MétaCan
Menu
Back to cohort
Record W7062022401

Size does not matter, but shape does : a structural neuroimaging study of the anterior cingulate cortex in acute post-traumatic stress disorder

2004· dissertation· en· W7062022401 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2004
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicGyrotron and Vacuum Electronics Research
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsAnterior cingulate cortexNeuroimagingGrey matterAmygdalaFunctional neuroimagingCingulate cortexCortex (anatomy)
DOInot available

Abstract

fetched live from OpenAlex

The neurobiological model of Post-Traumatic Stress Disorder, based upon the neurobiological model of fear-conditioning, states that the amygdala is hyperactivated, while other, inhibiting structures, like the Anterior Cingulate Cortex (ACC), are hypoactivated, therefore not fully inhibiting the amygdala. Two structural neuroimaging studies have examined the ACC volume to try to comprehend the hypoactivation of the ACC observed in subjects suffering from PTSD. Yamasue et al. (2003) found a lower grey matter density in the ACC of subjects with PTSD. Rauch et al. (2003) found a lower volume of the affective division of the ACC in subjects with PTSD compared to subjects exposed to trauma who did not suffer from PTSD. Comparing 14 subjects with Acute PTSD to 14 healthy control subjects, we replicated the results of Yamasue et al. (2003), but failed to observe any volumetric differences. Further analyses allowed us to be the first study to show that the nature of the difference observed in grey matter density was a shape difference of the ACC. Thus ACC volume does not seem to be related to Acute PTSD. Furthermore, this difference in shape raises questions as to the validity of the results of functional neuroimaging studies and of the neurobiological model of PTSD.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.272
Teacher spread0.264 · 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 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

Citations0
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueeScholarship@McGill (McGill)Same topicGyrotron and Vacuum Electronics ResearchFrench-language works237,207