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Rhythm in the Premature Neonate Brain: Very Early Processing of Auditory Beat and Meter

2023· article· en· W4324027869 on OpenAlexafffund
Mohammadreza Edalati, Fabrice Wallois, Javad Safaie, Ghida Ghostine, Guy Kongolo, Laurel J. Trainor, Sahar Moghimi

Bibliographic record

VenueJournal of Neuroscience · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcMaster UniversityBaycrest Hospital
FundersCanadian Institutes of Health ResearchFondation Pour l'AuditionCanadian Institute for Advanced Research
KeywordsRhythmBeat (acoustics)AudiologyPsychologyElectroencephalographyCommunicationNeuroscienceSpeech recognitionComputer scienceAcousticsMedicinePhysics

Abstract

fetched live from OpenAlex

The ability to extract rhythmic structure is important for the development of language, music, and social communication. Although previous studies show infants' brains entrain to the periodicities of auditory rhythms and even different metrical interpretations (e.g., groups of two vs three beats) of ambiguous rhythms, whether the premature brain tracks beat and meter frequencies has not been explored previously. We used high-resolution electroencephalography while premature infants (n= 19, 5 male; mean age, 32 ± 2.59 weeks gestational age) heard two auditory rhythms in the incubators. We observed selective enhancement of the neural response at both beat- and meter-related frequencies. Further, neural oscillations at the beat and duple (groups of 2) meter were phase aligned with the envelope of the auditory rhythmic stimuli. Comparing the relative power at beat and meter frequencies across stimuli and frequency revealed evidence for selective enhancement of duple meter. This suggests that even at this early stage of development, neural mechanisms for processing auditory rhythms beyond simple sensory coding are present. Our results add to a few previous neuroimaging studies demonstrating discriminative auditory abilities of premature neural networks. Specifically, our results demonstrate the early capacities of the immature neural circuits and networks to code both simple beat and beat grouping (i.e., hierarchical meter) regularities of auditory sequences. Considering the importance of rhythm processing for acquiring language and music, our findings indicate that even before birth, the premature brain is already learning this important aspect of the auditory world in a sophisticated and abstract way. SIGNIFICANCE STATEMENTProcessing auditory rhythm is of great neurodevelopmental importance. In an electroencephalography experiment in premature newborns, we found converging evidence that when presented with auditory rhythms, the premature brain encodes multiple periodicities corresponding to beat and beat grouping (meter) frequencies, and even selectively enhances the neural response to meter compared with beat, as in human adults. We also found that the phase of low-frequency neural oscillations aligns to the envelope of the auditory rhythms and that this phenomenon becomes less precise at lower frequencies. These findings demonstrate the initial capacities of the developing brain to code auditory rhythm and the importance of special care to the auditory environment of this vulnerable population during a highly dynamic period of neural development.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 head0.046
GPT teacher head0.298
Teacher spread0.252 · 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 designObservational
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

Citations44
Published2023
Admission routes2
Has abstractyes

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