title: Python for large-scale electrophysiology.
abstract: Electrophysiology is increasingly moving towards highly parallel recording techniques which generate large data sets. We record extracellularly in vivo 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 (http://swindale.ecc.ubc.ca/code). 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.
authors.affiliation: Ophthalmology and Visual Sciences, University of British Columbia Vancouver, BC, Canada.
authors.forename: Martin
authors.initials: M
authors.lastname: Spacek
authors.forename: Tim
authors.initials: T
authors.lastname: Blanche
authors.forename: Nicholas
authors.initials: N
authors.lastname: Swindale