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Record W2053988321 · doi:10.1093/brain/awu084

Uncovering the role of the insula in non-motor symptoms of Parkinson’s disease

2014· review· en· W2053988321 on OpenAlexafffund
Leigh Christopher, Yuko Koshimori, Anthony E. Lang, Marion Criaud, Antonio P. Strafella

Bibliographic record

VenueBrain · 2014
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsToronto Western HospitalUniversity of TorontoCentre for Addiction and Mental Health
FundersCanadian Institutes of Health Research
KeywordsInsulaNeuroscienceParkinson's diseasePsychologyCognitionNeuroimagingSomatosensory systemDiseaseMedicinePathology

Abstract

fetched live from OpenAlex

Patients with Parkinson's disease experience a range of non-motor symptoms, including cognitive impairment, behavioural changes, somatosensory and autonomic disturbances. The insula, which was once thought to be primarily a limbic cortical structure, is now known to be highly involved in integrating somatosensory, autonomic and cognitive-affective information to guide behaviour. Thus, it acts as a central hub for processing relevant information related to the state of the body as well as cognitive and mood states. Despite these crucial functions, the insula has been largely overlooked as a potential key region in contributing to non-motor symptoms of Parkinson's disease. The insula is affected in Parkinson's disease by alpha-synuclein deposition, disruptions in normal neurotransmitter function, alterations in connectivity as well as metabolic and structural changes. Although research focusing on the role of the insula in Parkinson's disease is scarce, there is evidence from neuroimaging studies linking the insula to cognitive decline, behavioural abnormalities and somatosensory disturbances. Here, we review imaging studies that provide insight into the potential role of the insula in Parkinson's disease non-motor symptoms.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.012
GPT teacher head0.279
Teacher spread0.267 · 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 designOther design
Domainnot available
GenreReview

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

Citations171
Published2014
Admission routes2
Has abstractyes

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