ReviewScientific data2023
A comparison of neuroelectrophysiology databases.
Review in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
15 citing papers in PubMed.
- Article
- Review
- Adaptive neuromodulation dialogues: navigating current challenges and emerging innovations in neuromodulation system development.Journal of neural engineering · 2025Review
- Article
- Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges.Epilepsia open · 2025Review
- Improving data sharing and knowledge transfer via the Neuroelectrophysiology Analysis Ontology (NEAO).Scientific data · 2025Article
- B(RAIN)Scientific data · 2025Article
- Automating the practice of science: Opportunities, challenges, and implications.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Multiscale Cloud-Based Pipeline for Neuronal Electrophysiology Analysis and Visualization.bioRxiv : the preprint server for biology · 2024Article
- Changes in Hippocampal Volume after Traumatic Brain Injury (TBI).Research square · 2024Article
- The BRAIN Initiative data-sharing ecosystem: Characteristics, challenges, benefits, and opportunities.eLife · 2024Article
- East Asian perspective of responsible research and innovation in neurotechnology.IBRO neuroscience reports · 2024Article
- Data science and its future in large neuroscience collaborations.bioRxiv : the preprint server for biology · 2024Article
- Dataset of human-single neuron activity during a Sternberg working memory task.Scientific data · 2024Article
- The past, present and future of neuroscience data sharing: a perspective on the state of practices and infrastructure for FAIR.Frontiers in neuroinformatics · 2023Review
Corrections and comments
- Update of
Authors and funding
25 authors.
Funding
Abstract
As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial neuroelectrophysiology data repositories: Data Archive for the BRAIN Initiative (DABI), Distributed Archives for Neurophysiology Data Integration (DANDI), OpenNeuro, and Brain-CODE. The aim of this review is to describe archives that provide researchers with tools to store, share, and reanalyze both human and non-human neurophysiology data based on criteria that are of interest to the neuroscientific community. The Brain Imaging Data Structure (BIDS) and Neurodata Without Borders (NWB) are utilized by these archives to make data more accessible to researchers by implementing a common standard. As the necessity for integrating large-scale analysis into data repository platforms continues to grow within the neuroscientific community, this article will highlight the various analytical and customizable tools developed within the chosen archives that may advance the field of neuroinformatics.
Indexed as
Identifiers
What OpenQuestion holds
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.