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Record W2958203696 · doi:10.1101/696914

Hysteresis in the selective synchronization of brain activity to musical rhythm

2019· preprint· en· W2958203696 on OpenAlexaff
Tomas Lenc, Peter E. Keller, Manuel Varlet, Sylvie Nozaradan

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsInternational Laboratory for Brain, Music and Sound Research
Fundersnot available
KeywordsRhythmStimulus (psychology)PerceptionPsychologyEntrainment (biomusicology)Active listeningCommunicationNeural correlates of consciousnessContext (archaeology)Speech recognitionCognitive psychologyAcousticsAudiologyNeuroscienceComputer scienceCognitionPhysicsBiology

Abstract

fetched live from OpenAlex

Abstract When listening to musical rhythm, people tend to spontaneously perceive and move along with a periodic pulse-like meter. Moreover, perception and entrainment to the meter show remarkable stability in the face of dynamically changing rhythmic structure of music, even when acoustic cues to meter frequencies are degraded in the rhythmic input. Here we show that this perceptual phenomenon is supported by a selective synchronization of endogenous brain activity to the perceived meter, and that this neural synchronization is significantly shaped by recent context, especially when the incoming input becomes increasingly ambiguous. We recorded the EEG while non-musician and musician participants listened to nonrepeating rhythmic sequences where acoustic cues to meter frequencies either gradually decreased (from regular to ambiguous) or increased (from ambiguous to regular). We observed that neural activity selectively synchronized to the perceived meter persisted longer when the sequence gradually changed from regular to ambiguous compared to the opposite, thus demonstrating hysteresis in the neural processing of a dynamically changing rhythmic stimulus. This dependence on recent context was weaker in the neural responses of musicians, who also showed greater ability to tap along with a regular meter irrespective of stimulus ambiguity, thus reflecting greater stability relative to current and recent stimulus in musicians. Together, these asymmetric context effects demonstrate how the relative contribution of incoming and prior signals is continuously weighted to shape neural selection of functionally-relevant features and guide perceptual organization of dynamic input. Significance statement When listening to musical rhythm, people tend to spontaneously perceive and move along with a periodic pulse-like meter. Moreover, perception and entrainment to the meter seem to show remarkable stability in the face of dynamically changing rhythmic structure of music. Here we show that this is supported by a selective synchronization of brain activity at meter frequencies. This selective neural synchronization persists longer when a nonrepeating sequence gradually transforms from a regular to an ambiguous rhythm compared to the opposite. This asymmetric context effect suggests that the brain processes rhythm based on a flexible combination of sensory and endogenous information. Such continuously updated neural emphasis on meter periodicities might therefore guide robust perceptual organization of a dynamic rhythmic input.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 head0.019
GPT teacher head0.234
Teacher spread0.216 · 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 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

Citations5
Published2019
Admission routes1
Has abstractyes

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