Evidence map›Paper›PMID 25767445›Full record

ReviewFrontiers in computational neuroscience2015

State-dependencies of learning across brain scales.

Petra Ritter, Jan Born, Michael Brecht, Hubert R Dinse, Uwe Heinemann, Burkhard Pleger, Dietmar Schmitz, Susanne Schreiber, Arno Villringer, Richard Kempter

Abstract readReview
In one paragraph

Review in Frontiers in computational neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. An Interactive Brain Atlas of Knowledge.bioRxiv : the preprint server for biology · 2026
    Article
  2. Article
  3. Article
  4. Neurobiological mechanisms of state-dependent learning.Current opinion in neurobiology · 2017
    Review
  5. Article
  6. Article
  7. Editorial: State-dependent brain computation.Frontiers in computational neuroscience · 2015
    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

10 authors.

Petra RitterMinerva Research Group BrainModes, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany ; Department of Neurology, Charité University Medicine Berlin Berlin, Germany ; Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany ; Berlin School of Mind and Brain & Mind and Brain Institute, Humboldt-Universität zu Berlin Berlin, Germany.
Jan BornDepartment of Medical Psychology and Behavioral Neurobiology & Center for Integrative Neuroscience (CIN), University of Tübingen Tübingen, Germany.
Michael BrechtBernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany.
Hubert R DinseNeural Plasticity Lab, Institute for Neuroinformatics, Ruhr-University Bochum Bochum, Germany ; Department of Neurology, BG University Hospital Bergmannsheil, Ruhr-University Bochum Bochum, Germany.
Uwe HeinemannBernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany ; NeuroCure Cluster of Excellence Berlin, Germany.
Burkhard PlegerClinic for Cognitive Neurology, University Hospital Leipzig Leipzig, Germany ; Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany.
Dietmar SchmitzBernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany ; NeuroCure Cluster of Excellence Berlin, Germany ; Neuroscience Research Center NWFZ, Charité University Medicine Berlin Berlin, Germany ; Max-Delbrück Center for Molecular Medicine, MDC Berlin, Germany ; Center for Neurodegenerative Diseases (DZNE) Berlin, Germany.
Susanne SchreiberBernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany ; Department of Biology, Institute for Theoretical Biology (ITB), Humboldt-Universität zu Berlin Berlin, Germany.
Arno VillringerBerlin School of Mind and Brain & Mind and Brain Institute, Humboldt-Universität zu Berlin Berlin, Germany ; Clinic for Cognitive Neurology, University Hospital Leipzig Leipzig, Germany ; Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany.
Richard KempterBernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany ; Department of Biology, Institute for Theoretical Biology (ITB), Humboldt-Universität zu Berlin Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Learning is a complex brain function operating on different time scales, from milliseconds to years, which induces enduring changes in brain dynamics. The brain also undergoes continuous "spontaneous" shifts in states, which, amongst others, are characterized by rhythmic activity of various frequencies. Besides the most obvious distinct modes of waking and sleep, wake-associated brain states comprise modulations of vigilance and attention. Recent findings show that certain brain states, particularly during sleep, are essential for learning and memory consolidation. Oscillatory activity plays a crucial role on several spatial scales, for example in plasticity at a synaptic level or in communication across brain areas. However, the underlying mechanisms and computational rules linking brain states and rhythms to learning, though relevant for our understanding of brain function and therapeutic approaches in brain disease, have not yet been elucidated. Here we review known mechanisms of how brain states mediate and modulate learning by their characteristic rhythmic signatures. To understand the critical interplay between brain states, brain rhythms, and learning processes, a wide range of experimental and theoretical work in animal models and human subjects from the single synapse to the large-scale cortical level needs to be integrated. By discussing results from experiments and theoretical approaches, we illuminate new avenues for utilizing neuronal learning mechanisms in developing tools and therapies, e.g., for stroke patients and to devise memory enhancement strategies for the elderly.

Indexed as

brain scalescomputational modelinglearningplasticitystate-dependencies

Identifiers

PMID25767445
PMCPMC4341560

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.