scholarly journals Electrical Stimulus Artifact Cancellation and Neural Spike Detection on Large Multi-Electrode Arrays

2016 ◽  
Author(s):  
Gonzalo E. Mena ◽  
Lauren E. Grosberg ◽  
Sasidhar Madugula ◽  
Paweł Hottowy ◽  
Alan Litke ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
High Resolution ◽  
Action Potentials ◽  
Process Model ◽  
Error Rates ◽  
Neural Interfaces ◽  
Spike Sorting ◽  
Electrode Arrays ◽  
Retinal Prostheses ◽  
Sorting Process

AbstractSimultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these measurements is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is greatly complicated by electrical stimulation artifacts across the array, which can exhibit complex and nonlinear waveforms, and overlap temporarily with evoked spikes. Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes. The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation. We establish small error rates in the identification of evoked spikes, with a computational complexity that is compatible with real-time data analysis. This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation (e.g., retinal prostheses), and for closed-loop neural stimulation at a much larger scale than currently possible.Author SummarySimultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these recordings is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is largely stymied by electrical stimulation artifacts across the array, which are typically larger than the signals of interest. We develop a novel computational framework to estimate and subtract away this contaminating artifact, enabling the large-scale analysis of responses of possibly hundreds of cells to tailored stimulation. Importantly, we suggest that this technology may also be helpful for the development of future high-resolution neural prosthetic devices (e.g., retinal prostheses).

scholarly journals A low-cost computational approach to analyze spiking activity in cockroach sensory neurons

2021 ◽  
Vol 45 (1) ◽  
pp. 145-153
Author(s):  
David J. Torres ◽  
Andres Romero ◽  
Wes Colgan ◽  
Ulises M. Ricoy
Keyword(s):  
Action Potentials ◽  
Selection Criteria ◽  
Low Cost ◽  
Underrepresented Students ◽  
Spike Sorting ◽  
Interspike Intervals ◽  
Sorting Process ◽  
Rural College ◽  
Stimulation Of ◽  
Spiking Activity

Undergraduates use a spike sorting routine developed in Octave to analyze the spiking activity generated from mechanical stimulation of spines of cockroach legs with the inexpensive SpikerBox amplifier and the free software Audacity. Students learn the procedures involved in handling the cockroaches and recording extracellular action potentials (spikes) with the SpikerBox apparatus as well as the importance of spike sorting for analysis in neuroscience. The spike sorting process requires students to choose the spike threshold and spike selection criteria and interact with the clustering process that forms the groups of similar spikes. Once the spike groups are identified, interspike intervals and neuron firing frequencies can be calculated and analyzed. A classic neurophysiology lab exercise is thus adapted to be interdisciplinary for underrepresented students in a small rural college.

An Unsupervised Online Spike-Sorting Framework

2016 ◽  
Vol 26 (05) ◽  
pp. 1550042 ◽  
Author(s):  
Simeon Knieling ◽  
Kousik S. Sridharan ◽  
Paolo Belardinelli ◽  
Georgios Naros ◽  
Daniel Weiss ◽  
...  
Keyword(s):  
Clinical Application ◽  
Action Potentials ◽  
Scoring Systems ◽  
Spike Sorting ◽  
Microelectrode Recordings ◽  
Sorting Process ◽  
Feature Normalization ◽  
Offline Analysis ◽  
Fine Tune

Extracellular neuronal microelectrode recordings can include action potentials from multiple neurons. To separate spikes from different neurons, they can be sorted according to their shape, a procedure referred to as spike-sorting. Several algorithms have been reported to solve this task. However, when clustering outcomes are unsatisfactory, most of them are difficult to adjust to achieve the desired results. We present an online spike-sorting framework that uses feature normalization and weighting to maximize the distinctiveness between different spike shapes. Furthermore, multiple criteria are applied to either facilitate or prevent cluster fusion, thereby enabling experimenters to fine-tune the sorting process. We compare our method to established unsupervised offline (Wave_Clus (WC)) and online (OSort (OS)) algorithms by examining their performance in sorting various test datasets using two different scoring systems (AMI and the Adamos metric). Furthermore, we evaluate sorting capabilities on intra-operative recordings using established quality metrics. Compared to WC and OS, our algorithm achieved comparable or higher scores on average and produced more convincing sorting results for intra-operative datasets. Thus, the presented framework is suitable for both online and offline analysis and could substantially improve the quality of microelectrode-based data evaluation for research and clinical application.

scholarly journals Spike sorting for large, dense electrode arrays

2015 ◽  
Author(s):  
Cyrille Rossant ◽  
Shabnam N Kadir ◽  
Dan F. M. Goodman ◽  
John Schulman ◽  
Mariano Belluscio ◽  
...  
Keyword(s):  
Open Source Software ◽  
Simultaneous Recording ◽  
Error Rates ◽  
Spike Sorting ◽  
Electrode Arrays ◽  
Rat Cortex ◽  
Neural Electrode ◽  
Large Numbers ◽  
Microfabrication Technology ◽  
User Friendly

Developments in microfabrication technology have enabled the production of neural electrode arrays with hundreds of closely-spaced recording sites, and electrodes with thousands of sites are currently under development. These probes will in principle allow the simultaneous recording of very large numbers of neurons. However, use of this technology requires the development of techniques for decoding the spike times of the recorded neurons, from the raw data captured from the probes. There currently exists no practical solution to this problem of “spike sorting” for large, dense electrode arrays. Here, we present a set of novel tools to solve this problem, implemented in a suite of practical, user-friendly, open-source software. We validate these methods on data from rat cortex, demonstrating error rates as low as 5%.

scholarly journals Extracellular detection of neuronal coupling

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Elmer Guzman ◽  
Zhuowei Cheng ◽  
Paul K. Hansma ◽  
Kenneth R. Tovar ◽  
Linda R. Petzold ◽  
...  
Keyword(s):  
Action Potentials ◽  
Microelectrode Arrays ◽  
Short Latency ◽  
Spike Sorting ◽  
Neuronal Connectivity ◽  
Direct Stimulation ◽  
Multiple Electrodes

AbstractWe developed a method to non-invasively detect synaptic relationships among neurons from in vitro networks. Our method uses microelectrode arrays on which neurons are cultured and from which propagation of extracellular action potentials (eAPs) in single axons are recorded at multiple electrodes. Detecting eAP propagation bypasses ambiguity introduced by spike sorting. Our methods identify short latency spiking relationships between neurons with properties expected of synaptically coupled neurons, namely they were recapitulated by direct stimulation and were sensitive to changing the number of active synaptic sites. Our methods enabled us to assemble a functional subset of neuronal connectivity in our cultures.

Electronmicroscopic and electrophysiological studies of the teat branch of the XIII thoracic nerve: relationship with lactation in the rat

1988 ◽  
Vol 118 (3) ◽  
pp. 471-483 ◽  
Author(s):  
L. M. Voloschin ◽  
E. Décima ◽  
J. H. Tramezzani
Keyword(s):  
Electrical Stimulation ◽  
Conduction Velocity ◽  
Action Potentials ◽  
Silent Period ◽  
High Amplitude ◽  
Milk Ejection ◽  
Nerve Activity ◽  
Thoracic Nerve ◽  
Myelinated Fibres ◽  
Stimulation Of

ABSTRACT Electrical stimulation of the XIII thoracic nerve (the 'mammary nerve') causes milk ejection and the release of prolactin and other hormones. We have analysed the route of the suckling stimulus at the level of different subgroups of fibres of the teat branch of the XIII thoracic nerve (TBTN), which innervates the nipple and surrounding skin, and assessed the micromorphology of the TBTN in relation to lactation. There were 844 ± 63 and 868 ± 141 (s.e.m.) nerve fibres in the TBTN (85% non-myelinated) in virgin and lactating rats respectively. Non-myelinated fibres were enlarged in lactating rats; the modal value being 0·3–0·4 μm2 for virgin and 0·4–0·5 μm2 for lactating rats (P > 0·001; Kolmogorov–Smirnov test). The modal value for myelinated fibres was 3–6 μm2 in both groups. The compound action potential of the TBTN in response to electrical stimulation showed two early volleys produced by the Aα- and Aδ-subgroups of myelinated fibres (conduction velocity rate of 60 and 14 m/s respectively), and a late third volley originated in non-myelinated fibres ('C') group; conduction velocity rate 1·4 m/s). Before milk ejection the suckling pups caused 'double bursts' of fibre activity in the Aδ fibres of the TBTN. Each 'double burst' consisted of low amplitude action potentials and comprised two multiple discharges (33–37 ms each) separated by a silent period of around 35 ms. The 'double bursts' occurred at a frequency of 3–4/s, were triggered by the stimulation of the nipple and were related to fast cheek movements visible only by watching the pups closely. In contrast, the Aα fibres of the TBTN showed brief bursts of high amplitude potentials before milk ejection. These were triggered by the stimulation of cutaneous receptors during gross slow sucking motions of the pup (jaw movements). Immediately before the triggering of milk ejection the mother was always asleep and a low nerve activity was recorded in the TBTN at this time. When reflex milk ejection occurred, the mother woke and a brisk increase in nerve activity was detected; this decreased when milk ejection was accomplished. In conscious rats the double-burst type of discharges in Aδ fibres was not observed, possibly because this activity cannot be detected by the recording methods currently employed in conscious animals. During milk ejection, action potentials of high amplitude were conveyed in the Aα fibres of the TBTN. During the treading time of the stretch reaction (SR), a brisk increase in activity occurred in larger fibres; during the stretching periods of the SR a burst-type discharge was again observed in slow-conducting afferents; when the pups changed nipple an abrupt increase in activity occurred in larger fibres. In summary, the non-myelinated fibres of the TBTN are increased in diameter during lactation, and the pattern of suckling-evoked nerve activity in myelinated fibres showed that (a) the double burst of Aδ fibres, produced by individual sucks before milk ejection, could be one of the conditions required for the triggering of the reflex, and (b) the nerve activity displayed during milk-ejection action may result, at least in part, from 'non-specific' stimulation of cutaneous receptors. J. Endocr. (1988) 118, 471–483

Abstract P498: Polycystin-1 Regulates Excitation-contraction Coupling In Atrial Cardiomyocytes

2021 ◽  
Vol 129 (Suppl_1) ◽  
Author(s):  
Troy Hendrickson ◽  
William Perez ◽  
Vincent Provasek ◽  
Francisco J Altamirano
Keyword(s):  
Electrical Stimulation ◽  
Action Potentials ◽  
Primary Cilia ◽  
Calcium Influx ◽  
Calcium Transient ◽  
Calcium Handling ◽  
Excitation Contraction Coupling ◽  
Contraction Coupling ◽  
Atrial Cardiomyocytes ◽  
Atrial Excitation

Patients with Autosomal Dominant Polycystic Kidney disease (ADPKD) have multiple cardiovascular manifestations, including increased susceptibility to arrhythmias. Mutations in polycystin-1 (PC1) encoding gene accounts for 85% cases of ADPKD, whereas mutations in polycystin-2 (PC2) only accounts for 15%. In kidney cells, PC1 interacts with PC2 to form a protein complex at the primary cilia to regulate calcium influx via PC2. However, cardiomyocytes are non-ciliated cells and the role of both PC1 and PC2 in atrial cardiomyocytes remains unknown. We have previously demonstrated that PC1 regulates action potentials and calcium handling to fine-tune ventricular cardiomyocyte contraction. Here, we hypothesize that PC1 regulates action potentials and calcium handling in atrial cardiomyocytes independent of PC2 actions. To test this hypothesis, we differentiated human induced pluripotent stem cells (iPSC) into atrial cardiomyocytes (iPSC-aCM) using previously published protocols. To determine the contribution of PC1/PC2 in atrial excitation-contraction coupling, protein expression was knocked down utilizing specific siRNA constructs, for each protein, or a universal control siRNA transfected using lipofectamine RNAiMAX. We measured action potentials using the potentiometric dye FluoVolt and intracellular calcium with Fura-2 AM or Fluo-4. Changes in fluorescence were monitored using a multiwavelength IonOptix system. iPSC-aCM were paced at 2 Hz to synchronize the beating pattern using field electrical stimulation. Our data shows that PC1 ablation significantly decreased action potential duration at 50% and 80% of repolarization, by 24% and 23%, respectively. Moreover, we observed that PC1 knockdown significantly reduced calcium transient amplitude elicited by field electrical stimulation without changes in calcium transient decay. Interestingly, PC2 knockdown did not modify calcium transients in atrial cardiomyocytes (iPSC-aCM). Our data suggest that PC1 regulates atrial excitation-contraction coupling independent of PC2 actions. This study warrants further investigation into atrial dysfunction in ADPKD patients with PC1 mutations.

A Synchronous Neural Recording Platform for Multiple High-Resolution CMOS Probes and Passive Electrode Arrays

2018 ◽  
Vol 12 (3) ◽  
pp. 532-542 ◽  
Author(s):  
Gian Nicola Angotzi ◽  
Mario Malerba ◽  
Fabio Boi ◽  
Ermanno Miele ◽  
Alessandro Maccione ◽  
...  
Keyword(s):  
High Resolution ◽  
Neural Recording ◽  
Electrode Arrays ◽  
Passive Electrode

Editing trains of action potentials from multi-electrode arrays

2004 ◽  
Vol 134 (1) ◽  
pp. 91-100 ◽  
Author(s):  
Richard B. Stein ◽  
Douglas J. Weber
Keyword(s):  
Action Potentials ◽  
Electrode Arrays

scholarly journals MEA Viewer: a High-performance Interactive Application for Visualizing Electrophysiological Data

2017 ◽  
Author(s):  
Daniel C. Bridges ◽  
Kenneth R. Tovar ◽  
Bian Wu ◽  
Paul K. Hansma ◽  
Kenneth S. Kosik
Keyword(s):  
Action Potentials ◽  
High Performance ◽  
Detection Threshold ◽  
Electrode Arrays ◽  
Electrophysiological Data ◽  
Signal Average ◽  
Research Areas ◽  
Raster Plot ◽  
Data Files ◽  
Interactive Application

AbstractMulti-electrode arrays (MEAs) have been used for many years to measure electrical activity in ensembles of many hundreds of neurons, and are used in research areas as diverse as neuronal connectivity and drug discovery. A high sampling frequency is required to adequately capture action potentials, also known as spikes, the primary electrical event associated with neuronal activity, and the resulting raw data files are large and difficult to visualize with traditional plotting tools. Many common approaches to deal with this issue, such as extracting spikes times and solely performing spike train analysis, significantly reduce data dimensionality. Unbiased data exploration benefits from the use of tools that minimize data transforms and such tools enable the development of heuristic perspective from data prior to any subsequent processing. Here we introduce MEA Viewer, a high-performance interactive application for the direct visualization of multi-channel electrophysiological data. MEA Viewer provides many high-performance visualizations of electrophysiological data, including an easily navigable overview of all recorded extracellular signals overlaid with spike timestamp data and an interactive raster plot. Beyond the fundamental data displays, MEA Viewer can signal average and spatially overlay the extent of action potential propagation within single neurons. This view extracts information below the spike detection threshold to directly visualize the propagation of action potentials across the plane of the MEA. This entirely new method of using MEAs opens up new and novel research applications for medium density arrays. MEA Viewer is licensed under the General Public License version 3, GPLv3, and is available at http://github.com/dbridges/mea-tools.

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