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Record W7132993427

Synaptic Plasticity in Basal Ganglia Output Neurons in Parkinson's Disease Patients

2009· dissertation· en· W7132993427 on OpenAlexafffund
Ian A. Prescott

Bibliographic record

VenueTSpace · 2009
Typedissertation
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsUniversity of Toronto
FundersParkinson Society Canada
KeywordsBasal gangliaDopamineSubstantia nigraLong-term potentiationSynaptic plasticityPlasticityNeuroplasticityIndirect pathway of movement
DOInot available

Abstract

fetched live from OpenAlex

Parkinson’s disease (PD) is characterized by the loss of dopamine in the basal ganglia and leads to paucity of movements, rigidity of the limbs, and rest tremor. Synaptic plasticity was characterized in the substantia nigra pars reticulata (SNr), a basal ganglia output structure, in 18 PD patients undergoing implantation of deep brain stimulating electrodes. Field evoked potentials (fEPs) in SNr were measured with one microelectrode using single pulses from a second microelectrode ~ 1 mm away. High frequency stimulation (HFS – 4 trains of 2s at 100Hz) in the SNr failed to induce a lasting change in test fEPs amplitudes in patients OFF medication. Following L-Dopa, HFS induced a potentiation of the fEPs that lasted more than 150s. Our findings suggest that extrastriatal dopamine modulates activity dependent synaptic plasticity at basal ganglia output neurons. Dopamine medication state clearly impacts fEP amplitude, and the lasting nature of the increase is reminiscent of LTP-like changes, indicating that aberrant synaptic plasticity may play a role in the pathophysiology of PD.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.024
GPT teacher head0.324
Teacher spread0.299 · 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

Citations0
Published2009
Admission routes2
Has abstractyes

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