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The neural circuitry of pain as explored with functional MRI

2000· review· en· W72134949 on OpenAlexaff
Karen D. Davis

Bibliographic record

VenueNeurological Research · 2000
Typereview
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of Toronto
FundersMedical Research CouncilFondation pour la Recherche MédicaleWhitehall Foundation
KeywordsFunctional magnetic resonance imagingNeuroscienceSomatosensory systemThalamusSensory systemPsychologyAnterior cingulate cortexCingulate cortexStimulus (psychology)Secondary somatosensory cortexNoxious stimulusInsulaMedicineCognitionNociceptionCentral nervous systemCognitive psychology

Abstract

fetched live from OpenAlex

Since the discovery in the early 1990s that magnetic resonance imaging (MRI) can be used for functional imaging of the human brain, the technique has been used to examine the contribution of thalamic and cortical areas to the human pain experience. In a series of studies in this laboratory, functional MRI (fMRI) of noxious heat-, cold-, and median nerve stimulation-evoked activations demonstrated the involvement of the thalamus and multiple cortical areas in pain. The cortical areas identified included the primary and secondary somatosensory cortex (S1, S2), the anterior insula and the anterior cingulate cortex. The data also revealed a significant intersubject variability in the activation of any one of these regions, particularly during heat- and cold-evoked pain. These findings revealed the widespread cortical regions that are recruited by a noxious stimulus and provide clues to the neural circuitry of pain that undoubtedly include sensory, motor and cognitive components.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.313
GPT teacher head0.445
Teacher spread0.133 · 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 designNot applicable
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

Citations146
Published2000
Admission routes1
Has abstractyes

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