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Neuropsychology: Traditional and New Methods of Investigation

2006· review· en· W2128928166 on OpenAlexaff
Maryse Lassonde, Hannelore C. Sauerwein, Anne Gallagher, Martin Thériault, Franco Leporé

Bibliographic record

VenueEpilepsia · 2006
Typereview
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
Fundersnot available
KeywordsNeuropsychologyNeuroimagingEpilepsyPsychologyPositron emission tomographyLateralization of brain functionMagnetic resonance imagingNeuropsychological assessmentWada testCognitionNeuroscienceEpilepsy surgeryMedicineRadiology

Abstract

fetched live from OpenAlex

The neuropsychological assessment is an integral part of the clinical investigation of patients suffering from epilepsy. The aim of the evaluation is to determine disease-related and treatment-related effects on cognition and behavior in order to orient therapeutic interventions, by taking into account the compensatory mechanisms that are available to the patient. Examples of the tests best illustrating the classical neuropsychological protocol are presented. Neuropsychology also plays an important role in the assessment of language lateralization in patients slated for epilepsy surgery. Traditionally, this has been achieved by means of the rather invasive Wada procedure. However, with the advent of new neuroimaging techniques, this procedure is gradually being replaced by minimally invasive or noninvasive methods, such as functional magnetic resonance imaging, positron emission tomography, and optical imaging. In the present paper, we discuss some of the newer techniques that are available to the neuropsychologist for the study of the impact of epilepsy on cerebral functioning.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.259
GPT teacher head0.461
Teacher spread0.202 · 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.

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

Citations25
Published2006
Admission routes1
Has abstractyes

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