Evaluation and resolution of many challenges of neural spike sorting: a new sorter
Nathan J. Hall, David J. Herzfeld, Stephen G. Lisberger
Abstract
Electrophysiological recordings from multiple neurons across multiple channels pose great difficulty for spike sorting of single neurons. We propose methods that improve the ability to determine the number of individual neurons present in a recording and resolve near-simultaneous spike events from single neurons. We use ground-truth data sets to demonstrate the pros and cons of several current sorting algorithms and suggest strategies for determining the accuracy of spike sorting when ground-truth data are not available.
Topics & Concepts
Spike sortingSpike (software development)SortingComputer sciencePattern recognition (psychology)Binary numberArtificial intelligenceSpike trainAlgorithmMathematicsSoftware engineeringArithmeticNeural dynamics and brain functionNeuroscience and Neural EngineeringAdvanced Memory and Neural Computing