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Record W4362475999 · doi:10.15540/nr.10.1.21

Intractable Epilepsy Controlled by Neurofeedback and Adjunctive Treatments: A Case Report

2023· article· en· W4362475999 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNeuroRegulation · 2023
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of GuelphYork University
Fundersnot available
KeywordsNeurofeedbackEpilepsyAdjunctive treatmentIntractable epilepsyCoachingPsychologyMedicinePsychological interventionPsychiatryElectroencephalographyPhysical therapyPhysical medicine and rehabilitationPsychotherapistInternal medicine

Abstract

fetched live from OpenAlex

This case report documents the treatment of a female patient with intractable temporal lobe epilepsy with secondary generalization. At the age of 13, the patient was hospitalized with ~120 seizures in a day, some of which were life-threatening. After hospital discharge, despite a regimen of multiple antiseizure medications, the patient still experienced ~90 seizures per day. After the interventions described in this work, over 500 neurofeedback sessions guided by EEG or qEEG data and adjunctive treatments including mental skills coaching, the patient became seizure- and medication-free, progressing from poor academic performance and inability to carry out normal daily life to attending university as a student athlete playing an NCAA Division I sport. This case emphasizes that, with professional guidance and supervision, it is possible for people with epilepsy or their caregivers to provide the extensive, long-term neurofeedback and adjunctive training necessary for reduction and control of intractable seizures.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.019
GPT teacher head0.304
Teacher spread0.285 · 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