Evidence map›Paper›PMID 41503102›Full record

ArticleArXiv2025

EM and XRM Connectomics Imaging and Experimental Metadata Standards.

Miguel E Wimbish, Nicole K Guittari, Victoria A Rose, Jorge L Rivera, Patricia K Rivlin, Mark A Hinton, Jordan K Matelsky, Nicole E Stock, Brock A Wester, Erik C Johnson and 1 more

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Miguel E WimbishResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
Nicole K GuittariResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
Victoria A RoseResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
Jorge L RiveraResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
Patricia K RivlinResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
Mark A HintonResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
Jordan K MatelskyResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
Nicole E StockResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
Brock A WesterResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
Erik C JohnsonResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
William R Gray-RoncalResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.

Funding

Boss: A cloud-based data archive for electron microscopy and x-ray microtomographyR24MH114785 · NIMH · JOHNS HOPKINS UNIVERSITY · PI BROCK A. WESTER · 2018 to 2026
$6.9M
Big-Data Electron-microscopy for Novel Community Hypotheses: Measuring And Retrieving Knowledge (BENCHMARK)R01MH126684 · NIMH · JOHNS HOPKINS UNIVERSITY · PI GRAY RONCAL, WILLIAM R · 2021 to 2022
$1.3M
SABER: Scalable Analytics for Brain Exploration Research using X-Ray Microtomography and Electron MicroscopyR24MH114799 · NIMH · JOHNS HOPKINS UNIVERSITY · PI GRAY RONCAL, WILLIAM R · 2017 to 2019
$1.2M
NIMH NIH HHS R01 MH126684NIMH NIH HHS R24 MH114785NIMH NIH HHS R24 MH114799
6 · The paper itself

Abstract

High resolution volumetric neuroimaging datasets from electron microscopy (EM) and x-ray micro and holographic-nano tomography (XRM/XHN) are being generated at an increasing rate and by a growing number of research teams. These datasets are derived from an increasing number of species, in an increasing number of brain regions, and with an increasing number of techniques. Each of these large-scale datasets, often surpassing petascale levels, is typically accompanied by a unique and varied set of metadata. These datasets can be used to derive connectomes, or neuron-synapse level connectivity diagrams, to investigate the fundamental organization of neural circuitry, neuronal development, and neurodegenerative disease. Standardization is essential to facilitate comparative connectomics analysis and enhance data utilization. Although the neuroinformatics community has successfully established and adopted data standards for many modalities, this effort has not yet encompassed EM and XRM/ XHN connectomics data. This lack of standardization isolates these datasets, hindering their integration and comparison with other research performed in the field. Towards this end, our team formed a working group consisting of community stakeholders to develop Image and Experimental Metadata Standards for EM and XRM/XHN data to ensure the scientific impact and further motivate the generation and sharing of these data. This document addresses version 1.1 of these standards, aiming to support metadata services and future software designs for community collaboration. Standards for derived annotations are described in a companion document. Standards definitions are available on a community github page. We hope these standards will enable comparative analysis, improve interoperability between connectomics software tools, and continue to be refined and improved by the neuroinformatics community.

Indexed as

ConnectomicsData StandardsElectron MicroscopyFAIR DataNeuroanatomyX-ray Microtomagraphy

Identifiers

PMID41503102
PMCPMC12772707

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.