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Record W3113952461 · doi:10.1111/psyp.13755

The gap prepulse inhibition of the acoustic startle (GPIAS) paradigm to assess auditory temporal processing: Monaural versus binaural presentation

2020· article· en· W3113952461 on OpenAlexafffund
Philippe Fournier, Sylvie Hébert

Bibliographic record

VenuePsychophysiology · 2020
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsUniversité de MontréalMcGill UniversityInternational Laboratory for Brain, Music and Sound Research
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsMonauralBinaural recordingAcoustic Startle ReflexPrepulse inhibitionAudiologyPsychologyHyperacusisLoudnessTinnitusAcousticsMoro reflexReflexNeurosciencePhysicsMedicineSchizophrenia (object-oriented programming)

Abstract

fetched live from OpenAlex

The Gap Prepulse Inhibition of the Acoustic Startle Reflex (GPIAS) is a paradigm used to assess auditory temporal processing in both animals and humans. It consists of the presentation of a silent gap embedded in noise and presented a few milliseconds before a startle sound. The silent gap produces the inhibition of the startle reflex, a phenomenon called gap-prepulse inhibition (GPI). This paradigm is also used to detect tinnitus in animal models. The lack of inhibition by the silent gaps is suggested to be indicative of the presence of tinnitus "filling-in" the gaps. The current research aims at improving the GPIAS technique by comparing the GPI produced by monaural versus binaural silent gaps in 29 normal-hearing subjects. Two gap durations (5 or 50 ms), each embedded in two different frequency backgrounds (centered around 500 or 4 kHz). Both low- and high- frequency narrowband noises had a bandwidth of half an octave. Overall, the startle magnitude was greater for the binaural versus the monaural presentation, which might reflect binaural loudness summation. In addition, the GPI was similar between the monaural and the binaural presentations for the high-frequency background noise. However, the GPI was greater for the low-frequency background noise for the binaural, compared to the monaural, presentation. These findings suggest that monaural GPIAS might be more suited to detect tinnitus compared to the binaural presentation.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.109
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

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

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 head0.117
GPT teacher head0.346
Teacher spread0.228 · 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

Citations11
Published2020
Admission routes2
Has abstractyes

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