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Record W2073191284 · doi:10.1159/000188533

Subcortical Laterality of Speech Encoding

2008· article· en· W2073191284 on OpenAlexaff
Jane Hornickel, Erika Skoe, Nina Kraus

Bibliographic record

VenueAudiology and Neurotology · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsWestern University
FundersNational Institute on Deafness and Other Communication DisordersNational Institutes of HealthNorthwestern University
KeywordsLateralization of brain functionLateralityAudiologyBrainstemFormantStimulus (psychology)PsychologyPopulationNeuroscienceSpeech recognitionMedicineCognitive psychologyComputer science

Abstract

fetched live from OpenAlex

It is well established that in the majority of the population language processing is lateralized to the left hemisphere. Evidence suggests that lateralization is also present in the brainstem. In the current study, the syllable /da/ was presented monaurally to the right and left ears and electrophysiological responses from the brainstem were recorded in adults with symmetrical interaural click-evoked responses. Responses to the right-ear presentation occurred earlier than those to left-ear presentation in two peaks of the frequency following response (FFR) and approached significance for the third peak of the FFR and the offset peak. Interestingly, there were no differences in interpeak latencies indicating the response to right-ear presentation simply occurred earlier over this region. Analyses also showed more robust frequency encoding when stimuli were presented to the right ear than the left ear. The effect was found for the harmonics of the fundamental that correspond to the first formant of the stimulus, but was not seen in the fundamental frequency range. The results suggest that left lateralization of processing acoustic elements important for discriminating speech extends to the auditory brainstem and that these effects are speech specific.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.085
GPT teacher head0.306
Teacher spread0.222 · 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

Citations110
Published2008
Admission routes1
Has abstractyes

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