Jove
Visualize
Contact Us
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

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

Visual Speech Recognition with Lightweight Psychologically Motivated Gabor Features.

Entropy (Basel, Switzerland)·2020
Same author

A Biologically Supported Error-Correcting Learning Rule.

Neural computation·2019
Same author

Toward a neuromorphic microphone.

Frontiers in neuroscience·2015
Same author

A Power-Efficient Capacitive Read-Out Circuit With Parasitic-Cancellation for MEMS Cochlea Sensors.

IEEE transactions on biomedical circuits and systems·2015
Same author

A Bio-Realistic Analog CMOS Cochlea Filter With High Tunability and Ultra-Steep Roll-Off.

IEEE transactions on biomedical circuits and systems·2014
Same author

A neurally inspired musical instrument classification system based upon the sound onset.

The Journal of the Acoustical Society of America·2012
Same journal

Expression of concern: "Effect of perioperative preemptive analgesia on hippocampal GABAA receptor α1/α5 balance in aged mild cognitive impairment rats" [Brain Res. Bull. 237 (2026) 111811].

Brain research bulletin·2026
Same journal

Ubiquitination in ischemic stroke: molecular mechanisms and therapeutic implications.

Brain research bulletin·2026
Same journal

Corrigendum to "Peripheral to central: Exploring the neural, endocrine, and immune pathways of the gut-brain axis in postoperative neurocognitive dysfunction" [Brain Res. Bull. 242 (2026) 111975].

Brain research bulletin·2026
Same journal

GLUT1-driven glycolytic reprogramming in microglia promotes neuroinflammation and cognitive deficits in sepsis-associated encephalopathy.

Brain research bulletin·2026
Same journal

Spinal astrocytes hardly proliferate following peripheral nerve injury: Evidence from adult Aldh1l1-GFP reporter mice.

Brain research bulletin·2026
Same journal

Shared Neural Mechanisms of Trait Mindfulness and Hypnotic Susceptibility: A Scoping Review Toward a Unifying Predictive Coding Framework.

Brain research bulletin·2026
See all related articles

Related Experiment Video

Updated: Apr 7, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

6.2K

Why sharing matters for electrophysiological data analysis.

Leslie S Smith1

  • 1Computing Science and Mathematics, University of Stirling, Stirling FK9 4LA, UK.

Brain Research Bulletin
|July 8, 2015
PubMed
Summary
This summary is machine-generated.

Sharing electrophysiological data and analysis tools is crucial for advancing brain research. This paper discusses challenges and reviews efforts to improve data and code sharing in electrophysiology.

Keywords:
Analysis tool sharingData sharingElectrophysiologyNeuroinformaticsRepository

More Related Videos

Electroencephalographic Signal Acquisition Framework for Neurodiverse: A Case Study of Dolphin-Assisted Therapy
07:21

Electroencephalographic Signal Acquisition Framework for Neurodiverse: A Case Study of Dolphin-Assisted Therapy

Published on: June 27, 2025

603
Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
09:32

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients

Published on: December 18, 2016

13.1K

Related Experiment Videos

Last Updated: Apr 7, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

6.2K
Electroencephalographic Signal Acquisition Framework for Neurodiverse: A Case Study of Dolphin-Assisted Therapy
07:21

Electroencephalographic Signal Acquisition Framework for Neurodiverse: A Case Study of Dolphin-Assisted Therapy

Published on: June 27, 2025

603
Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
09:32

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients

Published on: December 18, 2016

13.1K

Area of Science:

  • Neuroscience
  • Computational Biology
  • Data Science

Background:

  • Electrophysiology generates large, complex datasets.
  • Current data and tool sharing practices in electrophysiology face significant barriers.
  • Reproducibility and collaboration are hindered by limited data accessibility.

Purpose of the Study:

  • Advocate for enhanced sharing of electrophysiological datasets and analysis tools.
  • Identify and discuss sociological and technical challenges impeding data and code sharing.
  • Review existing initiatives and consider the sharing aspects of major brain research projects.

Main Methods:

  • Literature review of data and code sharing efforts in electrophysiology.
  • Analysis of challenges in data and tool sharing.
  • Examination of data sharing policies and practices in large-scale brain research projects.

Main Results:

  • Sociological and technical hurdles significantly impact data and tool sharing.
  • Existing work demonstrates a growing trend towards improved sharing practices.
  • Large brain research projects are increasingly incorporating data sharing components.

Conclusions:

  • Increased data and tool sharing in electrophysiology is essential for scientific progress.
  • Addressing identified challenges requires collaborative efforts from researchers and institutions.
  • Future brain research will benefit from robust, open-access electrophysiological data and analysis tools.