O7.2. ALTERED HIPPOCAMPAL CENTRALITY IN RELATION TO COORDINATED CHANGES OF INTRACORTICAL MICROSTRUCTURE IN FIRST EPISODE PSYCHOSIS
Notice bibliographique
Résumé
The hippocampus and associated circuitry are integral to the manifestation of psychosis and associated symptoms. There is evidence for the hippocampus as a key hub in healthy brain networks, which situates the hippocampus as an important target in the emerging view of psychosis as a disorder of altered connectome development. Here, we test the hypothesis that longitudinal changes in the hippocampus and surrounding white matter in relation to coordinated changes within intracortical (IC) and superficial white matter (SWM) microstructure in first episode psychosis (FEP) patients is altered compared to controls. We also examine whether such alterations are associated with changes in negative symptoms and verbal memory, two significant predictors of functional outcome. Longitudinal MRI scans (3T; 2–4 visits over 3–21 months) were acquired for 23 FEP and 26 HC. MP2RAGE quantitative T1 (qT1) maps, sensitive to myelin content, were used to sample microstructure of the hippocampus, IC and SWM regions. Mean qT1 for hippocampal subfields and output circuitry (fimbria, alveus, fornix, mammillary bodies) were calculated based on labels extracted from high-resolution T2-weighted scans (0.64 mm3) with MAGeT-Brain. IC qT1 was defined as the average qT1 at 35/45/55/65% cortical depths, and SWM qT1 was sampled 1mm below the grey-white matter boundary, across 81924 points of the brain surface, in relation to grey and white matter surfaces generated by CIVET. Cortical regions were then parcellated based on the Desikan-Killiany-Tourville atlas. Relationships between pair-wise regional trajectories were calculated for each subject, defined as the theta angle of separation between the qT1 rates of change of any two brain regions between timepoints. Parcellations of brain regions were defined a priori, where hippocampal subfields and surrounding white matter formed one parcel, and cortical regions were assigned to 7 parcels based on known functional networks. Graph theory was used to calculate participation coefficient (PC), to measure the distribution of connections between the hippocampal parcel to IC and SWM of the 7 cortical parcels. Mean PC of the hippocampal module was compared between FEP and controls, then correlated to changes in negative symptoms and Logical Memory from the Weschler Memory Scale in FEP. The PC of the hippocampal parcel in relation to IC networks was significantly reduced in FEP compared to HC (F1,45=9.85, p=0.003), and nominally reduced in relation to SWM (F1,45=4.67, p=0.036). Post-hoc analyses of individual subregions were restricted to hippocampal-IC networks, where CA1 and alveus bilaterally, left molecular layer, fornix, mammillary body and right fimbria significantly contributed to reduced hippocampal PC (p<0.05). Lower PC of the hippocampal parcel was significantly associated with worsening negative symptoms (r=-0.58, p=0.0043) and nominally associated with worsening verbal memory (r=0.46, p=0.031). These associations were driven by left CA1, alveus, mammillary body, and right fimbria (p<0.05). This study provides evidence for reduced hippocampal centrality in FEP in relation to coordinated anatomical changes within intracortical microstructure, suggesting the hippocampus may be related to changes in cortico-cortical connectivity. Particularly, centrality of output structures of the hippocampus, situated as putative connector hubs, are significantly related to changes in factors that contribute to patient functional outcomes. The myelin-rich output regions of the hippocampus may serve as an important therapeutic target in early psychosis, with cascading effects on broader cortical networks and resultant clinical profiles.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
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.
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 ».