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Record W3205705483 · doi:10.3390/neuroglia2010005

Neurovascular Coupling in Seizures

2021· article· en· W3205705483 on OpenAlexafffund
G. Campbell Teskey, Cam Ha T. Tran

Bibliographic record

VenueNeuroglia · 2021
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Calgary
FundersNational Institute of General Medical SciencesCanadian Institutes of Health Research
KeywordsNeurovascular bundleCerebral blood flowNeuroscienceEpilepsyFunctional imagingNeuroimagingMedicineCoupling (piping)Blood flowHemodynamicsPsychologyCardiologyAnesthesiaAnatomy

Abstract

fetched live from OpenAlex

Neurovascular coupling is a key control mechanism in cerebral blood flow (CBF) regulation. Importantly, this process was demonstrated to be affected in several neurological disorders, including epilepsy. Neurovascular coupling (NVC) is the basis for functional brain imaging, such as PET, SPECT, fMRI, and fNIRS, to assess and map neuronal activity, thus understanding NVC is critical to properly interpret functional imaging signals. However, hemodynamics, as assessed by these functional imaging techniques, continue to be used as a surrogate to map seizure activity; studies of NVC and cerebral blood flow control during and following seizures are rare. Recent studies have provided conflicting results, with some studies showing focal increases in CBF at the onset of a seizure while others show decreases. In this brief review article, we provide an overview of the current knowledge state of neurovascular coupling and discuss seizure-related alterations in neurovascular coupling and CBF control.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.020
GPT teacher head0.312
Teacher spread0.292 · 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

Citations10
Published2021
Admission routes2
Has abstractyes

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