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Record W2752496317 · doi:10.47513/mmd.v9i3.542

Vibroacoustic Stimulation and Brain Oscillation: From Basic Research to Clinical Application

2017· article· en· W2752496317 on OpenAlex
Lee Bartel, Robert Chen, Claude Alain, Bernhard Roß

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMusic and Medicine · 2017
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsBaycrest HospitalUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsStimulationDepression (economics)NeuroscienceBrain activity and meditationBrain stimulationOscillation (cell signaling)Electrical brain stimulationCognitionPsychologyMedicineElectroencephalographyBiology

Abstract

fetched live from OpenAlex

Abstract: This paper addresses the importance of steady state brain oscillation for brain connectivity and cognition. Given that a healthy brain maintains particular levels of oscillatory activity, it argues that disturbances or dysrhythmias of this oscillatory activity can be implicated in common health conditions including Alzheimer’s disease, Parkinson’s Disease, pain, and depression. Literature is reviewed that shows that electric stimulation of the brain can contribute to regulation of neural oscillatory activity and the alleviation of related health conditions. It is then argued that specific frequencies of sound in their vibratory nature can serve as a means to brain stimulation through auditory and vibrotactile means and as such can contribute to regulation of oscillatory activity. The frequencies employed and found effective in electric stimulation are reviewed with the intent of guiding the selection of sound frequencies for vibroacoustic stimulation in the treatment of AD, PD, Pain, and depression.

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.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.947

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.294
GPT teacher head0.572
Teacher spread0.278 · 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