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Hyperexcitability of intact neurons underlies acute development of trauma‐related electrographic seizures in cats <i>in vivo</i>

2003· article· en· W2036520904 on OpenAlexaff
Lisa Topolnik, Mircea Steriade, Igor Timofeev

Bibliographic record

VenueEuropean Journal of Neuroscience · 2003
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversité Laval
FundersNational Institute of Neurological Disorders and Stroke
KeywordsNeuroscienceEpileptogenesisBurstingCortex (anatomy)CATSCerebral cortexDisinhibitionSomatosensory systemEpilepsyPsychologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Cortical trauma can lead to development of electrographic paroxysmal activities. Current views of trauma-induced epileptogenesis suggest that chronic neuronal hyperexcitability and extensive morphological reorganization of the traumatized cortex are required for the generation of electrographic seizures. However, the mechanisms responsible for the initiation of electrographic seizures shortly after cortical injury are poorly understood. Here we show that, in the experimental model of partially deafferented (undercut) cortex, an increase in intrinsic and synaptic excitability of neurons in areas adjacent to the undercut cortex is sufficient for the generation of electrographic paroxysmal activity within few hours after partial cortical deafferentation. Locally increased and spatially restricted neuronal excitability arose from the increased incidence of intrinsically bursting neurons, enhanced intrinsic and synaptic neuronal responsiveness, and slight disinhibition. These mechanisms only operate in neurons located in the vicinity of partially deafferented sites because, after the cortical injury, partially deafferented neurons are mostly silent and hypoexcitable. Our results suggest that trauma-induced electrographic seizures first arise in cortical fields that are closest to the site of injury and such seizures do not require long-term neuronal reorganization.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.322
Teacher spread0.266 · 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.

Study designBench or experimental
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

Citations76
Published2003
Admission routes1
Has abstractyes

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