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Record W4402638881 · doi:10.1101/2024.09.16.24313753

Selective effects of dopaminergic and noradrenergic degeneration on cognition in Parkinson’s disease

2024· preprint· en· W4402638881 on OpenAlexaff
Sophie Sun, Victoria Madge, Jelena Djordjevic, Jean‐François Gagnon, D. Louis Collins, Alain Dagher, Madeleine Sharp

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsHôpital du Sacré-Cœur de MontréalUniversité du Québec à MontréalMontreal Neurological Institute and HospitalMcGill University
Fundersnot available
KeywordsDegeneration (medical)DopaminergicParkinson's diseaseNeuroscienceCognitionDiseaseDopaminePsychologyMedicineInternal medicinePathology

Abstract

fetched live from OpenAlex

Abstract The substantia nigra and locus coeruleus are among the first brain regions to degenerate in Parkinson’s disease. This has important implications for early cognitive deficits as these nuclei are sources of ascending neuromodulators (i.e., dopamine and noradrenaline) that support various cognitive functions like learning, memory, and executive function. However, because most studies of the relationship between patterns of degeneration and cognition have either studied these neuromodulator systems in isolation or studied specific cognitive domains in isolation, it is unknown if degeneration in the substantia nigra and degeneration in the locus coeruleus independently and selectively contribute to different cognitive deficits in Parkinson’s disease. To address this gap, we tested people with Parkinson’s disease and older adults on tasks of positive reinforcement learning, attention/working memory, executive function, and memory to measure performance in domains of cognition specifically thought to be related to dopaminergic and noradrenergic function. Participants also underwent neuromelanin-sensitive magnetic resonance imaging which provides a measure of degeneration of dopamine neurons in the substantia nigra and of noradrenergic neurons in the locus coeruleus. Brain-behaviour relationships were evaluated by separate linear regressions predicting cognitive performance in each domain from substantia nigra and locus coeruleus neuromelanin signal intensities controlling for age, sex, and education. As expected, Parkinson’s disease patients had significantly slower learning from positive feedback and lower performance on tests of attention/working memory, executive function, and memory than controls. Parkinson’s patients also had lower neuromelanin signal intensity in the substantia nigra and locus coeruleus. Examining brain-behaviour relationships, we found that reduced neuromelanin signal in the substantia nigra in Parkinson’s disease patients was independently associated with impaired positive reinforcement learning, controlling for changes in the locus coeruleus, but was not associated with other domains of cognition. In contrast, reduced neuromelanin signal in the locus coeruleus was independently associated with impairments in attention/working memory and executive function, controlling for changes in the substantia nigra, but not with reinforcement learning performance. These results show that substantia nigra degeneration and locus coeruleus degeneration independently and selectively contribute to cognitive deficits and therefore suggests that individual differences in the degree of neurodegeneration in these nuclei could explain the significant heterogeneity that exists in the cognitive and behavioural manifestations of Parkinson’s disease. These findings also highlight the potential value of leveraging known brain-behaviour relationships to develop performance-based measures of cognition that reflect underlying patterns of neurodegeneration.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

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 head0.012
GPT teacher head0.259
Teacher spread0.247 · 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
Published2024
Admission routes1
Has abstractyes

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