Evidence map›Paper›PMID 34672259›Full record

ArticleeLife2021

Modality-specific tracking of attention and sensory statistics in the human electrophysiological spectral exponent.

Leonhard Waschke, Thomas Donoghue, Lorenz Fiedler, Sydney Smith, Douglas D Garrett, Bradley Voytek, Jonas Obleser

Abstract read
In one paragraph

Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 129 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
129citing papers in PubMed, 2 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

129 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Neural and autonomic predictors of future listening errors.bioRxiv : the preprint server for biology · 2026
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  14. Brain-computer interface-based neurofeedback training enables transferable control of cortical state switching in humans.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  20. Thalamocortical network dynamics in focal epilepsy: SEEG investigation.bioRxiv : the preprint server for biology · 2026
    Article

69 more citing papers are in PubMed but not listed here.

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.

Leonhard WaschkeMax Planck UCL Centre for Computational Psychiatry and Ageing Research, Max Planck Institute for Human Development, Berlin, Germany.ORCID 0000-0002-1248-9259
Thomas DonoghueDepartment of Cognitive Science, University of California, San Diego, La Jolla, United States.ORCID 0000-0001-5911-0472
Lorenz FiedlerEriksholm Research Centre, Oticon A/S, Snekkersten, Denmark.ORCID 0000-0002-7892-6917
Sydney SmithNeurosciences Graduate Program, University of California, San Diego, La Jolla, United States.
Douglas D GarrettMax Planck UCL Centre for Computational Psychiatry and Ageing Research, Max Planck Institute for Human Development, Berlin, Germany.ORCID 0000-0002-0629-7672
Bradley Voytek *Department of Cognitive Science, University of California, San Diego, La Jolla, United States.ORCID 0000-0003-1640-2525
Jonas Obleser *Department of Psychology, University of Lübeck, Lübeck, Germany.ORCID 0000-0002-7619-0459

Funding

Tools for parameterizing and visualizing electrophysiological rhythmic and arrhythmic featuresR01GM134363 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI VOYTEK, BRADLEY T. · 2019 to 2022
$1.4M
NIGMS NIH HHS R01 GM134363
6 · The paper itself

Abstract

A hallmark of electrophysiological brain activity is its 1/f-like spectrum - power decreases with increasing frequency. The steepness of this 'roll-off' is approximated by the spectral exponent, which in invasively recorded neural populations reflects the balance of excitatory to inhibitory neural activity (E:I balance). Here, we first establish that the spectral exponent of non-invasive electroencephalography (EEG) recordings is highly sensitive to general (i.e., anaesthesia-driven) changes in E:I balance. Building on the EEG spectral exponent as a viable marker of E:I, we then demonstrate its sensitivity to the focus of selective attention in an EEG experiment during which participants detected targets in simultaneous audio-visual noise. In addition to these endogenous changes in E:I balance, EEG spectral exponents over auditory and visual sensory cortices also tracked auditory and visual stimulus spectral exponents, respectively. Individuals' degree of this selective stimulus-brain coupling in spectral exponents predicted behavioural performance. Our results highlight the rich information contained in 1/f-like neural activity, providing a window into diverse neural processes previously thought to be inaccessible in non-invasive human recordings.

Indexed as

Acoustic StimulationAnesthetics, IntravenousAttentionBrainElectroencephalographyElectrophysiological PhenomenaFemaleHumansKetamineMalePhotic StimulationPropofolYoung AdultAnesthetics, IntravenousKetaminePropofolEEGelectrophysiologyhumanneuroscience

Identifiers

PMID34672259
PMCPMC8585481

What OpenQuestion holds

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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.