Mukherjee
Graduate Program in Neuroscience, Brandeis University, Waltham, MA, USA

Joseph Wachutka
Graduate Program in Neuroscience, Brandeis University, Waltham, MA, USA

Donald B Katz
Department of Psychology, Brandeis University, Waltham, MA, USA
Volen National Center for Complex Systems, Brandeis University, Waltham, MA, USA

Abstract

In-vivo electrophysiology, the recording of neurons in the brains of awake, behaving animals, is currently undergoing paradigm shifts. There is a push towards moving to open-source technologies that can: 1) be adjusted to specific experiments; 2) be shared with ease; and 3) more affordably record from larger numbers of electrodes simultaneously. Here we describe our construction of a system that satisfies these three desirable properties using the scientific Python stack and Linux. Using a Raspberry Pi to control experimental paradigms, we build a completely open-source, HDF5-based analysis (spike sorting) toolkit in Python. This toolkit can be easily parallelized and scales to incorporate increasing electrode counts and longer recordings. Our rig costs about \$5000, an order of magnitude less than many comparable commercially available electrophysiology systems.

Keywords

in-vivo electrophysiology, Python, open-source, HDF5, spike sorting

DOI

10.25080/shinma-7f4c6e7-00e

Bibtex entry

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Copyright © 2017 Narendra Mukherjee et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.