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Record W4412532570 · doi:10.1162/imag.a.96

The multidimensional relationship between alpha oscillations and cognition

2025· article· en· W4412532570 on OpenAlexaff
Agatha Lenartowicz, Sebastian C. Coleman, Nicolas Zink, Karen J. Mullinger

Bibliographic record

VenueImaging Neuroscience · 2025
Typearticle
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsMental Health Research Canada
FundersNational Institute of Mental HealthDeutsche ForschungsgemeinschaftUniversity of Nottingham
KeywordsAlpha (finance)CognitionPsychologyCognitive psychologyNeuroscienceDevelopmental psychologyPsychometrics

Abstract

fetched live from OpenAlex

Alpha oscillations are a robust neurophysiological phenomenon associated with cortical suppression and synaptic input gating, functionally interpreted as a mechanism of selective attention. Here, we highlight known dissociations between alpha oscillations and selective attention that question the specificity of this interpretation. We postulate that the inconsistencies are accounted for when we consider alpha oscillations as a neurophysiological mechanism that tracks cortical excitability, but one that can be modulated by a multitude of factors that include but are not limited to selective attention and include bottom-up and top-down interactions, internal processes, and regulatory system influences on cortical excitability. Thus, reverse inference regarding the cognitive role of alpha modulations may depend on experimental context. Importantly, this perspective reiterates that there exists a significant need for research that disentangles the mechanistic bases of alpha oscillations across different cognitive phenomena.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.324
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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