Evidence map›Paper›PMID 40575249›Full record

ArticleSpora : a journal of biomathematics2025

Web Application for Simulation of an Agent-Based Model in NetLogo3D.

Chris Davis Perumal, Abraham Nofal, Benedict J Kolber, Rachael Miller Neilan

Abstract read
In one paragraph

Article in Spora : a journal of biomathematics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Chris Davis PerumalDepartment of Mathematics and Computer Science, Duquesne University, Pittsburgh, PA.
Abraham NofalDepartment of Neuroscience and Center for Advanced Pain Studies, The University of Texas at Dallas, Richardson, TX.
Benedict J KolberDepartment of Neuroscience and Center for Advanced Pain Studies, The University of Texas at Dallas, Richardson, TX.
Rachael Miller NeilanDepartment of Mathematics and Computer Science, Duquesne University, Pittsburgh, PA.

Funding

Impact of Amygdala Lateralization on Processing and Modulation of Bladder PainR01DK115478 · NIDDK · UNIVERSITY OF TEXAS DALLAS · PI BENEDICT J KOLBER · 2018 to 2026
$4.3M
The integration of laboratory data with computational 3-D modeling to analyze the role of the central amygdala in neuropathic painR15NS128624 · NINDS · DUQUESNE UNIVERSITY · PI MILLER NEILAN, RACHAEL · 2023 to 2023
$442k
NIDDK NIH HHS R01 DK115478NINDS NIH HHS R15 NS128624
6 · The paper itself

Abstract

Agent-based models (ABMs) are computer simulation models for studying systems of autonomous agents. Modelers often use specialized software like NetLogo to develop ABMs, but this software poses barriers to researchers in other disciplines with no prior programming experience. To address this issue, we developed a web application that allows users to simulate our ABM via a web browser, eliminating the need for the user to download and use specialized software. While presented in the context of a specific ABM, our approach can be applied to other ABMs to enhance accessibility. The ABM presented here was developed in NetLogo3D. The model simulates pain-related neural activity in the central nucleus of the amygdala and generates an emergent measure of pain output. The web application enables users to modify parameters, run simulations, visualize output, and export data without interacting with the model's code or downloading software, broadening access to researchers and the public.

Indexed as

accessibilityagent-based modelNetLogoneurosciencesimulation

Identifiers

PMID40575249
PMCPMC12199284

What OpenQuestion holds

Textmetadata
LicenceTDM
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.