Adverse Life Experiences and Brain Function
Notice bibliographique
Résumé
Importance: Adverse life experiences have been proposed to contribute to diverse mental health problems through an association with corticolimbic functioning. Despite compelling evidence from animal models, findings from studies in humans have been mixed; activation likelihood estimation (ALE) meta-analyses have failed to identify a consistent association of adverse events with brain function. Objective: To investigate the association of adversity exposure with altered brain reactivity using multilevel kernel density analyses (MKDA), a meta-analytic approach considered more robust than ALE to small sample sizes and methodological differences between studies. Data Sources: Searches were conducted using PsycInfo, Medline, EMBASE, and Web of Science from inception through May 4, 2022. The following search term combinations were used for each database: trauma, posttraumatic stress disorder (PTSD), abuse, maltreatment, poverty, adversity, or stress; and functional magnetic resonance imaging (fMRI) or neuroimaging; and emotion, emotion regulation, memory, memory processing, inhibitory control, executive functioning, reward, or reward processing. Study Selection: Task-based fMRI studies within 4 domains (emotion processing, memory processing, inhibitory control, and reward processing) that included a measure of adverse life experiences and whole-brain coordinate results reported in Talairach or Montreal Neurological Institute space were included. Conference abstracts, books, reviews, meta-analyses, opinions, animal studies, articles not in English, and studies with fewer than 5 participants were excluded. Data Extraction and Synthesis: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline, 2 independent reviewers assessed abstracts and full-text articles for entry criteria. A third reviewer resolved conflicts and errors in data extraction. Data were pooled using a random-effects model and data analysis occurred from August to November 2022. Main Outcomes and Measures: Peak activation x-axis (left-right), y-axis (posterior-anterior), and z-axis (inferior-superior) coordinates were extracted from all studies and submitted to MKDA meta-analyses. Results: A total of 83 fMRI studies were included in the meta-analysis, yielding a combined sample of 5242 participants and 801 coordinates. Adversity exposure was associated with higher amygdala reactivity (familywise error rate corrected at P < .001; x-axis = 22; y-axis = -4; z-axis = -17) and lower prefrontal cortical reactivity (familywise error rate corrected at P < .001; x-axis = 10; y-axis = 60; z-axis = 10) across a range of task domains. These altered responses were only observed in studies that used adult participants and were clearest among those who had been exposed to severe threat and trauma. Conclusions and Relevance: In this meta-analysis of fMRI studies of adversity exposure and brain function, prior adversity exposure was associated with altered adult brain reactivity to diverse challenges. These results might better identify how adversity diminishes the ability to cope with later stressors and produces enduring susceptibility to mental health problems.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,037 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».