MEArec: A Fast and Customizable Testbench Simulator for Ground-truth Extracellular Spiking Activity
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SOFTWARE ORIGINAL ARTICLE
MEArec: A Fast and Customizable Testbench Simulator for Ground-truth Extracellular Spiking Activity Alessio Paolo Buccino1,2
· Gaute Tomas Einevoll1,3
© The Author(s) 2020
Abstract When recording neural activity from extracellular electrodes, both in vivo and in vitro, spike sorting is a required and very important processing step that allows for identification of single neurons’ activity. Spike sorting is a complex algorithmic procedure, and in recent years many groups have attempted to tackle this problem, resulting in numerous methods and software packages. However, validation of spike sorting techniques is complicated. It is an inherently unsupervised problem and it is hard to find universal metrics to evaluate performance. Simultaneous recordings that combine extracellular and patch-clamp or juxtacellular techniques can provide ground-truth data to evaluate spike sorting methods. However, their utility is limited by the fact that only a few cells can be measured at the same time. Simulated ground-truth recordings can provide a powerful alternative mean to rank the performance of spike sorters. We present here MEArec, a Pythonbased software which permits flexible and fast simulation of extracellular recordings. MEArec allows users to generate extracellular signals on various customizable electrode designs and can replicate various problematic aspects for spike sorting, such as bursting, spatio-temporal overlapping events, and drifts. We expect MEArec will provide a common testbench for spike sorting development and evaluation, in which spike sorting developers can rapidly generate and evaluate the performance of their algorithms. Keywords Spike sorting testbench · Benchmark data · Extracellular recordings simulator · Open-source software
Introduction Extracellular neural electrophysiology is one of the most used and important techniques to study brain function. It consists of measuring the electrical activity of neurons from electrodes in the extracellular space, that pick up the electrical activity of surrounding neurons. To communicate with each other, neurons generate action potentials, which can be identified in the recorded signals as fast potential transients called spikes.
Alessio Paolo Buccino
[email protected]; [email protected] 1
Centre for Integrative Neuroplasticity (CINPLA), University of Oslo, Oslo, Norway
2
Present address: Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Z¨urich, Z¨urich, Switzerland
3
Faculty of Science and Technology, Norwegian University ˚ Norway of Life Sciences, As,
Since electrodes can record the extracellular activity of several surrounding neurons, a processing step called spike sorting is needed. Historically this has required manual curation of the data, which in addition to being time consuming also introduces human bias to data interpretations. In recent years, several automated spike sorters have been developed to alleviate this problems. Spike sorting algorithms (Rey et al. 2015;
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