Evidence map›Paper›PMID 26579071›Full record

ArticleFrontiers in neurology2015

The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke.

Maria Inez Falcon, Jeffrey D Riley, Viktor Jirsa, Anthony R McIntosh, Ahmed D Shereen, E Elinor Chen, Ana Solodkin

Abstract read
In one paragraph

Article in Frontiers in neurology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Article
  3. Mapping global brain reconfigurations following local targeted manipulations.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Whole-Brain Modelling: Past, Present, and Future.Advances in experimental medicine and biology · 2022
    Article
  9. Review
  10. Article
  11. Review
  12. Dynamical Mechanisms of Interictal Resting-State Functional Connectivity in Epilepsy.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2020
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

7 authors.

Maria Inez FalconDepartment of Anatomy and Neurobiology, University of California Irvine School of Medicine , Irvine, CA , USA.
Jeffrey D RileyDepartment of Anatomy and Neurobiology, University of California Irvine School of Medicine , Irvine, CA , USA ; Department of Neurology, University of California Irvine School of Medicine , Irvine, CA , USA.
Viktor JirsaInstitut de Neurosciences des Systèmes, Faculté de Médecine, Aix-Marseille Université , Marseille , France ; INSERM UMR1106, Aix-Marseille Université , Marseille , France.
Anthony R McIntoshRotman Research Institute, Baycrest Health Sciences, University of Toronto , Toronto, ON , Canada.
Ahmed D ShereenDepartment of Anatomy and Neurobiology, University of California Irvine School of Medicine , Irvine, CA , USA.
E Elinor ChenDepartment of Anatomy and Neurobiology, University of California Irvine School of Medicine , Irvine, CA , USA.
Ana SolodkinDepartment of Anatomy and Neurobiology, University of California Irvine School of Medicine , Irvine, CA , USA ; Department of Neurology, University of California Irvine School of Medicine , Irvine, CA , USA.

Funding

Mirror Imitation Therapy for Motor Recovery After StrokeR01NS054942 · NINDS · UNIVERSITY OF CHICAGO · PI SOLODKIN, ANA · 2007 to 2010
$1.3M
NINDS NIH HHS R01 NS054942
6 · The paper itself

Abstract

There currently remains considerable variability in stroke survivor recovery. To address this, developing individualized treatment has become an important goal in stroke treatment. As a first step, it is necessary to determine brain dynamics associated with stroke and recovery. While recent methods have made strides in this direction, we still lack physiological biomarkers. The Virtual Brain (TVB) is a novel application for modeling brain dynamics that simulates an individual's brain activity by integrating their own neuroimaging data with local biophysical models. Here, we give a detailed description of the TVB modeling process and explore model parameters associated with stroke. In order to establish a parallel between this new type of modeling and those currently in use, in this work we establish an association between a specific TVB parameter (long-range coupling) that increases after stroke with metrics derived from graph analysis. We used TVB to simulate the individual BOLD signals for 20 patients with stroke and 10 healthy controls. We performed graph analysis on their structural connectivity matrices calculating degree centrality, betweenness centrality, and global efficiency. Linear regression analysis demonstrated that long-range coupling is negatively correlated with global efficiency (P = 0.038), but is not correlated with degree centrality or betweenness centrality. Our results suggest that the larger influence of local dynamics seen through the long-range coupling parameter is closely associated with a decreased efficiency of the system. We thus propose that the increase in the long-range parameter in TVB (indicating a bias toward local over global dynamics) is deleterious because it reduces communication as suggested by the decrease in efficiency. The new model platform TVB hence provides a novel perspective to understanding biophysical parameters responsible for global brain dynamics after stroke, allowing the design of focused therapeutic interventions.

Indexed as

brain dynamicsbrain networkscomputational biophysical modelingconnectomegraph theoryimagingMRIstroke

Identifiers

PMID26579071
PMCPMC4629463

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.