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Record W2156822246 · doi:10.1590/0001-3765201420130301

Alcohol Effects on the P2 component of Auditory Evoked Potentials

2014· article· en· W2156822246 on OpenAlexfundno aff
Óscar Hernández, Rolando García-Martínez, Vı́ctor Monteón

Bibliographic record

VenueAnais da Academia Brasileira de Ciências · 2014
Typearticle
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsnot available
FundersUniversity of Waterloo
KeywordsAlcoholEthanolEvoked potentialStimulus (psychology)AudiologyPlaceboElectrophysiologyLatency (audio)ChemistryPsychologyMedicineNeuroscienceBiochemistryComputer scienceTelecommunicationsCognitive psychology

Abstract

fetched live from OpenAlex

This is a second part of a research aimed to study the effects of alcohol on the electrophysiological processes in student volunteers. The first part showed that alcohol slowed the Omitted Stimulus Potential (OSP). This work studied the ethanol effects on the parameters (i.e. rate of rise, amplitude and peak latency) of the P2 component of the evoked potentials (EPs) yielded by trains of auditory stimuli. It is hypothesized here that if P2 and OSP waves share some common neural processes then alcohol should also affect these specific parameters. A dose of 0.8 g/kg of alcohol or a placebo (0 g/kg) was administered to two groups of 15 young men who were tested before and again after treatment. The pre-post treatment change in each of the measurements was used to assess the treatment effects. The results showed that compared to placebo, alcohol slowed the P2 rise rate and reduced its amplitude, with no effects on peak latency. The rise rate is more sensitive to alcohol but more resistant to the adaptation process. Alcohol resembles the response inhibition model acting against the adaptation. The rise rate of the P2 and the OSP waves are affected by alcohol in a similar fashion, suggesting similar neural generative mechanisms.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.036
GPT teacher head0.288
Teacher spread0.252 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2014
Admission routes1
Has abstractyes

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