Online template-matching based spike sorting for microelectrode arrays with hundreds of channels
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1
École Normale Supérieure, France
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2
UMR7210 Institut de la Vision, France
Understanding how assemblies of neurons encode information requires recording of large populations of cells in the brain. In recent years, multi-electrode arrays and large silicon probes have been developed to record simultaneously from thousands of electrodes packed with a high density. To tackle the fact that these new devices challenge the classical way to perform spike sorting, we recently developed a fast and accurate spike sorting algorithm (available as an open source software, called SpyKING CIRCUS), validated both with in vivo and in vitro ground truth experiments. The software, performing a smart clustering of the spike waveforms followed by a greedy template-matching reconstruction of the signal, is able to scale to up to 4225 channels in parallel, solving the problem of temporally overlapping spikes. It thus appears as a general solution to sort, offline, spikes from large-scale extracellular recordings.
In this work, we implemented this algorithm in an “online” mode, sorting spikes in real time while the data are acquired, to allow closed-loop experiments for high density electrophysiology. To achieve such a goal, we built a robust architecture for distributed asynchronous computations and we proposed a modified algorithm that is composed of two concurrent processes running continuously: 1) “a template-finding” process to extract the cell templates (i.e. the pattern of activity evoked over many electrodes when one neuron fires an action potential) over the recent time course; 2) a “template-matching” process where the templates are matched onto the raw data to identify the spikes. Templates are updated online with a density-based clustering algorithm adapted for data streams, to keep track of drifts over time. A key advantage of our implementation is to be parallelized over a computing cluster to use optimally the computing resources: all the different processing steps of the algorithms (whitening, filtering, spike detection, template identification and fit) can be distributed according to the computational needs. Our software is therefore a promising solution for future closed-loop experiments involving recordings with hundreds of electrodes.
Keywords:
multielectrode array,
data analysis,
spike sorting,
Online analysis,
closed-loop stimulation
Conference:
MEA Meeting 2018 | 11th International Meeting on Substrate Integrated Microelectrode Arrays, Reutlingen, Germany, 4 Jul - 6 Jul, 2018.
Presentation Type:
Poster Presentation
Topic:
Stimulation strategies
Citation:
Lefebvre
B,
Stimberg
M,
Marre
O and
Yger
P
(2019). Online template-matching based spike sorting for microelectrode arrays with hundreds of channels.
Conference Abstract:
MEA Meeting 2018 | 11th International Meeting on Substrate Integrated Microelectrode Arrays.
doi: 10.3389/conf.fncel.2018.38.00031
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Received:
18 Mar 2018;
Published Online:
17 Jan 2019.
*
Correspondence:
Mr. Baptiste Lefebvre, École Normale Supérieure, Paris, France, baptiste.lefebvre@ens.fr