MétaCan
Menu
Back to cohort
Record W2614338757 · doi:10.1017/s1041610217000461

BOLD activation of the ventromedial prefrontal cortex in patients with late life depression and comparison participants

2017· article· en· W2614338757 on OpenAlexaff
Akshya Vasudev, Michael Firbank, Joseph S. Gati, Emily Ionson, Alan Thomas

Bibliographic record

VenueInternational Psychogeriatrics · 2017
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsVentromedial prefrontal cortexPsychologyValence (chemistry)Late life depressionEmotional valenceNeuroimagingFunctional magnetic resonance imagingAudiologyPrefrontal cortexArousalBrain activity and meditationCognitionPsychiatryMedicineNeuroscienceElectroencephalography

Abstract

fetched live from OpenAlex

ABSTRACTThe ventromedial prefrontal cortex's (vMPFC) role in regulating emotions in late life depression (LLD) remains unclarified. We assessed vMPFC activation in an emotional valence blood oxygenation level-dependent (BOLD) functional magnetic neuroimaging (fMRI) task and related the findings to extent of white matter hyperintensities (WMH). Sixteen participants with mild to moderate LLD were compared to 14 similar aged comparison participants. Participants in the scanner viewed words matched for length and arousal, indicated the perceived valence by pressing one of the three buttons i.e. "positive, negative, or neutral." WMH volume was greater in LLD participants than comparison participants. There were no differences in activations between groups to any valence contrast. Female LLD participants showed greater activation for negative versus positive and negative versus neutral words as compared to female comparison participants. Female LLD participants respond differently to emotionally laden words compared to comparison participants. WMH could play a role in etiopathology of emotional perception in female LLD participants.

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)0.003
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 score0.004
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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 head0.034
GPT teacher head0.302
Teacher spread0.268 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational PsychogeriatricsSame topicFunctional Brain Connectivity StudiesFrench-language works237,207