Test of spike-sorting algorithms on the basis of simulated network data

Results of spike-sorting algorithms are usually compared with recorded signals which themselves underly interpretations, distortions and errors. Our approach is to provide and compare physiological extracellular potential data by a realistic cortical network simulation. For this purpose, we utilize...

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Bibliographic Details
Published in:Neurocomputing (Amsterdam) 2002-06, Vol.44, p.1119-1126
Main Authors: Menne, Kerstin M.L, Folkers, Andre, Malina, Thomas, Maex, Reinoud, Hofmann, Ulrich G
Format: Article
Language:English
Subjects:
Multisite recordings
Multiunit signals
Realistic modeling
Silicon probes
Spike detection
Tetrode data
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Summary:Results of spike-sorting algorithms are usually compared with recorded signals which themselves underly interpretations, distortions and errors. Our approach is to provide and compare physiological extracellular potential data by a realistic cortical network simulation. For this purpose, we utilize the neural simulator GENESIS and simulate a region of rat hippocampus containing 90 cells. We are able to “record” simulated extracellular potentials from “virtual electrodes” and produce test data closely resembling multisite neuronal recordings. Our realisitic, artificial data are complex and almost natural in appearance; however, current spike detection schemes appear unable to reliably detect all spikes produced.
ISSN:0925-2312
1872-8286
DOI:10.1016/S0925-2312(02)00432-0