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Quantity language speakers show enhanced subcortical processing

2016· article· en· W2412252617 on OpenAlexaff
Caitlin Dawson, Daniel Aalto, Juraj Šimko, Vesa Putkinen, Mari Tervaniemi, Martti Vainio

Bibliographic record

VenueBiological Psychology · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of Alberta
FundersKansainvälisen Liikkuvuuden ja Yhteistyön KeskusAcademy of Finland
KeywordsPsychologyMismatch negativityStimulus (psychology)GermanAudiologyDuration (music)SynchronicityCommunicationLinguisticsElectroencephalographyCognitive psychologyAcousticsNeuroscience

Abstract

fetched live from OpenAlex

The complex auditory brainstem response (cABR) can reflect language-based plasticity in subcortical stages of auditory processing. It is sensitive to differences between language groups as well as stimulus properties, e.g. intensity or frequency. It is also sensitive to the synchronicity of the neural population stimulated by sound, which results in increased amplitude of wave V. Finnish is a full-fledged quantity language, in which word meaning is dependent upon duration of the vowels and consonants. Previous studies have shown that Finnish speakers have enhanced behavioural sound duration discrimination ability and larger cortical mismatch negativity (MMN) to duration change compared to German and French speakers. The next step is to find out whether these enhanced duration discrimination abilities of quantity language speakers originate at the brainstem level. Since German has a complementary quantity contrast which restricts the possible patterns of short and long vowels and consonants, the current experiment compared cABR between nonmusician Finnish and German native speakers using seven short complex stimuli. Finnish speakers had a larger cABR peak amplitude than German speakers, while the peak onset latency was only affected by stimulus intensity and spectral band. The results suggest that early cABR responses are better synchronised for Finns, which could underpin the enhanced duration sensitivity of quantity language speakers.

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 score0.449
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.137
GPT teacher head0.399
Teacher spread0.262 · 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
Published2016
Admission routes1
Has abstractyes

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