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Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: A tool for synthesizing spike trains with realistic interference
Author(s): Smith, Leslie
Mtetwa, Nhamoinesu
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Keywords: Spike detection
Spike sorting
Synthetic data
Issue Date: Jan-2007
Date Deposited: 17-Jul-2014
Citation: Smith L & Mtetwa N (2007) A tool for synthesizing spike trains with realistic interference. Journal of Neuroscience Methods, 159 (1), pp. 170-180.
Abstract: Spike detection and spike sorting techniques are often difficult to assess because of the lack of ground truth data (i.e., spike timings for each neuron). This is particularly important for in vitro recordings where the signal to noise ratio is poor (as is the case for multi-electrode arrays at the bottom of a cell culture dish). We present an analysis of the transmission of intracellular signals from neurons to an extracellular electrode, and a set of MATLAB functions based on this analysis. These produce realistic signals from neighboring neurons as well as interference from more distant neurons, and Gaussian noise. They thus generate realistic but controllable synthetic signals (for which the ground truth is known) for assessing spike detection and spike sorting techniques. They can also be used to generate realistic (non-Gaussian) background noise. We use signals generated in this way to compare two automated spike-sorting techniques. The software is available freely on the web.
DOI Link: 10.1016/j.jneumeth.2006.06.019
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