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Record W4402442280 · doi:10.70121/001c.123590

Periodic and Aperiodic EEG Activity in Cognitive Tasks: A Scalp Topography Study

2024· article· en· W4402442280 on OpenAlexfundno aff
Nidhi George

Bibliographic record

VenueScholarly review . · 2024
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsnot available
FundersUniversity of California, San DiegoBrock University
KeywordsAperiodic graphElectroencephalographyScalpCognitionComputer scienceAudiologyPsychologyCognitive psychologyNeuroscienceMathematicsMedicineAnatomy

Abstract

fetched live from OpenAlex

This study investigates the correlation between electrical activity patterns in various brain regions during an information-integration task using electroencephalography (EEG). EEG recordings were analyzed to find both periodic activity, in this case, Alpha power, and aperiodic activity, which is usually considered background noise. The study found that Alpha power was most prominent in the posterior regions of the brain, while aperiodic activity was most prominent in the anterior regions. Using an open EEG dataset and multiple Python packages, the study includes multiple scalp topography maps and violin plots to visualize the data. The results indicate the importance of considering both aperiodic and periodic activity in the brain during different cognitive functions, supporting previous findings about neural excitation and inhibition.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.330
Teacher spread0.276 · 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 teacher head, not a consensus.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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