Evidence map›Paper›PMID 41266140›Full record

RevieweNeuro2025

Open Data In Neurophysiology: Advancements, Solutions & Challenges.

Colleen J Gillon, Cody Baker, Ryan Ly, Edoardo Balzani, Bingni W Brunton, Manuel Schottdorf, Satrajit Ghosh, Nima Dehghani

Abstract readReview
In one paragraph

Review in eNeuro, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Neurodatascience: Past, Present, and Future.Data science in science · 2026
    Article
  2. Review
  3. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Colleen J GillonDepartment of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom.ORCID https://orcid.org/0000-0002-2253-7816
Cody BakerDartmouth College, Hanover, New Hampshire 03755.
Ryan LyScientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720.
Edoardo BalzaniCenter for Computational Neuroscience, Flatiron Institute, New York, New York 10010.
Bingni W BruntonDepartment of Biology, University of Washington, Seattle, Washington 98195.ORCID https://orcid.org/0000-0002-4831-3466
Manuel SchottdorfPrinceton Neuroscience Institute, Princeton University, Princeton, New Jersey 08540.
Satrajit GhoshMcGovern Institute for Brain Research, MIT, Cambridge, Massachusetts 02139.
Nima DehghaniMcGovern Institute for Brain Research, MIT, Cambridge, Massachusetts 02139 nima.dehghani@mit.edu.ORCID https://orcid.org/0000-0003-2032-8903

Funding

P5: Mechanistic Multi-Region Brain ModelsU19NS132720 · NINDS · PRINCETON UNIVERSITY · PI Carlos D Brody · 2023 to 2026
$21.5M
DANDI: Distributed Archives for Neurophysiology Data IntegrationR24MH117295 · NIMH · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Satrajit Sujit Ghosh, Yaroslav O Halchenko · 2019 to 2026
$11.6M
Evaluation and optimization of NWB neurophysiology software and data in the cloudU24NS120057 · NINDS · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI DICHTER, BENJAMIN K, RUEBEL, OLIVER · 2021 to 2025
$5.9M
NIMH NIH HHS R24 MH117295NINDS NIH HHS U19 NS132720NINDS NIH HHS U24 NS120057Wellcome Trust
6 · The paper itself

Abstract

Ongoing efforts over the last 50 years have made data and methods more reproducible and transparent across the life sciences. This openness has led to transformative insights and vastly accelerated scientific progress (Gražulis et al., 2012; Munafó et al., 2017). For example, structural biology (Bruno and Groom, 2014) and genomics (Benson et al., 2013; Porter and Hajibabaei, 2018) have undertaken systematic collection and publication of protein sequences and structures over the past half century. These data, in turn, have led to scientific breakthroughs that were unthinkable when data collection first began (Jumper et al., 2021). We believe that neuroscience is poised to follow the same path, and that principles of open data and open science will transform our understanding of the nervous system in ways that are impossible to predict at the moment. New social structures supporting an active and open scientific community are essential (Saunders, 2022) to facilitate and expand the still limited adoption of open science practices in our field (Schottdorf et al., 2024). Unified by shared values of openness, we set out to organize a symposium for open data in neurophysiology (ODIN) to strengthen our community and facilitate transformative open neuroscience research at large. In this report, we synthesize insights from this first ODIN event. We also lay out plans for how to grow this movement, document emerging conversations, and propose a path toward a better and more transparent science of tomorrow.

Indexed as

Information DisseminationNeurophysiologyHumansNeurosciencescodecollaborationdatasetsneurophysiologyopen sciencesharing

Identifiers

PMID41266140
PMCPMC12658310

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.