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Record W1540038165 · doi:10.1177/1073858415591964

Deep Brain Stimulation

2015· article· en· W1540038165 on OpenAlexaff
Gerson Florence, Koichi Sameshima, Erich Talamoni Fonoff, Clement Hamani

Bibliographic record

VenueThe Neuroscientist · 2015
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsToronto Western HospitalUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsNeuroscienceDeep brain stimulationStimulationExtracellularPremovement neuronal activityPotassium channelIntracellularNeocortexChemistryBiologyBiophysicsMedicineCell biologyInternal medicine

Abstract

fetched live from OpenAlex

High-frequency deep brain stimulation (DBS) is an effective treatment for some movement disorders. Though mechanisms underlying DBS are still unclear, commonly accepted theories include a "functional inhibition" of neuronal cell bodies and the excitation of axonal projections near the electrodes. It is becoming clear, however, that the paradoxical dissociation "local inhibition" and "distant excitation" is far more complex than initially thought. Despite an initial increase in neuronal activity following stimulation, cells are often unable to maintain normal ionic concentrations, particularly those of sodium and potassium. Based on currently available evidence, we proposed an alternative hypothesis. Increased extracellular concentrations of potassium during DBS may change the dynamics of both cells and axons, contributing not only to the intermittent excitation and inhibition of these elements but also to interrupt abnormal pathological activity. In this article, we review mechanisms through which high extracellular potassium may mediate some of the effects of DBS.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.004

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 head0.053
GPT teacher head0.312
Teacher spread0.259 · 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

Citations74
Published2015
Admission routes1
Has abstractyes

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