Evidence map›Paper›PMID 40162160›Full record

ArticleFrontiers in neuroinformatics2025

Developing a multiscale neural connectivity knowledgebase of the autonomic nervous system.

Fahim T Imam, Thomas H Gillespie, Ilias Ziogas, Monique C Surles-Zeigler, Susan Tappan, Burak I Ozyurt, Jyl Boline, Bernard de Bono, Jeffrey S Grethe, Maryann E Martone

Abstract read
In one paragraph

Article in Frontiers in neuroinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Fahim T ImamFAIR Data Informatics Lab, Department of Neurosciences, School of Medicine, University of California, San Diego, La Jolla, CA, United States.
Thomas H GillespieFAIR Data Informatics Lab, Department of Neurosciences, School of Medicine, University of California, San Diego, La Jolla, CA, United States.
Ilias ZiogasSPARC K-Core, La Jolla, CA, United States.
Monique C Surles-ZeiglerFAIR Data Informatics Lab, Department of Neurosciences, School of Medicine, University of California, San Diego, La Jolla, CA, United States.
Susan TappanRock Maple Science, LLC, Hinesburg, VT, United States.
Burak I OzyurtFAIR Data Informatics Lab, Department of Neurosciences, School of Medicine, University of California, San Diego, La Jolla, CA, United States.
Jyl BolineInformed Minds Inc, Walnut Creek, CA, United States.
Bernard de BonoWhitby et al., LLC, Indianapolis, IN, United States.
Jeffrey S GretheFAIR Data Informatics Lab, Department of Neurosciences, School of Medicine, University of California, San Diego, La Jolla, CA, United States.
Maryann E MartoneFAIR Data Informatics Lab, Department of Neurosciences, School of Medicine, University of California, San Diego, La Jolla, CA, United States.

Funding

K-CORE: Curation and Knowledge Management for SPARCOT2OD030541 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DE BONO, BERNARD, MARTONE, MARYANN E · 2020 to 2024
$10.3M
NIH HHS OT2 OD030541
6 · The paper itself

Abstract

The Stimulating Peripheral Activity to Relieve Conditions (SPARC) program is a U.S. National Institutes of Health (NIH) funded effort to enhance our understanding of the neural circuitry responsible for visceral control. SPARC's mission is to identify, extract, and compile our overall existing knowledge and understanding of the autonomic nervous system (ANS) connectivity between the central nervous system and end organs. A major goal of SPARC is to use this knowledge to promote the development of the next generation of neuromodulation devices and bioelectronic medicine for nervous system diseases. As part of the SPARC program, we have been developing the SPARC Connectivity Knowledge Base of the Autonomic Nervous System (SCKAN), a dynamic resource containing information about the origins, terminations, and routing of ANS projections. The distillation of SPARC's connectivity knowledge into this knowledge base involves a rigorous curation process to capture connectivity information provided by experts, published literature, textbooks, and SPARC scientific data. SCKAN is used to automatically generate anatomical and functional connectivity maps on the SPARC portal. In this article, we present the design and functionality of SCKAN, including the detailed knowledge engineering process developed to populate the resource with high quality and accurate data. We discuss the process from both the perspective of SCKAN's ontological representation as well as its practical applications in developing information systems. We share our techniques, strategies, tools and insights for developing a practical knowledgebase of ANS connectivity that supports continual enhancement.

Indexed as

autonomic nervous systemknowledge graphknowledge representationneural connectivityontologies

Identifiers

PMID40162160
PMCPMC11949889

What Socratic 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 Socratic graph.