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Record W4393181701 · doi:10.1038/s41598-024-57075-1

Visual modulation of auditory evoked potentials in the cat

2024· article· en· W4393181701 on OpenAlexaff
Xiaohan Bao, Stephen G. Lomber

Bibliographic record

VenueScientific Reports · 2024
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsMcGill University
Fundersnot available
KeywordsModulation (music)ElectroencephalographyNeuroscienceFacilitationMultisensory integrationAuditory stimuliAudiologyComputer sciencePsychologyPerceptionMedicinePhysicsAcoustics

Abstract

fetched live from OpenAlex

Visual modulation of the auditory system is not only a neural substrate for multisensory processing, but also serves as a backup input underlying cross-modal plasticity in deaf individuals. Event-related potential (ERP) studies in humans have provided evidence of a multiple-stage audiovisual interactions, ranging from tens to hundreds of milliseconds after the presentation of stimuli. However, it is still unknown if the temporal course of visual modulation in the auditory ERPs can be characterized in animal models. EEG signals were recorded in sedated cats from subdermal needle electrodes. The auditory stimuli (clicks) and visual stimuli (flashes) were timed by two independent Poison processes and were presented either simultaneously or alone. The visual-only ERPs were subtracted from audiovisual ERPs before being compared to the auditory-only ERPs. N1 amplitude showed a trend of transiting from suppression-to-facilitation with a disruption at ~ 100-ms flash-to-click delay. We concluded that visual modulation as a function of SOA with extended range is more complex than previously characterized with short SOAs and its periodic pattern can be interpreted with "phase resetting" hypothesis.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.373
Teacher spread0.334 · 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 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

Citations4
Published2024
Admission routes1
Has abstractyes

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