scholarly journals SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sorters

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Jeremy Magland ◽  
James J Jun ◽  
Elizabeth Lovero ◽  
Alexander J Morley ◽  
Cole Lincoln Hurwitz ◽  
...  
Keyword(s):  
Ground Truth ◽  
Brain Regions ◽  
Optimal Choice ◽  
Spike Sorting ◽  
Experimental Conditions ◽  
Total Size ◽  
Sorting Algorithms ◽  
Electrophysiological Recordings ◽  
Wide Range ◽  
Electrophysiological Studies

Spike sorting is a crucial step in electrophysiological studies of neuronal activity. While many spike sorting packages are available, there is little consensus about which are most accurate under different experimental conditions. SpikeForest is an open-source and reproducible software suite that benchmarks the performance of automated spike sorting algorithms across an extensive, curated database of ground-truth electrophysiological recordings, displaying results interactively on a continuously-updating website. With contributions from eleven laboratories, our database currently comprises 650 recordings (1.3 TB total size) with around 35,000 ground-truth units. These data include paired intracellular/extracellular recordings and state-of-the-art simulated recordings. Ten of the most popular spike sorting codes are wrapped in a Python package and evaluated on a compute cluster using an automated pipeline. SpikeForest documents community progress in automated spike sorting, and guides neuroscientists to an optimal choice of sorter and parameters for a wide range of probes and brain regions.

scholarly journals SpikeForest: reproducible web-facing ground-truth validation of automated neural spike sorters

2020 ◽  
Author(s):  
Jeremy F. Magland ◽  
James J. Jun ◽  
Elizabeth Lovero ◽  
Alexander J. Morley ◽  
Cole L. Hurwitz ◽  
...  
Keyword(s):  
Ground Truth ◽  
Brain Regions ◽  
Optimal Choice ◽  
Spike Sorting ◽  
Experimental Conditions ◽  
Total Size ◽  
Electrophysiological Recordings ◽  
Wide Range ◽  
Electrophysiological Studies ◽  
Synthetic Datasets

AbstractSpike sorting is a crucial but time-intensive step in electrophysiological studies of neuronal activity. While there are many popular software packages for spike sorting, there is little consensus about which are the most accurate under different experimental conditions. SpikeForest is an open-source and reproducible software suite that benchmarks the performance of automated spike sorting algorithms across an extensive, curated database of electrophysiological recordings with ground truth, displaying results interactively on a continuously-updating website. With contributions from over a dozen participating laboratories, our database currently comprises 650 recordings (1.3 TB total size) with around 35,000 ground-truth units. These data include extracellular recordings paired with intracellular voltages, state-of-the-art simulated recordings, and hybrid synthetic datasets. Ten of the most frequently used modern spike sorting codes are wrapped under a common Python framework and evaluated on a compute cluster using an automated pipeline. SpikeForest validates and documents community progress in automated spike sorting, and guides neuroscientists to an optimal choice of sorter and parameters for a wide range of probes and brain regions.

scholarly journals SHYBRID: A graphical tool for generating hybrid ground-truth spiking data for evaluating spike sorting performance

2019 ◽  
Author(s):  
Jasper Wouters ◽  
Fabian Kloosterman ◽  
Alexander Bertrand
Keyword(s):  
Ground Truth ◽  
Neural Recording ◽  
Data Driven ◽  
Sorting Algorithm ◽  
Spike Sorting ◽  
Recording Device ◽  
Ground Truth Data ◽  
Sorting Algorithms ◽  
Graphical Tool ◽  
Fine Tune

AbstractSpike sorting is the process of retrieving the spike times of individual neurons that are present in an extracellular neural recording. Over the last decades, many spike sorting algorithms have been published. In an effort to guide a user towards a specific spike sorting algorithm, given a specific recording setting (i.e., brain region and recording device), we provide an open-source graphical tool for the generation of hybrid ground-truth data in Python. Hybrid ground-truth data is a data-driven modelling paradigm in which spikes from a single unit are moved to a different location on the recording probe, thereby generating a virtual unit of which the spike times are known. The tool enables a user to efficiently generate hybrid ground-truth datasets and make informed decisions between spike sorting algorithms, fine-tune the algorithm parameters towards the used recording setting, or get a deeper understanding of those algorithms.

scholarly journals Validation of neural spike sorting algorithms without ground-truth information

2016 ◽  
Vol 264 ◽  
pp. 65-77 ◽  
Author(s):  
Alex H. Barnett ◽  
Jeremy F. Magland ◽  
Leslie F. Greengard
Keyword(s):  
Ground Truth ◽  
Spike Sorting ◽  
Sorting Algorithms ◽  
Neural Spike ◽  
Ground Truth Information

scholarly journals Redox artifacts in electrophysiological recordings

2013 ◽  
Vol 304 (7) ◽  
pp. C604-C613 ◽  
Author(s):  
Jonathan M. Berman ◽  
Mouhamed S. Awayda
Keyword(s):  
Voltage Clamp ◽  
Membrane Conductance ◽  
Chloride Ions ◽  
Experimental Conditions ◽  
Chemical Reagents ◽  
Electrophysiological Recordings ◽  
Electrode Voltage ◽  
Electrophysiological Studies ◽  
Increased Sensitivity ◽  
Chloride Deposition

Electrophysiological techniques make use of Ag/AgCl electrodes that are in direct contact with cells or bath. In the bath, electrodes are exposed to numerous experimental conditions and chemical reagents that can modify electrode voltage. We examined voltage offsets created in Ag/AgCl electrodes by exposure to redox reagents used in electrophysiological studies. Voltage offsets were measured in reference to an electrode separated from the solution by an agar bridge. The reducing reagents Tris-2-carboxyethly-phosphine, dithiothreitol (DTT), and glutathione, as well as the oxidizing agent H2O2used at experimentally relevant concentrations reacted with Ag in the electrodes to produce voltage offsets. Chloride ions and strong acids and bases produced offsets at millimolar concentrations. Electrolytic depletion of the AgCl layer, to replicate voltage clamp and sustained use, resulted in increased sensitivity to flow and DTT. Offsets were sensitive to electrode silver purity and to the amount and method of chloride deposition. For example, exposure to 10 μM DTT produced a voltage offset between 10 and 284 mV depending on the chloride deposition method. Currents generated by these offsets are significant and dependent on membrane conductance and by extension the expression of ion channels and may therefore appear to be biological in origin. These data demonstrate a new source of artifacts in electrophysiological recordings that can affect measurements obtained from a variety of experimental techniques from patch clamp to two-electrode voltage clamp.

scholarly journals Systematic assessment of the accuracy of subunit counting in biomolecular complexes using automated single molecule brightness analysis

2021 ◽  
Author(s):  
John S H Danial ◽  
Yuri Quintana ◽  
Uris Ros ◽  
Raed Shalaby ◽  
Eleonora Germana Margheritis ◽  
...  
Keyword(s):  
Single Molecule ◽  
Ground Truth ◽  
Experimental Conditions ◽  
Systematic Analysis ◽  
Ground Truth Data ◽  
Systematic Assessment ◽  
Brightness Analysis ◽  
Wide Range ◽  
Biomolecular Complexes ◽  
Biological Complexes

Analysis of single molecule brightness allows subunit counting of high-order oligomeric biomolecular complexes. Although the theory behind the method has been extensively assessed, systematic analysis of the experimental conditions required to accurately quantify the stoichiometry of biological complexes remains challenging. In this work, we develop a high-throughput, automated computational pipeline for single molecule brightness analysis that requires minimal human input. We use this strategy to systematically quantify the accuracy of counting under a wide range of experimental conditions in simulated ground-truth data and then validate its use on experimentally obtained data. Our approach defines a set of conditions under which subunit counting by brightness analysis is designed to work optimally and helps establishing the experimental limits in quantifying the number of subunits in a complex of interest. Finally, we combine these features into a powerful, yet simple, software that can be easily used for the stoichiometry analysis of such complexes.

scholarly journals Evaluation and resolution of many challenges of neural spike-sorting: a new sorter

2021 ◽  
Author(s):  
Nathan J Hall ◽  
David J Herzfeld ◽  
Stephen G Lisberger
Keyword(s):  
Failure Modes ◽  
Ground Truth ◽  
Spike Sorting ◽  
Appropriate Use ◽  
Neural Data ◽  
Sorting Algorithms ◽  
Recording Session ◽  
Neural Spike ◽  
Detailed Assessment ◽  
Process Speed

We evaluate existing spike sorters and present a new one that resolves many sorting challenges. The new sorter, called "full binary pursuit" or FBP, comprises multiple steps. First, it thresholds and clusters to identify the waveforms of all unique neurons in the recording. Second, it uses greedy binary pursuit to optimally assign all the spike events in the original voltages to separable neurons. Third, it resolves spike events that are described more accurately as the superposition of spikes from two other neurons. Fourth, it resolves situations where the recorded neurons drift in amplitude or across electrode contacts during a long recording session. Comparison with other sorters on ground-truth datasets reveals many of the failure modes of spike sorting. We examine overall spike sorter performance in ground-truth datasets and suggest post-sorting analyses that can improve the veracity of neural analyses by minimizing the intrusion of failure modes into analysis and interpretation of neural data. Our analysis reveals the tradeoff between the number of channels a sorter can process, speed of sorting, and some of the failure modes of spike sorting. FBP works best on data from 32 channels or fewer. It trades speed and number of channels for avoidance of specific failure modes that would be challenges for some use cases. We conclude that all spike sorting algorithms studied have advantages and shortcomings, and the appropriate use of a spike sorter requires a detailed assessment of the data being sorted and the experimental goals for analyses.

Strongly Coupled Redox-Linked Conformational Switching at the Active Site of the Non-Heme Iron-Dependent Dioxygenase, TauD

2019 ◽  
Author(s):  
Christopher John ◽  
Greg M. Swain ◽  
Robert P. Hausinger ◽  
Denis A. Proshlyakov
Keyword(s):  
Active Site ◽  
Structural Model ◽  
Heme Iron ◽  
Chemical Transformations ◽  
Experimental Conditions ◽  
Strongly Coupled ◽  
Non Heme Iron ◽  
Reversible Redox ◽  
Wide Range ◽  
Complex Structural

2-Oxoglutarate (2OG)-dependent dioxygenases catalyze C-H activation while performing a wide range of chemical transformations. In contrast to their heme analogues, non-heme iron centers afford greater structural flexibility with important implications for their diverse catalytic mechanisms. We characterize an <i>in situ</i> structural model of the putative transient ferric intermediate of 2OG:taurine dioxygenase (TauD) by using a combination of spectroelectrochemical and semi-empirical computational methods, demonstrating that the Fe (III/II) transition involves a substantial, fully reversible, redox-linked conformational change at the active site. This rearrangement alters the apparent redox potential of the active site between -127 mV for reduction of the ferric state and 171 mV for oxidation of the ferrous state of the 2OG-Fe-TauD complex. Structural perturbations exhibit limited sensitivity to mediator concentrations and potential pulse duration. Similar changes were observed in the Fe-TauD and taurine-2OG-Fe-TauD complexes, thus attributing the reorganization to the protein moiety rather than the cosubstrates. Redox difference infrared spectra indicate a reorganization of the protein backbone in addition to the involvement of carboxylate and histidine ligands. Quantitative modeling of the transient redox response using two alternative reaction schemes across a variety of experimental conditions strongly supports the proposal for intrinsic protein reorganization as the origin of the experimental observations.

scholarly journals Low-Energy Electron Damage to Condensed-Phase DNA and Its Constituents

2021 ◽  
Vol 22 (15) ◽  
pp. 7879
Author(s):  
Yingxia Gao ◽  
Yi Zheng ◽  
Léon Sanche
Keyword(s):  
Condensed Phase ◽  
Genetic Material ◽  
High Energy ◽  
Dna Lesions ◽  
Low Energy ◽  
Experimental Investigations ◽  
Experimental Conditions ◽  
Strand Breaks ◽  
Sequence Of Events ◽  
Wide Range

The complex physical and chemical reactions between the large number of low-energy (0–30 eV) electrons (LEEs) released by high energy radiation interacting with genetic material can lead to the formation of various DNA lesions such as crosslinks, single strand breaks, base modifications, and cleavage, as well as double strand breaks and other cluster damages. When crosslinks and cluster damages cannot be repaired by the cell, they can cause genetic loss of information, mutations, apoptosis, and promote genomic instability. Through the efforts of many research groups in the past two decades, the study of the interaction between LEEs and DNA under different experimental conditions has unveiled some of the main mechanisms responsible for these damages. In the present review, we focus on experimental investigations in the condensed phase that range from fundamental DNA constituents to oligonucleotides, synthetic duplex DNA, and bacterial (i.e., plasmid) DNA. These targets were irradiated either with LEEs from a monoenergetic-electron or photoelectron source, as sub-monolayer, monolayer, or multilayer films and within clusters or water solutions. Each type of experiment is briefly described, and the observed DNA damages are reported, along with the proposed mechanisms. Defining the role of LEEs within the sequence of events leading to radiobiological lesions contributes to our understanding of the action of radiation on living organisms, over a wide range of initial radiation energies. Applications of the interaction of LEEs with DNA to radiotherapy are briefly summarized.

scholarly journals Review of the Upright Balance Assessment Based on the Force Plate

2021 ◽  
Vol 18 (5) ◽  
pp. 2696
Author(s):  
Baoliang Chen ◽  
Peng Liu ◽  
Feiyun Xiao ◽  
Zhengshi Liu ◽  
Yong Wang
Keyword(s):  
Postural Balance ◽  
Force Plate ◽  
Assessment Method ◽  
Balance Assessment ◽  
Experimental Conditions ◽  
Methodological Research ◽  
Assessment Tests ◽  
Wide Range ◽  
Foot Posture ◽  
Plate System

Quantitative assessment is crucial for the evaluation of human postural balance. The force plate system is the key quantitative balance assessment method. The purpose of this study is to review the important concepts in balance assessment and analyze the experimental conditions, parameter variables, and application scope based on force plate technology. As there is a wide range of balance assessment tests and a variety of commercial force plate systems to choose from, there is room for further improvement of the test details and evaluation variables of the balance assessment. The recommendations presented in this article are the foundation and key part of the postural balance assessment; these recommendations focus on the type of force plate, the subject’s foot posture, and the choice of assessment variables, which further enriches the content of posturography. In order to promote a more reasonable balance assessment method based on force plates, further methodological research and a stronger consensus are still needed.

scholarly journals Classification of unlabeled online media

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sakthi Kumar Arul Prakash ◽  
Conrad Tucker
Keyword(s):  
Social Media ◽  
Real World ◽  
Graphical Model ◽  
Ground Truth ◽  
Classification Problem ◽  
Machine Learning Algorithms ◽  
Social Media Networks ◽  
Online Social Media ◽  
Wide Range

AbstractThis work investigates the ability to classify misinformation in online social media networks in a manner that avoids the need for ground truth labels. Rather than approach the classification problem as a task for humans or machine learning algorithms, this work leverages user–user and user–media (i.e.,media likes) interactions to infer the type of information (fake vs. authentic) being spread, without needing to know the actual details of the information itself. To study the inception and evolution of user–user and user–media interactions over time, we create an experimental platform that mimics the functionality of real-world social media networks. We develop a graphical model that considers the evolution of this network topology to model the uncertainty (entropy) propagation when fake and authentic media disseminates across the network. The creation of a real-world social media network enables a wide range of hypotheses to be tested pertaining to users, their interactions with other users, and with media content. The discovery that the entropy of user–user and user–media interactions approximate fake and authentic media likes, enables us to classify fake media in an unsupervised learning manner.

Sign in / Sign up

Export Citation Format

Share Document