Workflow automation of electrophysiological data analysis in receptive field mapping
Bengt Ljungquist (Neuronano Research Center, Lund University)
To address this problem, a number of automatic spike-sorting methods have been suggested previously. However, their overall performance is relatively poor as they have been organized as single tasks. In this work we show how spike-sorting may be automated as one step of a larger workflow-like analysis using a computer program written in MATLAB. Further steps in this workflow include storing the recordings in a database to facilitate meta-data based analysis, peristimulus evoked potential and spike train analysis per stimulus site as well as visualization and plotting of the analysis.
We have applied this analysis to a receptive field mapping of nociceptive and tactile stimuli in order to characterize changes in nociceptive and tactile input to neurons in primary somatosensory cortex (SI) during the development of hyperalgesia in awake, freely moving rats. The results have been checked manually and yield results in par with manual analysis and spike sorting. Single units are readily extracted from multi-unit spike trains. Remarkably, the time required to perform the analysis is reduced from a month to a couple of hours.
The main benefits of this work are that we may now address complex research problems and perform data mining of the electrophysiological data, which has not been previously possible, thus providing a basis for rapid analysis and direct feedback to the experimental set-up in the context of performing electrophysiological recordings in future research.