Automatic spike sorting evaluation: A website based community approach
Felix Franke (ETH Zürich, Bio Engineering Laboratory (BEL)), Philipp Meier (School for Electrical Engineering and Computer Science, Berlin Institute of Technology, Germany), Andrey Sobolev (Biologie II, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany), Espen Hagen (Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway), Andreas Hierlemann (ETH Zürich, Bio Engineering Laboratory (BEL)), Klaus Obermayer (Bernstein Center for Computational Neuroscience, Berlin, Germany), Gaute T Einevoll (Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway), Thomas Wachtler (Biologie II, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany)
Here, we develop a framework for automated spike sorting evaluation based on several different benchmark datasets used in recent publications. The framework is implemented on a website that allows the user to download benchmark files, upload their sorting results, and compare the performance of their sorting algorithm to those of other users. Furthermore, users can also upload their own benchmark datasets and make them available to the community. We hope that the website will help in comparing the performance of different spike sorting algorithms and foster the development of new ones.
The underlying framework, i.e., website frontend and evaluation backend, can be generalized to other, similar, algorithm evaluation problems, such as encountered in EEG data analysis.
The website is available at http://www.g-node.org/spike.
Supported by the Research Council of Norway (NevroNor, eScience, Notur), by INCF through its German Node (BMBF grant 01GQ0801), and by the Deutsche Forschungs Gemeinschaft (DFG) with grant GRK 1589/1.
Einevoll, G. T., Franke, F., Hagen, E., Pouzat, C., and Harris, K. D. (2011). Towards reliable spike-train recordings from thousands of neurons with multielectrodes. Current Opinion in Neurobiology 27, 1–7.
Lewicki, M. S. (1998). A review of methods for spike sorting: the detection and classification of neural action potentials. Network (Bristol, England) 9, R53–R78