ArticleNeuroinformatics2009
Spike train analysis toolkit: enabling wider application of information-theoretic techniques to neurophysiology.
Article in Neuroinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Characterization of DnaJ gene family in Castanea mollissima and functional analysis of CmDnaJ27 under cold and heat stresses.BMC plant biology · 2025Article
- MINT: A toolbox for the analysis of multivariate neural information coding and transmission.PLoS computational biology · 2025Article
- Identification and Characterization of SQUAMOSA Promoter Binding Protein-like Transcription Factor Family Members inPlants (Basel, Switzerland) · 2025Article
- Genome-wide identification, phylogeny, and expression analysis of PEBP gene family inFrontiers in genetics · 2025Article
- A high heterozygosity genome assembly of Aedes albopictus enables the discovery of the association of PGANT3 with blood-feeding behavior.BMC genomics · 2024Article
- Introducing the STReaC (Spike Train Response Classification) toolbox.Journal of neuroscience methods · 2024Article
- Identification of BBX gene family and its function in the regulation of microtuber formation in yam.BMC genomics · 2023Article
- Construction of a caries diagnosis model based on microbiome novelty score.Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology · 2023Article
- Genome-wide identification and characterization of theFrontiers in plant science · 2023Article
- CEPS: An Open Access MATLAB Graphical User Interface (GUI) for the Analysis of Complexity and Entropy in Physiological Signals.Entropy (Basel, Switzerland) · 2021Article
- ProGeo-neo: a customized proteogenomic workflow for neoantigen prediction and selection.BMC medical genomics · 2020Article
- MEAnalyzer - a Spike Train Analysis Tool for Multi Electrode Arrays.Neuroinformatics · 2020Article
- Comparing Open-Source Toolboxes for Processing and Analysis of Spike and Local Field Potentials Data.Frontiers in neuroinformatics · 2019Review
- NeoAnalysis: a Python-based toolbox for quick electrophysiological data processing and analysis.Biomedical engineering online · 2017Article
- PRANAS: A New Platform for Retinal Analysis and Simulation.Frontiers in neuroinformatics · 2017Article
- Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding.PLoS computational biology · 2016Article
- Processing and Analysis of Multichannel Extracellular Neuronal Signals: State-of-the-Art and Challenges.Frontiers in neuroscience · 2016Review
- Temporal and rate code analysis of responses to low-frequency components in the bird's own song by song system neurons.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2015Article
- High Stimulus-Related Information in Barrel Cortex Inhibitory Interneurons.PLoS computational biology · 2015Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Conventional methods widely available for the analysis of spike trains and related neural data include various time- and frequency-domain analyses, such as peri-event and interspike interval histograms, spectral measures, and probability distributions. Information theoretic methods are increasingly recognized as significant tools for the analysis of spike train data. However, developing robust implementations of these methods can be time-consuming, and determining applicability to neural recordings can require expertise. In order to facilitate more widespread adoption of these informative methods by the neuroscience community, we have developed the Spike Train Analysis Toolkit. STAToolkit is a software package which implements, documents, and guides application of several information-theoretic spike train analysis techniques, thus minimizing the effort needed to adopt and use them. This implementation behaves like a typical Matlab toolbox, but the underlying computations are coded in C for portability, optimized for efficiency, and interfaced with Matlab via the MEX framework. STAToolkit runs on any of three major platforms: Windows, Mac OS, and Linux. The toolkit reads input from files with an easy-to-generate text-based, platform-independent format. STAToolkit, including full documentation and test cases, is freely available open source via http://neuroanalysis.org , maintained as a resource for the computational neuroscience and neuroinformatics communities. Use cases drawn from somatosensory and gustatory neurophysiology, and community use of STAToolkit, demonstrate its utility and scope.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.