scholarly journals Fast and accurate spike sorting in vitro and in vivo for up to thousands of electrodes

2016 ◽  
Author(s):  
Pierre Yger ◽  
Giulia L.B. Spampinato ◽  
Elric Esposito ◽  
Baptiste Lefebvre ◽  
Stéphane Deny ◽  
...  
Keyword(s):  
Template Matching ◽  
Large Scale ◽  
Ground Truth ◽  
Spike Sorting ◽  
Electrode Arrays ◽  
Ground Truth Data ◽  
Sorting Problem ◽  
Large Populations

AbstractUnderstanding how assemblies of neurons encode information requires recording large populations of cells in the brain. In recent years, multi-electrode arrays and large silicon probes have been developed to record simultaneously from hundreds or thousands of electrodes packed with a high density. However, these new devices challenge the classical way to do spike sorting. Here we developed a new method to solve these issues, based on a highly automated algorithm to extract spikes from extracellular data, and show that this algorithm reached near optimal performance both in vitro and in vivo. The algorithm is composed of two main steps: 1) a “template-finding” phase to extract the cell templates, i.e. the pattern of activity evoked over many electrodes when one neuron fires an action potential; 2) a “template-matching” phase where the templates were matched to the raw data to find the location of the spikes. The manual intervention by the user was reduced to the minimal, and the time spent on manual curation did not scale with the number of electrodes. We tested our algorithm with large-scale data from in vitro and in vivo recordings, from 32 to 4225 electrodes. We performed simultaneous extracellular and patch recordings to obtain “ground truth” data, i.e. cases where the solution to the sorting problem is at least partially known. The performance of our algorithm was always close to the best expected performance. We thus provide a general solution to sort spikes from large-scale extracellular recordings.

scholarly journals A spike sorting toolbox for up to thousands of electrodes validated with ground truth recordings in vitro and in vivo

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Pierre Yger ◽  
Giulia LB Spampinato ◽  
Elric Esposito ◽  
Baptiste Lefebvre ◽  
Stéphane Deny ◽  
...  
Keyword(s):  
Large Scale ◽  
Ground Truth ◽  
Multielectrode Arrays ◽  
Signal To Noise ◽  
Ground Truth Data ◽  
Sorting Problem ◽  
Expected Performance ◽  
Large Ensembles

In recent years, multielectrode arrays and large silicon probes have been developed to record simultaneously between hundreds and thousands of electrodes packed with a high density. However, they require novel methods to extract the spiking activity of large ensembles of neurons. Here, we developed a new toolbox to sort spikes from these large-scale extracellular data. To validate our method, we performed simultaneous extracellular and loose patch recordings in rodents to obtain ‘ground truth’ data, where the solution to this sorting problem is known for one cell. The performance of our algorithm was always close to the best expected performance, over a broad range of signal-to-noise ratios, in vitro and in vivo. The algorithm is entirely parallelized and has been successfully tested on recordings with up to 4225 electrodes. Our toolbox thus offers a generic solution to sort accurately spikes for up to thousands of electrodes.

scholarly journals MEArec: A Fast and Customizable Testbench Simulator for Ground-truth Extracellular Spiking Activity

2020 ◽  
Vol 19 (1) ◽  
pp. 185-204 ◽  
Author(s):  
Alessio Paolo Buccino ◽  
Gaute Tomas Einevoll
Keyword(s):  
Ground Truth ◽  
Spike Sorting ◽  
Ground Truth Data ◽  
Extracellular Signals ◽  
Software Packages ◽  
Processing Step ◽  
Important Processing ◽  
Spatio Temporal

AbstractWhen 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 , a Python-based software which permits flexible and fast simulation of extracellular recordings. 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 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.

scholarly journals MEArec: a fast and customizable testbench simulator for ground-truth extracellular spiking activity

2019 ◽  
Author(s):  
Alessio P. Buccino ◽  
Gaute T. Einevoll
Keyword(s):  
Ground Truth ◽  
Spike Sorting ◽  
Ground Truth Data ◽  
Extracellular Signals ◽  
Software Packages ◽  
Processing Step ◽  
Important Processing ◽  
Spatio Temporal

AbstractWhen 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 Python-based 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.

scholarly journals Reconstruction of in-vivo subthreshold activity of single neurons from large-scale spiking recordings

2019 ◽  
Author(s):  
Stylianos Papaioannou ◽  
André Marques Smith ◽  
David Eriksson
Keyword(s):  
Membrane Potential ◽  
Large Scale ◽  
Ground Truth ◽  
Brain Structures ◽  
Single Neurons ◽  
Ground Truth Data ◽  
Large Populations ◽  
Subthreshold Activity ◽  
Spiking Activity

SummaryCurrent developments in the manufacturing of silicon probes allow recording of spikes from large populations of neurons from several brain structures in freely moving animals. It is still, however, technically challenging to record the membrane potential from awake behaving animals. Routine access to the subthreshold activity of neurons would be of great value in order to understand the role of, for example, neuronal integration, oscillations, and excitability. Here we have developed a framework for reconstructing the subthreshold activity of single neurons using the spiking activity from large neuronal populations. The reconstruction accuracy and reliability have been evaluated with ground truth data provided from simultaneous patch clamp membrane potential recordings in-vivo. Given the abundance of large-scale spike recordings in the contemporary systems neuroscience society, this approach provides a general access to the subthreshold activity and hence could shed light on the intricate mechanisms of the genesis of spiking activity.

scholarly journals How do spike collisions affect spike sorting performance?

2021 ◽  
Author(s):  
Samuel Garcia ◽  
Alessio Buccino ◽  
Pierre Yger
Keyword(s):  
Template Matching ◽  
Ground Truth ◽  
Spatial Density ◽  
Neuron Activity ◽  
Spike Sorting ◽  
Extracellular Signals ◽  
New Generation ◽  
Single Neuron Activity

Recently, a new generation of devices have been developed to record neural activity simultaneously from hundreds of electrodes with a very high spatial density, both for in vitro and in vivo applications. While these advances enable to record from many more cells, they also dramatically increase the amount overlapping "synchronous" spikes (colliding in space and/or in time), challenging the already complicated process of spike sorting (i.e. extracting isolated single-neuron activity from extracellular signals). In this work, we used synthetic ground-truth recordings to quantitatively benchmark the performance of state-of-the-art spike sorters focusing specifically on spike collisions. Our results show that while modern template-matching based algorithms are more accurate than density-based approaches, all methods, to some extent, failed to detect synchronous spike events of neurons with similar extracellular signals. Interestingly, the performance of the sorters is not largely affected by the the spiking activity in the recordings, with respect to average firing rates and spike-train correlation levels.

scholarly journals D.sort: template based automatic spike sorting tool

2018 ◽  
Author(s):  
Madeny Belkhiri ◽  
Duda Kvitsiani
Keyword(s):  
Template Matching ◽  
Ground Truth ◽  
Sorting Algorithm ◽  
Processing Unit ◽  
Spike Sorting ◽  
Ground Truth Data ◽  
Objective Metrics ◽  
Movement Artifacts ◽  
Freely Behaving ◽  
The Individual

AbstractUnderstanding how populations of neurons represent and compute internal or external variables requires precise and objective metrics for tracing the individual spikes that belong to a given neuron. Despite recent progress in the development of accurate and fast spike sorting tools, the scarcity of ground truth data makes it difficult to settle on the best performing spike sorting algorithm. Besides, the use of different configurations of electrodes and ways to acquire signal (e.g. anesthetized, head fixed, freely behaving animal recordings, tetrode vs. silicone probes, etc.) makes it even harder to develop a universal spike sorting tool that will perform well without human intervention. Some of the prevalent problems in spike sorting are: units separating due to drift, clustering bursting cells, and dealing with nonstationarity in background noise. The last is particularly problematic in freely behaving animals where the noises from the electrophysiological activity of hundreds or thousands of neurons are intermixed with noise arising from movement artifacts. We address these problems by developing a new spike sorting tool that is based on a template matching algorithm. The spike waveform templates are used to perform normalized cross correlation (NCC) with an acquired signal for spike detection. The normalization addresses problems with drift, bursting, and nonstationarity of noise and provides normative scoring to compare different units in terms of cluster quality. Our spike sorting algorithm, D.sort, runs on the graphic processing unit (GPU) to accelerate computations. D.sort is a freely available software package (https://github.com/1804MB/Kvistiani-lab_Dsort).

scholarly journals Neurophysiology of the Developing Cerebral Cortex: What We Have Learned and What We Need to Know

2022 ◽  
Vol 15 ◽  
Author(s):  
Heiko J. Luhmann
Keyword(s):  
Cerebral Cortex ◽  
Large Scale ◽  
Activity Patterns ◽  
Neuronal Cell ◽  
Electrode Arrays ◽  
Novel Technologies ◽  
The Past ◽  
Sensory Evoked

This review article aims to give a brief summary on the novel technologies, the challenges, our current understanding, and the open questions in the field of the neurophysiology of the developing cerebral cortex in rodents. In the past, in vitro electrophysiological and calcium imaging studies on single neurons provided important insights into the function of cellular and subcellular mechanism during early postnatal development. In the past decade, neuronal activity in large cortical networks was recorded in pre- and neonatal rodents in vivo by the use of novel high-density multi-electrode arrays and genetically encoded calcium indicators. These studies demonstrated a surprisingly rich repertoire of spontaneous cortical and subcortical activity patterns, which are currently not completely understood in their functional roles in early development and their impact on cortical maturation. Technological progress in targeted genetic manipulations, optogenetics, and chemogenetics now allow the experimental manipulation of specific neuronal cell types to elucidate the function of early (transient) cortical circuits and their role in the generation of spontaneous and sensory evoked cortical activity patterns. Large-scale interactions between different cortical areas and subcortical regions, characterization of developmental shifts from synchronized to desynchronized activity patterns, identification of transient circuits and hub neurons, role of electrical activity in the control of glial cell differentiation and function are future key tasks to gain further insights into the neurophysiology of the developing cerebral cortex.

scholarly journals Spike sorting of synchronous spikes from local neuron ensembles

2015 ◽  
Vol 114 (4) ◽  
pp. 2535-2549 ◽  
Author(s):  
Felix Franke ◽  
Robert Pröpper ◽  
Henrik Alle ◽  
Philipp Meier ◽  
Jörg R. P. Geiger ◽  
...  
Keyword(s):  
Cortical Neurons ◽  
Template Matching ◽  
Spatial Information ◽  
Simulated Data ◽  
Error Rates ◽  
Dimensional Structure ◽  
Spike Sorting ◽  
Spike Discharge

Synchronous spike discharge of cortical neurons is thought to be a fingerprint of neuronal cooperativity. Because neighboring neurons are more densely connected to one another than neurons that are located further apart, near-synchronous spike discharge can be expected to be prevalent and it might provide an important basis for cortical computations. Using microelectrodes to record local groups of neurons does not allow for the reliable separation of synchronous spikes from different cells, because available spike sorting algorithms cannot correctly resolve the temporally overlapping waveforms. We show that high spike sorting performance of in vivo recordings, including overlapping spikes, can be achieved with a recently developed filter-based template matching procedure. Using tetrodes with a three-dimensional structure, we demonstrate with simulated data and ground truth in vitro data, obtained by dual intracellular recording of two neurons located next to a tetrode, that the spike sorting of synchronous spikes can be as successful as the spike sorting of nonoverlapping spikes and that the spatial information provided by multielectrodes greatly reduces the error rates. We apply the method to tetrode recordings from the prefrontal cortex of behaving primates, and we show that overlapping spikes can be identified and assigned to individual neurons to study synchronous activity in local groups of neurons.

scholarly journals Kilosort: realtime spike-sorting for extracellular electrophysiology with hundreds of channels

2016 ◽  
Author(s):  
Marius Pachitariu ◽  
Nicholas Steinmetz ◽  
Shabnam Kadir ◽  
Matteo Carandini ◽  
Harris Kenneth D.
Keyword(s):  
Large Scale ◽  
Superior Performance ◽  
Spike Sorting ◽  
Electrode Arrays ◽  
Manual Curation ◽  
Electrophysiological Recordings ◽  
Dimensional Approximation ◽  
Low Dimensional ◽  
Channel Electrode

AbstractAdvances in silicon probe technology mean that in vivo electrophysiological recordings from hundreds of channels will soon become commonplace. To interpret these recordings we need fast, scalable and accurate methods for spike sorting, whose output requires minimal time for manual curation. Here we introduce Kilosort, a spike sorting framework that meets these criteria, and show that it allows rapid and accurate sorting of large-scale in vivo data. Kilosort models the recorded voltage as a sum of template waveforms triggered on the spike times, allowing overlapping spikes to be identified and resolved. Rapid processing is achieved thanks to a novel low-dimensional approximation for the spatiotemporal distribution of each template, and to batch-based optimization on GPUs. A novel post-clustering merging step based on the continuity of the templates substantially reduces the requirement for subsequent manual curation operations. We compare Kilosort to an established algorithm on data obtained from 384-channel electrodes, and show superior performance, at much reduced processing times. Data from 384-channel electrode arrays can be processed in approximately realtime. Kilosort is an important step towards fully automated spike sorting of multichannel electrode recordings, and is freely available (github.com/cortex-lab/Kilosort).

scholarly journals Development of experimental ground truth and quantification of intracranial aneurysm pulsation in a patient

2020 ◽  
Author(s):  
Axel Vanrossomme ◽  
Kamil Chodzyński ◽  
Omer Eker ◽  
Karim Zouaoui Boudjeltia
Keyword(s):  
Radiation Dose ◽  
Artery Aneurysm ◽  
Ground Truth ◽  
Anterior Communicating Artery ◽  
Ground Truth Data ◽  
Acquisition Protocol ◽  
Aneurysm Wall ◽  
Detection And Quantification

Abstract Aneurysm wall motion has been reported to be associated with rupture. However, its quantification with medical imaging is challenging and should be based on experimental ground-truth to avoid misinterpretation of results. In this work a time-resolved CT angiography (4D-CTA) acquisition protocol is proposed to detect the pulsation of intracranial aneurysms with a low radiation dose. To acquire ground-truth data, the accuracy of pulsation detection and quantification in a silicone phantom was assessed by applying pressure sinusoidal waves of increasing amplitudes. These experiments were carried out using a test bench that could reproduce pulsatile waveforms similar to those inside the internal carotid arteries of human subjects. 4D-CTA acquisition parameters (mAs, kVp) were then selected to achieve reliable pulsation detection and quantification with the lowest radiation dose achievable. The resulting acquisition protocol was then used to image an anterior communicating artery aneurysm in a human subject. Data reveals that in a simplified in vitro setting 4D-CTA allows for an effective and reproducible method to detect and quantify aneurysm pulsation with an inferior limit as low as 3 mm³ and a background noise of 0.5 to 1 mm³. Aneurysm pulsation can be detected in vivo with a radiation dose approximating 1 mSv.

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