Evidence map›Paper›PMID 27600689›Full record

ArticleHuman brain mapping2017

Real-time estimation of dynamic functional connectivity networks.

Ricardo Pio Monti, Romy Lorenz, Rodrigo M Braga, Christoforos Anagnostopoulos, Robert Leech, Giovanni Montana

Abstract read
In one paragraph

Article in Human brain mapping, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Closed-loop fMRI at the mesoscopic scale of columns and layers: Can we do it and why would we want to?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Article
  3. Article
  4. Article
  5. Is it time to put rest to rest?Trends in cognitive sciences · 2021
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. 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

6 authors.

Ricardo Pio MontiDepartment of Mathematics, Imperial College London, London, United Kingdom.
Romy LorenzThe Computational, Cognitive and Clinical Neuroimaging Laboratory, the Division of Brain Sciences, Imperial College London, London, United Kingdom.
Rodrigo M BragaDepartment of Mathematics, Imperial College London, London, United Kingdom.
Christoforos AnagnostopoulosDepartment of Mathematics, Imperial College London, London, United Kingdom.
Robert LeechThe Computational, Cognitive and Clinical Neuroimaging Laboratory, the Division of Brain Sciences, Imperial College London, London, United Kingdom.
Giovanni MontanaDepartment of Mathematics, Imperial College London, London, United Kingdom.

Funding

Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
NIMH NIH HHS U54 MH091657Wellcome Trust 103980
6 · The paper itself

Abstract

Two novel and exciting avenues of neuroscientific research involve the study of task-driven dynamic reconfigurations of functional connectivity networks and the study of functional connectivity in real-time. While the former is a well-established field within neuroscience and has received considerable attention in recent years, the latter remains in its infancy. To date, the vast majority of real-time fMRI studies have focused on a single brain region at a time. This is due in part to the many challenges faced when estimating dynamic functional connectivity networks in real-time. In this work, we propose a novel methodology with which to accurately track changes in time-varying functional connectivity networks in real-time. The proposed method is shown to perform competitively when compared to state-of-the-art offline algorithms using both synthetic as well as real-time fMRI data. The proposed method is applied to motor task data from the Human Connectome Project as well as to data obtained from a visuospatial attention task. We demonstrate that the algorithm is able to accurately estimate task-related changes in network structure in real-time. Hum Brain Mapp 38:202-220, 2017. © 2016 Wiley Periodicals, Inc.

Indexed as

Brain MappingModels, NeurologicalAttentionBrainComputer SimulationCuesFemaleFunctional LateralityHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMotor ActivityNeural PathwaysOxygenPhotic StimulationOxygendynamic networksfunctional connectivityneurofeedbackreal-timestreaming penalized optimization

Identifiers

PMID27600689
PMCPMC6639120

What OpenQuestion holds

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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.