AUTHOR=Spacek Martin A., Blanche Tim , Swindale Nick 

TITLE=Python for large-scale electrophysiology

JOURNAL=Frontiers in Neuroinformatics

VOLUME=2

YEAR=2009

URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/neuro.11.009.2008

DOI=10.3389/neuro.11.009.2008

ISSN=1662-5196

ABSTRACT=<p>Electrophysiology is increasingly moving towards highly parallel recording techniques which generate large data sets. We record extracellularly <italic>in vivo</italic> in cat and rat visual cortex with 54-channel silicon polytrodes, under time-locked visual stimulation, from localized neuronal populations within a cortical column. To help deal with the complexity of generating and analysing these data, we used the Python programming language to develop three software projects: one for temporally precise visual stimulus generation (“dimstim”); one for electrophysiological waveform visualization and spike sorting (“spyke”); and one for spike train and stimulus analysis (“neuropy”). All three are open source and available for download (<monospace><uri xlink:href="http://swindale.ecc.ubc.ca/code" xmlns:xlink="http://www.w3.org/1999/xlink">http://swindale.ecc.ubc.ca/code</uri></monospace>). The requirements and solutions for these projects differed greatly, yet we found Python to be well suited for all three. Here we present our software as a showcase of the extensive capabilities of Python in neuroscience.</p>