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Record W2323472426 · doi:10.1097/wnr.0b013e32833282c8

Dopamine-dependent high-frequency oscillatory activity in thalamus and subthalamic nucleus of patients with Parkinson's disease

2009· article· en· W2323472426 on OpenAlexafffund
A. Kane, William D. Hutchison, Mojgan Hodaie, Andrés M. Lozano, Jonathan O. Dostrovsky

Bibliographic record

VenueNeuroreport · 2009
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsCanada Research ChairsToronto Western HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsSubthalamic nucleusParkinson's diseaseThalamusDopamineNeuroscienceBasal gangliaDegenerative diseaseMedicineCentral nervous system diseasePsychologyDiseaseDeep brain stimulationCentral nervous systemInternal medicine

Abstract

fetched live from OpenAlex

In recent years there has been great interest in oscillatory activity in the brain and in the role of pathological oscillations in the basal ganglia in mediating some of the symptoms of Parkinson's disease (PD). In this study, thalamic and subthalamic nucleus local field potentials were intraoperatively recorded from pairs of closely separated microelectrodes in six PD patients ON and OFF dopaminergic medication. Using correlation and coherence analyses, we found high-frequency oscillatory activity in the 110-170 Hz band in thalamus in patients OFF dopamine. These oscillations were significantly reduced after administration of dopamine-replacement therapy. In contrast, activity in the lower frequencies (the theta and beta ranges) was increased. However, in subthalamic nucleus, we observed an increase in high-frequency oscillatory activity (150-200 Hz), and a reduction of the activity in the low-frequency range after levodopa administration. These findings confirm and extend earlier findings suggesting that in PD there are marked changes in basal ganglia oscillatory activity and that these can be reversed after dopaminergic therapy.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.222
Teacher spread0.214 · 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 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

Citations30
Published2009
Admission routes2
Has abstractyes

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