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Record W2946658038 · doi:10.1101/647628

The Effect of Aging, Parkinson’s Disease, and Exogenous Dopamine on the Neural Response Associated with Auditory Regularity Processing

2019· preprint· en· W2946658038 on OpenAlexafffund
Abdullah Al Jaja, Jessica A. Grahn, Björn Herrmann, Penny A. MacDonald

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundAcademic Medical Organization of Southwestern Ontario
KeywordsDopaminergicDopamineParkinson's diseaseElectroencephalographyPsychologyVentral tegmental areaNeuroscienceAudiologyDiseaseMedicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Processing regular patterns in auditory scenes is important for navigating complex environments. Electroencephalography (EEG) studies find enhancement of sustained brain activity, correlating with the emergence of a regular pattern in sounds. How aging, aging-related diseases such as Parkinson’s disease (PD), and treatment of PD affect this fundamental function remain unknown. We addressed this knowledge gap. Healthy younger and older adults, and PD patients listened to sounds that contained or were devoid of regular patterns. Healthy older adults and PD patients were tested twice—on and off dopaminergic medication in counterbalanced order. Regularity-evoked, sustained EEG activity was reduced in older, compared to younger adults. PD patients and older controls had comparable attenuation of the sustained response. Dopaminergic therapy further weakened the sustained response in both groups. These findings suggest that fundamental regularity processing is impacted by aging-related neural changes but not those underlying PD. The finding that dopaminergic therapy attenuates rather than improves the sustained response coheres with the dopamine overdose response and implicates brain regions receiving dopamine from the ventral tegmental area in regularity processing.

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)0.000
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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