A fully automated approach to spike sorting
| Autor: | Kye Y Lee, Loren M. Frank, Jason E. Chung, Jeremy F. Magland, Alex H. Barnett, Sarah Felix, Kedar G. Shah, Leslie Greengard, Vanessa Tolosa, Angela C. Tooker |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Male Standardization hippocampus Computer science media_common.quotation_subject Action Potentials cluster metrics Bioengineering spike sorting Bioinformatics computer.software_genre Article 03 medical and health sciences Automation Computer-Assisted 0302 clinical medicine Psychology Animals Quality (business) Cluster analysis reproducibility media_common Neurons Neurology & Neurosurgery General Neuroscience Scale (chemistry) Neurosciences Brain Signal Processing Computer-Assisted Rats automated cortex 030104 developmental biology Spike sorting Signal Processing Cognitive Sciences Spike (software development) Central processing unit Data mining Raw data computer 030217 neurology & neurosurgery Algorithms Software clustering |
| Zdroj: | Neuron, vol 95, iss 6 |
| Popis: | Summary Understanding the detailed dynamics of neuronal networks will require the simultaneous measurement of spike trains from hundreds of neurons (or more). Currently, approaches to extracting spike times and labels from raw data are time consuming, lack standardization, and involve manual intervention, making it difficult to maintain data provenance and assess the quality of scientific results. Here, we describe an automated clustering approach and associated software package that addresses these problems and provides novel cluster quality metrics. We show that our approach has accuracy comparable to or exceeding that achieved using manual or semi-manual techniques with desktop central processing unit (CPU) runtimes faster than acquisition time for up to hundreds of electrodes. Moreover, a single choice of parameters in the algorithm is effective for a variety of electrode geometries and across multiple brain regions. This algorithm has the potential to enable reproducible and automated spike sorting of larger scale recordings than is currently possible. |
| Databáze: | OpenAIRE |
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