Jove
Visualize
Contact Us

Related Experiment Video

Updated: May 28, 2026

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

Making neurophysiological data analysis reproducible: why and how?

Matthieu Delescluse1, Romain Franconville, Sébastien Joucla

  • 1Laboratoire de physiologie cérébrale, CNRS UMR 8118, UFR biomédicale, Université Paris-Descartes, 45 rue des Saints-Péres, 75006 Paris, France. matthieu.delescluse@polytechnique.org

Journal of Physiology, Paris
|October 12, 2011
PubMed
Summary

Reproducible data analysis enhances scientific articles by including data, code, and methods for result verification. This approach, termed reproducible research, is crucial for computational fields and can improve scientific communication.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A Drosophila computational brain model reveals sensorimotor processing.

Nature·2024
Same author

A leaky integrate-and-fire computational model based on the connectome of the entire adult <i>Drosophila</i> brain reveals insights into sensorimotor processing.

bioRxiv : the preprint server for biology·2023
Same author

Face Processing in Developmental Prosopagnosia: Altered Neural Representations in the Fusiform Face Area.

Frontiers in behavioral neuroscience·2021
Same author

A simple method for getting standard error on the ratiometric calcium estimator.

MethodsX·2021
Same author

Datasets for calcium dynamics comparison between the whole-cell and a β-escin based perforated patch configuration in brain slices from adult mice.

Data in brief·2021
Same author

A connectome of the <i>Drosophila</i> central complex reveals network motifs suitable for flexible navigation and context-dependent action selection.

eLife·2021
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Area of Science:

  • Computational data analysis
  • Scientific communication

Background:

  • Classical scientific articles lack components for independent result reproduction.
  • The concept evolved from economic replication to reproducible research in computational fields.
  • Efficient tools are essential for implementing reproducible data analysis.

Purpose of the Study:

  • To present the history and tools for reproducible data analysis.
  • To demonstrate open-source software for reproducible research.
  • To advocate for the adoption of reproducible research in neuroscience.

Main Methods:

  • Historical overview of replication and reproducible research.
  • Description of available tools for reproducible data analysis.
  • Demonstration using "Sweave family" and emacs org-mode with R, Matlab, and Python.

More Related Videos

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

Related Experiment Videos

Last Updated: May 28, 2026

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

Main Results:

  • "Sweave family" (R-specific) and emacs org-mode (multi-language) are effective open-source tools.
  • Both tools support various operating systems (Unix-like, Windows, Mac).
  • Reproducible research paradigm facilitates efficient communication of scientific results.

Conclusions:

  • Reproducible data analysis, encompassing data, code, and methods, ensures result verification.
  • Open-source tools like "Sweave family" and emacs org-mode facilitate reproducible research.
  • Neuroscience can benefit significantly by adopting reproducible research practices for enhanced communication.