Evidence map›Paper›PMID 39006246›Full record

ArticleSpora : a journal of biomathematics2024

Improved Efficiency and Sensitivity Analysis of 3-D Agent-based Model for Pain-related Neural Activity in the Amygdala.

Kayla Kraeuter, Carley Reith, Benedict J Kolber, Rachael Miller Neilan

Abstract read
In one paragraph

Article in Spora : a journal of biomathematics, 2024. 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. Article
  2. Article
  3. Review
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.

Kayla KraeuterDepartment of Mathematics and Computer Science, Duquesne University, Pittsburgh, PA.
Carley ReithDepartment of Mathematics and Computer Science, Duquesne University, Pittsburgh, PA.
Benedict J KolberDepartment of Neuroscience and Center for Advanced Pain Studies, 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

Neuropathic pain is caused by nerve injury and involves brain areas such as the central nucleus of the amygdala (CeA). We developed the first 3-D agent-based model (ABM) of neuropathic pain-related neurons in the CeA using NetLogo3D. The execution time of a single ABM simulation using realistic parameters (e.g., 13,000 neurons and 22,000+ neural connections) is an important factor in the model's usability. In this paper, we describe our efforts to improve the computational efficiency of our 3-D ABM, which resulted in a 28% reduction in execution time on average for a typical simulation. With this upgraded model, we performed one- and two-parameter sensitivity analyses to study the sensitivity of model output to variability in several key parameters along the anterior to posterior axis of the CeA. These results highlight the importance of computational modeling in exploring spatial and cell-type specific properties of brain regions to inform future wet lab experiments.

Indexed as

agent-based modelamygdalaNetLogopainsensitivity analysis

Identifiers

PMID39006246
PMCPMC11243734

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.