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Record W2015159159 · doi:10.1111/epi.12581

Disrupted anatomic white matter network in left mesial temporal lobe epilepsy

2014· article· en· W2015159159 on OpenAlexafffund
Min Liu, Zhang Chen, Christian Beaulieu, Donald Gross

Bibliographic record

VenueEpilepsia · 2014
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchUniversity of Alberta
KeywordsWhite matterDiffusion MRITractographyPrecuneusTemporal lobeEpilepsyPsychologyNeuroscienceMedicineMagnetic resonance imagingCognitionRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Brain imaging studies have shown widespread structural abnormalities in patients with temporal lobe epilepsy (TLE) within and beyond the affected temporal lobe, suggesting an altered network. Graph theoretical analysis based on white matter tractography has provided a new perspective to evaluate the connectivity of the brain. The alterations in the topologic properties of a whole brain white matter network in patients with TLE remain unknown. The purpose of this study was to examine the white matter network in a cohort of patients with left TLE and mesial temporal sclerosis (mTLE) compared to healthy controls. METHODS: Anatomic brain networks of 16 patients with left mTLE were compared to those of 21 healthy controls. A white matter structural network was constructed from diffusion tensor tractography for each participant, and network parameters were compared between the patient and control groups. RESULTS: Patients with left mTLE exhibited concurrent decreases of global and local efficiencies and widespread reduction of regional efficiency in ipsilateral temporal, bilateral frontal, and bilateral parietal areas. Communication hubs, such as the left precuneus, were also altered in patients with mTLE compared to controls. SIGNIFICANCE: Our results demonstrate white matter network disruption in patients with left mTLE, supporting the notion that mTLE is a systemic brain disorder.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.711

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)0.0010.000

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 head0.024
GPT teacher head0.315
Teacher spread0.291 · 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 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

Citations88
Published2014
Admission routes2
Has abstractyes

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