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Enregistrement W2936923005 · doi:10.1093/schbul/sbz019.374

T94. CORTICAL THICKNESS TRAJECTORIES IN RELATION TO CHANGES IN EXECUTIVE FUNCTION AMONG FIRST EPISODE PSYCHOSIS PATIENTS

2019· article· en· W2936923005 sur OpenAlexaff
Charlie Henri-Bellemare, Carolina Makowski, John D. Lewis, Ridha Joober, Ashok Malla, Jai Shah, Michael Bodnar, M. Mallar Chakravarty, Martín Lepage

Notice bibliographique

RevueSchizophrenia Bulletin · 2019
Typearticle
Langueen
DomaineNeuroscience
ThématiqueFunctional Brain Connectivity Studies
Établissements canadiensRoyal Ottawa Mental Health CentreMcGill University
Organismes subventionnairesnon disponible
Mots-clésPsychosisPsychologySchizophrenia (object-oriented programming)AudiologyCognitionMedicineClinical psychologyPsychiatryNeuroscience

Résumé

récupéré en direct d'OpenAlex

Disorganized thinking and executive function impairments are often present in patients with psychosis. Several studies have found associations between cognitive abilities and cortical thickness in schizophrenia; however, only a few studies have investigated cortical thickness relative to executive function (EF) in patients with a first episode of psychosis (FEP) compared with healthy controls (HC), using cross-sectional study designs. Moreover, the direction of findings from these studies have been inconsistent, although results converge on the idea that EF are differentially related to brain structure in patients. The present study aims to examine longitudinal relationships between changes in cortical thickness and EF in individuals with a FEP relative to HC using structural brain imaging. Structural T1-weighted images were acquired on a 3T scanner for patients (n=21) and controls (n=28). Two to four timepoints were completed per subject, over a period of approximately 3–21 months. The Groton Maze Learning test and Set Shifting test from the CogState computerized battery were collected as measures of EF. Images were processed using the CIVET pipeline, and all cortical thickness-related analyses were performed across 81,924 vertices of the cortical surface, using the SurfStat toolbox in Matlab. A slope of CT at every vertex across the brain and a slope of EF across available timepoints per subject were independently calculated and subsequently used in the analysis. A linear model was applied to test for the main effect of change in EF to change in CT per group, and to assess the interaction between group and change in EF on cortical thickness rates of change. Models controlled for age and sex. For both sets of analyses, resultant t-statistic maps were thresholded and corrected for multiple comparisons with Random Field Theory (RFT), with a stringent cluster-threshold of p=0.005. Exploration of results was also done with a more relaxed threshold of p=0.01. A significant negative main effect of change in EF on change in CT was observed for HC in the right insula (i.e. improvement in EF was related to cortical thinning); additionally, the right cingulate gyrus was significant with a relaxed threshold of p=0.01. The main effect of change in EF on changes in CT was not significant for FEP patients. The interaction between change in EF and group was found to be significant, where negative associations between change in EF and change in CT were driven by HC. Specifically, a negative association of change in EF was found in right insula, right supramarginal gyrus and the left ventrolateral prefrontal cortex, whereas no such relationship was observed in patients. To our knowledge, longitudinal changes in cortical thickness relative to changes in EF have not been investigated before in FEP. Findings from this study suggest there are no significant associations between change in CT and change in EF among individuals early in the course of psychosis. Significant associations found in controls suggest that steeper improvements in EF is associated with cortical thinning in frontal-parietal regions. These results are consistent with a cross-sectional study in healthy adolescents suggesting that more rapid structural maturation in higher-order brain regions characterized by protracted development is associated with improvement in cognitive abilities. It is possible that in patients, these maturational patterns are altered and/or more diffuse, and thus, not as readily localized with a univariate analysis. We suggest that future studies should examine such brain-behaviour relationships in FEP with brain network approaches.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,018

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,014
Tête enseignante GPT0,230
Écart entre enseignants0,215 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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