Evidence map›Paper›PMID 24772077›Full record

ReviewFrontiers in computational neuroscience2014

The role of alpha-rhythm states in perceptual learning: insights from experiments and computational models.

Rodrigo Sigala, Sebastian Haufe, Dipanjan Roy, Hubert R Dinse, Petra Ritter

Abstract readReview
In one paragraph

Review in Frontiers in computational neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
–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

35 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. 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

5 authors.

Rodrigo SigalaDepartment Neurology, Charité-University Medicine Berlin, Germany ; Bernstein Focus State Dependencies of Learning, Bernstein Center for Computational Neuroscience Berlin, Germany.
Sebastian HaufeDepartment Neurology, Charité-University Medicine Berlin, Germany ; Bernstein Focus State Dependencies of Learning, Bernstein Center for Computational Neuroscience Berlin, Germany.
Dipanjan RoyDepartment Neurology, Charité-University Medicine Berlin, Germany ; Bernstein Focus State Dependencies of Learning, Bernstein Center for Computational Neuroscience Berlin, Germany.
Hubert R DinseNeural Plasticity Lab, Institute for Neuroinformatics, Ruhr-University Bochum Bochum, Germany.
Petra RitterDepartment Neurology, Charité-University Medicine Berlin, Germany ; Bernstein Focus State Dependencies of Learning, Bernstein Center for Computational Neuroscience Berlin, Germany ; Minerva Research Group BrainModes, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany ; Berlin School of Mind and Brain, Mind and Brain Institute, Humboldt University Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the past two decades growing evidence indicates that brain oscillations in the alpha band (~10 Hz) not only reflect an "idle" state of cortical activity, but also take a more active role in the generation of complex cognitive functions. A recent study shows that more than 60% of the observed inter-subject variability in perceptual learning can be ascribed to ongoing alpha activity. This evidence indicates a significant role of alpha oscillations for perceptual learning and hence motivates to explore the potential underlying mechanisms. Hence, it is the purpose of this review to highlight existent evidence that ascribes intrinsic alpha oscillations a role in shaping our ability to learn. In the review, we disentangle the alpha rhythm into different neural signatures that control information processing within individual functional building blocks of perceptual learning. We further highlight computational studies that shed light on potential mechanisms regarding how alpha oscillations may modulate information transfer and connectivity changes relevant for learning. To enable testing of those model based hypotheses, we emphasize the need for multidisciplinary approaches combining assessment of behavior and multi-scale neuronal activity, active modulation of ongoing brain states and computational modeling to reveal the mathematical principles of the complex neuronal interactions. In particular we highlight the relevance of multi-scale modeling frameworks such as the one currently being developed by "The Virtual Brain" project.

Indexed as

alpha rhythmattentioncognitionlarge-scale modelinglearningmemoryoscillations

Identifiers

PMID24772077
PMCPMC3983484

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.