Evidence map›Paper›PMID 30133448›Full record

ArticlePLoS computational biology2018

NFTsim: Theory and Simulation of Multiscale Neural Field Dynamics.

Paula Sanz-Leon, Peter A Robinson, Stuart A Knock, Peter M Drysdale, Romesh G Abeysuriya, Felix K Fung, Chris J Rennie, Xuelong Zhao

Abstract read
In one paragraph

Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Whole-Brain Modelling: Past, Present, and Future.Advances in experimental medicine and biology · 2022
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. 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

8 authors.

Paula Sanz-LeonSchool of Physics, University of Sydney, Sydney, Australia.ORCID 0000-0002-1545-6380
Peter A RobinsonSchool of Physics, University of Sydney, Sydney, Australia.
Stuart A KnockSchool of Physics, University of Sydney, Sydney, Australia.
Peter M DrysdaleSchool of Physics, University of Sydney, Sydney, Australia.
Romesh G AbeysuriyaSchool of Physics, University of Sydney, Sydney, Australia.ORCID 0000-0002-9618-6457
Felix K FungSchool of Physics, University of Sydney, Sydney, Australia.
Chris J RennieSchool of Physics, University of Sydney, Sydney, Australia.
Xuelong ZhaoSchool of Physics, University of Sydney, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A user ready, portable, documented software package, NFTsim, is presented to facilitate numerical simulations of a wide range of brain systems using continuum neural field modeling. NFTsim enables users to simulate key aspects of brain activity at multiple scales. At the microscopic scale, it incorporates characteristics of local interactions between cells, neurotransmitter effects, synaptodendritic delays and feedbacks. At the mesoscopic scale, it incorporates information about medium to large scale axonal ranges of fibers, which are essential to model dissipative wave transmission and to produce synchronous oscillations and associated cross-correlation patterns as observed in local field potential recordings of active tissue. At the scale of the whole brain, NFTsim allows for the inclusion of long range pathways, such as thalamocortical projections, when generating macroscopic activity fields. The multiscale nature of the neural activity produced by NFTsim has the potential to enable the modeling of resulting quantities measurable via various neuroimaging techniques. In this work, we give a comprehensive description of the design and implementation of the software. Due to its modularity and flexibility, NFTsim enables the systematic study of an unlimited number of neural systems with multiple neural populations under a unified framework and allows for direct comparison with analytic and experimental predictions. The code is written in C++ and bundled with Matlab routines for a rapid quantitative analysis and visualization of the outputs. The output of NFTsim is stored in plain text file enabling users to select from a broad range of tools for offline analysis. This software enables a wide and convenient use of powerful physiologically-based neural field approaches to brain modeling. NFTsim is distributed under the Apache 2.0 license.

Indexed as

AlgorithmsAnimalsAxonsBrainComputational BiologyGene Regulatory NetworksHumansModels, TheoreticalNerve NetNeuronsNormal DistributionSoftware

Identifiers

PMID30133448
PMCPMC6122812

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.