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Development of auditory‐specific brain rhythm in infants

2011· article· en· W2113712772 on OpenAlexafffund
Takako Fujioka, Nasser Mourad, Laurel J. Trainor

Bibliographic record

VenueEuropean Journal of Neuroscience · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsBaycrest HospitalMcMaster UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRhythmPsychologyPerceptionNeuroscienceElectroencephalographyCognitionSensory systemAudiologyMedicine

Abstract

fetched live from OpenAlex

Human infants rapidly develop their auditory perceptual abilities and acquire culture-specific knowledge in speech and music in the second 6 months of life. In the adult brain, neural rhythm around 10 Hz in the temporal lobes is thought to reflect sound analysis and subsequent cognitive processes such as memory and attention. To study when and how such rhythm emerges in infancy, we examined electroencephalogram (EEG) recordings in infants 4 and 12 months of age during sound stimulation and silence. In the 4-month-olds, the amplitudes of narrowly tuned 4-Hz brain rhythm, recorded from bilateral temporal electrodes, were modulated by sound stimuli. In the 12-month-olds, the sound-induced modulation occurred at faster 6-Hz rhythm at temporofrontal locations. The brain rhythms in the older infants consisted of more complex components, as even evident in individual data. These findings suggest that auditory-specific rhythmic neural activity, which is already established before 6 months of age, involves more speed-efficient long-range neural networks by the age of 12 months when long-term memory for native phoneme representation and for musical rhythmic features is formed. We suggest that maturation of distinct rhythmic components occurs in parallel, and that sensory-specific functions bound to particular thalamo-cortical networks are transferred to newly developed higher-order networks step by step until adult hierarchical neural oscillatory mechanisms are achieved across the whole brain.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.076
GPT teacher head0.251
Teacher spread0.175 · 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

Citations18
Published2011
Admission routes2
Has abstractyes

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