Cognitive profiles across the psychosis continuum.

Cognitive impairments are core features in individuals across the psychosis continuum and predict functional outcomes. Nevertheless, substantial variability in cognitive functioning within diagnostic groups, along with considerable overlap with healthy controls, hampers the translation of research findings into personalized treatment planning. Aligned with precision medicine, we employed a data driven machine learning method, self-organizing maps, to conduct transdiagnostic clustering based on cognitive functions in a sample comprising 228 healthy controls, 200 individuals at ultra-high risk for psychosis, and 98 antipsychotic-naïve patients with first-episode psychosis. The self-organizing maps revealed six clinically distinct cognitive profiles that significantly predicted baseline functional level and changes in functional level after one year. Cognitive flexibility in particular, as well as specific executive functions emerged as cardinal in differentiating the profiles. The application of self-organizing maps appears to be a promising approach to inform clinical decision-making based on individualized cognitive profiles, including patient allocation to different interventions. Moreover, this method has the potential to enable cross-diagnostic stratification in research trials, utilizing data-driven subgrouping informed by categories from underlying dimensions of cognition rather than from clinical diagnoses. Finally, the method enables cross-diagnostic profiling across other data modalities, such as brain networks or metabolic subtypes.

Structural and functional connectivity in relation to executive functions in antipsychotic-naïve patients with first episode schizophrenia and levels of glutamatergic metabolites.

Patients with schizophrenia exhibit structural and functional dysconnectivity but the relationship to the well-documented cognitive impairments is less clear. This study investigates associations between structural and functional connectivity and executive functions in antipsychotic-naïve patients experiencing schizophrenia. Sixty-four patients with schizophrenia and 95 matched controls underwent cognitive testing, diffusion weighted imaging and resting state functional magnetic resonance imaging. In the primary analyses, groupwise interactions between structural connectivity as measured by fixel-based analyses and executive functions were investigated using multivariate linear regression analyses. For significant structural connections, secondary analyses examined whether functional connectivity and associations with executive functions also differed for the two groups. In group comparisons, patients exhibited cognitive impairments across all executive functions compared to controls (p < 0.001), but no group difference were observed in the fixel-based measures. Primary analyses revealed a groupwise interaction between planning abilities and fixel-based measures in the left anterior thalamic radiation (p = 0.004), as well as interactions between cognitive flexibility and fixel-based measures in the isthmus of corpus callosum and cingulum (p = 0.049). Secondary analyses revealed increased functional connectivity between grey matter regions connected by the left anterior thalamic radiation (left thalamus with pars opercularis p = 0.018, and pars orbitalis p = 0.003) in patients compared to controls. Moreover, a groupwise interaction was observed between cognitive flexibility and functional connectivity between contralateral regions connected by the isthmus (precuneus p = 0.028, postcentral p = 0.012), all p-values corrected for multiple comparisons. We conclude that structural and functional connectivity appear to associate with executive functions differently in antipsychotic-naïve patients with schizophrenia compared to controls.

Using computer vision of facial expressions to assess symptom domains and treatment response in antipsychotic-naïve patients with first-episode psychosis.

BACKGROUND: Facial expressions are a core aspect of non-verbal communication. Reduced emotional expressiveness of the face is a common negative symptom of schizophrenia, however, quantifying negative symptoms can be clinically challenging and involves a considerable element of rater subjectivity. We used computer vision to investigate if (i) automated assessment of facial expressions captures negative as well as positive and general symptom domains, and (ii) if automated assessments are associated with treatment response in initially antipsychotic-naïve patients with first-episode psychosis. METHOD: We included 46 patients (mean age 25.4 (6.1); 65.2% males). Psychopathology was assessed at baseline and after 6 weeks of monotherapy with amisulpride using the Positive and Negative Syndrome Scale (PANSS). Baseline interview videos were recorded. Seventeen facial action units (AUs), that is, activation of muscles, from the Facial Action Coding System were extracted using OpenFace 2.0. A correlation matrix was calculated for each patient. Facial expressions were identified using spectral clustering at group-level. Associations between facial expressions and psychopathology were investigated using multiple linear regression. RESULTS: Three clusters of facial expressions were identified related to different locations of the face. Cluster 1 was associated with positive and general symptoms at baseline, Cluster 2 was associated with all symptom domains, showing the strongest association with the negative domain, and Cluster 3 was only associated with general symptoms. Cluster 1 was significantly associated with the clinically rated improvement in positive and general symptoms after treatment, and Cluster 2 was significantly associated with clinical improvement in all domains. CONCLUSION: Using automated computer vision of facial expressions during PANSS interviews did not only capture negative symptoms but also combinations of the three overall domains of psychopathology. Moreover, automated assessments of facial expressions at baseline were associated with initial antipsychotic treatment response. The findings underscore the clinical relevance of facial expressions and motivate further investigations of computer vision in clinical psychiatry.

Investigation of brain iron in anorexia nervosa, a quantitative susceptibility mapping study.

BACKGROUND: Anorexia nervosa (AN) is a potentially fatal psychiatric condition, associated with structural brain changes such as gray matter volume loss. The pathophysiological mechanisms for these changes are not yet fully understood. Iron is a crucial element in the development and function of the brain. Considering the systemic alterations in iron homeostasis in AN, we hypothesized that brain iron would be altered as a possible factor associated with structural brain changes in AN. METHODS: In this study, we used quantitative susceptibility mapping (QSM) magnetic resonance imaging to investigate brain iron in current AN (c-AN) and weight-restored AN compared with healthy individuals. Whole-brain voxel wise comparison was used to probe areas with possible group differences. Further, the thalamus, caudate nucleus, putamen, nucleus accumbens, hippocampus, and amygdala were selected as the regions of interest (ROIs) for ROI-based comparison of mean QSM values. RESULTS: Whole-brain voxel-wise and ROI-based comparison of QSM did not reveal any differences between groups. Exploratory analyses revealed a correlation between higher regional QSM (higher iron) and lower body mass index, higher illness severity, longer illness duration, and younger age at onset in the c-AN group. CONCLUSIONS: This study did not find evidence of altered brain iron in AN compared to healthy individuals. However, the correlations between clinical variables and QSM suggest a link between brain iron and weight status or biological processes in AN, which warrants further investigation.

Fibre density and fibre-bundle cross-section of the corticospinal tract are distinctly linked to psychosis-specific symptoms in antipsychotic-naïve patients with first-episode schizophrenia.

Multiple lines of research support the dysconnectivity hypothesis of schizophrenia. However, findings on white matter (WM) alterations in patients with schizophrenia are widespread and non-specific. Confounding factors from magnetic resonance image (MRI) processing, clinical diversity, antipsychotic exposure, and substance use may underlie some of the variability. By application of refined methodology and careful sampling, we rectified common confounders investigating WM and symptom correlates in a sample of strictly antipsychotic-naïve first-episode patients with schizophrenia. Eighty-six patients and 112 matched controls underwent diffusion MRI. Using fixel-based analysis (FBA), we extracted fibre-specific measures such as fibre density and fibre-bundle cross-section. Group differences on fixel-wise measures were examined with multivariate general linear modelling. Psychopathology was assessed with the Positive and Negative Syndrome Scale. We separately tested multivariate correlations between fixel-wise measures and predefined psychosis-specific versus anxio-depressive symptoms. Results were corrected for multiple comparisons. Patients displayed reduced fibre density in the body of corpus callosum and in the middle cerebellar peduncle. Fibre density and fibre-bundle cross-section of the corticospinal tract were positively correlated with suspiciousness/persecution, and negatively correlated with delusions. Fibre-bundle cross-section of isthmus of corpus callosum and hallucinatory behaviour were negatively correlated. Fibre density and fibre-bundle cross-section of genu and splenium of corpus callosum were negative correlated with anxio-depressive symptoms. FBA revealed fibre-specific properties of WM abnormalities in patients and differentiated associations between WM and psychosis-specific versus anxio-depressive symptoms. Our findings encourage an itemised approach to investigate the relationship between WM microstructure and clinical symptoms in patients with schizophrenia.

A Serendipitous Outcome of COVID-19: Modifications to ICU Management.

Nosocomial infections are common in intensive care units (ICUs) and often cause increased morbidity and mortality rates in ICU patients. With the emergence of the highly infectious COVID-19, the high prevalence of hospital-acquired infections (HAIs) in ICU has caused much more concern because patients admitted to the ICU have a more severe and prolonged form of the disease. These patients are more likely to develop HAIs than non-ICU patients. Medical communities adopted several measures to make ICU management safer during the pandemic all over the world. In this study, we re-examined the challenges faced and the changes made in ICU management during the pandemic to speculate how these changes will be relevant post-pandemic and can be permanently incorporated into the ICU to improve safety, management, and critical care and make critical care better equipped for future disease breakouts.

In Vivo 7-Tesla MRI Investigation of Brain Iron and Its Metabolic Correlates in Chronic Schizophrenia.

Brain iron is central to dopaminergic neurotransmission, a key component in schizophrenia pathology. Iron can also generate oxidative stress, which is one proposed mechanism for gray matter volume reduction in schizophrenia. The role of brain iron in schizophrenia and its potential link to oxidative stress has not been previously examined. In this study, we used 7-Tesla MRI quantitative susceptibility mapping (QSM), magnetic resonance spectroscopy (MRS), and structural T1 imaging in 12 individuals with chronic schizophrenia and 14 healthy age-matched controls. In schizophrenia, there were higher QSM values in bilateral putamen and higher concentrations of phosphocreatine and lactate in caudal anterior cingulate cortex (caCC). Network-based correlation analysis of QSM across corticostriatal pathways as well as the correlation between QSM, MRS, and volume, showed distinct patterns between groups. This study introduces increased iron in the putamen in schizophrenia in addition to network-wide disturbances of iron and metabolic status.

Affinity scores: An individual-centric fingerprinting framework for neuropsychiatric disorders.

Population-centric frameworks of biomarker identification for psychiatric disorders focus primarily on comparing averages between groups and assume that diagnostic groups are (1) mutually-exclusive, and (2) homogeneous. There is a paucity of individual-centric approaches capable of identifying individual-specific 'fingerprints' across multiple domains. To address this, we propose a novel framework, combining a range of biopsychosocial markers, including brain structure, cognition, and clinical markers, into higher-level 'fingerprints', capable of capturing intra-illness heterogeneity and inter-illness overlap. A multivariate framework was implemented to identify individualised patterns of brain structure, cognition and clinical markers based on affinity to other participants in the database. First, individual-level affinity scores defined each participant's "neighbourhood" across each measure based on variable-specific hop sizes. Next, diagnostic verification and classification algorithms were implemented based on multivariate affinity score profiles. To perform affinity-based classification, data were divided into training and test samples, and 5-fold nested cross-validation was performed on the training data. Affinity-based classification was compared to weighted K-nearest neighbours (KNN) classification. The framework was applied to the Australian Schizophrenia Research Bank (ASRB) dataset, which included data from individuals with chronic and treatment resistant schizophrenia and healthy controls. Individualised affinity scores provided a 'fingerprint' of brain structure, cognition, and clinical markers, which described the affinity of an individual to the representative groups in the dataset. Diagnostic verification capability was moderate to high depending on the choice of multivariate affinity metric. Affinity score-based classification achieved a high degree of accuracy in the training, nested cross-validation and prediction steps, and outperformed KNN classification in the training and test datasets. Affinity scores demonstrate utility in two keys ways: (1) Early and accurate diagnosis of neuropsychiatric disorders, whereby an individual can be grouped within a diagnostic category/ies that best matches their fingerprint, and (2) identification of biopsychosocial factors that most strongly characterise individuals/disorders, and which may be most amenable to intervention.

Long-term structural brain changes in adult rats after mild ischaemic stroke.

Preclinical studies of remote degeneration have largely focused on brain changes over the first few days or weeks after stroke. Accumulating evidence suggests that neurodegeneration occurs in other brain regions remote to the site of infarction for months and even years following ischaemic stroke. Brain atrophy appears to be driven by both axonal degeneration and widespread brain inflammation. The evolution and duration of these changes are increasingly being described in human studies, using advanced brain imaging techniques. Here, we sought to investigate long-term structural brain changes in a model of mild focal ischaemic stroke following injection of endothlin-1 in adult Long-Evans rats (n = 14) compared with sham animals (n = 10), over a clinically relevant time-frame of 48 weeks. Serial structural and diffusion-weighted MRI data were used to assess dynamic volume and white matter trajectories. We observed dynamic regional brain volume changes over the 48 weeks, reflecting both normal changes with age in sham animals and neurodegeneration in regions connected to the infarct following ischaemia. Ipsilesional cortical volume loss peaked at 24 weeks but was less prominent at 36 and 48 weeks. We found significantly reduced fractional anisotropy in both ipsi- and contralesional motor cortex and cingulum bundle regions of infarcted rats (P < 0.05) from 4 to 36 weeks, suggesting ongoing white matter degeneration in tracts connected to but distant from the stroke. We conclude that there is evidence of significant cortical atrophy and white matter degeneration up to 48 weeks following infarct, consistent with enduring, pervasive stroke-related degeneration.

Add-On MEmaNtine to Dopamine Antagonism to Improve Negative Symptoms at First Psychosis- the AMEND Trial Protocol.

Background: Antipsychotic drugs are primarily efficacious in treating positive symptoms by blocking the dopamine D2 receptor, but they fail to substantially improve negative symptoms and cognitive deficits. The limited efficacy may be attributed to the fact that the pathophysiology of psychosis involves multiple neurotransmitter systems. In patients with chronic schizophrenia, memantine, a non-competitive glutamatergic NMDA receptor antagonist, shows promise for ameliorating negative symptoms and improving cognition. Yet, it is unknown how memantine modulates glutamate levels, and memantine has not been investigated in patients with first-episode psychosis. Aims: This investigator-initiated double-blinded randomized controlled trial is designed to (1) test the clinical effects on negative symptoms of add-on memantine to antipsychotic medication, and (2) neurobiologically characterize the responders to add-on memantine. Materials and Equipment: Antipsychotic-naïve patients with first-episode psychosis will be randomized to 12 weeks treatment with [amisulpride + memantine] or [amisulpride + placebo]. We aim for a minimum of 18 patients in each treatment arm to complete the trial. Brain mapping will be performed before and after 12 weeks focusing on glutamate and neuromelanin in predefined regions. Regional glutamate levels will be probed with proton magnetic resonance spectroscopy (MRS), while neuromelanin signal will be mapped with neuromelanin-sensitive magnetic resonance imaging (MRI). We will also perform structural and diffusion weighted, whole-brain MRI. MRS and MRI will be performed at an ultra-high field strength (7 Tesla). Alongside, participants undergo clinical and neuropsychological assessments. Twenty matched healthy controls will undergo similar baseline- and 12-week examinations, but without receiving treatment. Outcome Measures: The primary endpoint is negative symptom severity. Secondary outcomes comprise: (i) clinical endpoints related to cognition, psychotic symptoms, side effects, and (ii) neurobiological endpoints related to regional glutamate- and neuromelanin levels, and structural brain changes. Anticipated Results: We hypothesize that add-on memantine to amisulpride will be superior to amisulpride monotherapy in reducing negative symptoms, and that this effect will correlate with thalamic glutamate levels. Moreover, we anticipate that add-on memantine will restore regional white matter integrity and improve cognitive functioning. Perspectives: By combining two licensed, off-patent drugs, AMEND aims to optimize treatment of psychosis while investigating the memantine response. Alongside, AMEND will provide neurobiological insights to effects of dual receptor modulation, which may enable future stratification of patients with first-episode psychosis before initial antipsychotic treatment. Clinical Trial Registration: [ClinicalTrials.gov], identifier [NCT04789915].

Cortico-cognition coupling in treatment resistant schizophrenia.

BACKGROUND: Brain structural alterations and cognitive dysfunction are independent predictors for poor clinical outcome in schizophrenia, and the associations between these domains remains unclear. We employed a novel, multiblock partial least squares correlation (MB-PLS-C) technique and investigated multivariate cortico-cognitive patterns in patients with treatment-resistant schizophrenia (TRS) and matched healthy controls (HC). METHOD: Forty-one TRS patients (age 38.5 ± 9.1, 30 males (M)), and 45 HC (age 40.2 ± 10.6, 29 M) underwent 3T structural MRI. Volumes of 68 brain regions and seven variables from CANTAB covering memory and executive domains were included. Univariate group differences were assessed, followed by the MB-PLS-C analyses to identify group-specific multivariate patterns of cortico-cognitive coupling. Supplementary three-group analyses, which included 23 non-affected first-degree relatives (NAR), were also conducted. RESULTS: Univariate tests demonstrated that TRS patients showed impairments in all seven cognitive tasks and volume reductions in 12 cortical regions following Bonferroni correction. The MB-PLS-C analyses revealed two significant latent variables (LVs) explaining > 90% of the sum-of-squares variance. LV1 explained 78.86% of the sum-of-squares variance, describing a shared, widespread structure-cognitive pattern relevant to both TRS patients and HCs. In contrast, LV2 (13.47% of sum-of-squares variance explained) appeared specific to TRS and comprised a differential cortico-cognitive pattern including frontal and temporal lobes as well as paired associates learning (PAL) and intra-extra dimensional set shifting (IED). Three-group analyses also identified two significant LVs, with NARs more closely resembling healthy controls than TRS patients. CONCLUSIONS: MB-PLS-C analyses identified multivariate brain structural-cognitive patterns in the latent space that may provide a TRS signature.

Prediction of Early Symptom Remission in Two Independent Samples of First-Episode Psychosis Patients Using Machine Learning.

BACKGROUND: Validated clinical prediction models of short-term remission in psychosis are lacking. Our aim was to develop a clinical prediction model aimed at predicting 4-6-week remission following a first episode of psychosis. METHOD: Baseline clinical data from the Athens First Episode Research Study was used to develop a Support Vector Machine prediction model of 4-week symptom remission in first-episode psychosis patients using repeated nested cross-validation. This model was further tested to predict 6-week remission in a sample of two independent, consecutive Danish first-episode cohorts. RESULTS: Of the 179 participants in Athens, 120 were male with an average age of 25.8 years and average duration of untreated psychosis of 32.8 weeks. 62.9% were antipsychotic-naïve. Fifty-seven percent attained remission after 4 weeks. In the Danish cohort, 31% attained remission. Eleven clinical scale items were selected in the Athens 4-week remission cohort. These included the Duration of Untreated Psychosis, Personal and Social Performance Scale, Global Assessment of Functioning and eight items from the Positive and Negative Syndrome Scale. This model significantly predicted 4-week remission status (area under the receiver operator characteristic curve (ROC-AUC) = 71.45, P < .0001). It also predicted 6-week remission status in the Danish cohort (ROC-AUC = 67.74, P < .0001), demonstrating reliability. CONCLUSIONS: Using items from common and validated clinical scales, our model significantly predicted early remission in patients with first-episode psychosis. Although replicated in an independent cohort, forward testing between machine learning models and clinicians' assessment should be undertaken to evaluate the possible utility as a routine clinical tool.

Disruptions in white matter microstructure associated with impaired visual associative memory in schizophrenia-spectrum illness.

Episodic memory ability relies on hippocampal-prefrontal connectivity. However, few studies have examined relationships between memory performance and white matter (WM) microstructure in hippocampal-prefrontal pathways in schizophrenia-spectrum disorder (SSDs). Here, we investigated these relationships in individuals with first-episode psychosis (FEP) and chronic schizophrenia-spectrum disorders (SSDs) using tractography analysis designed to interrogate the microstructure of WM tracts in the hippocampal-prefrontal pathway. Measures of WM microstructure (fractional anisotropy [FA], radial diffusivity [RD], and axial diffusivity [AD]) were obtained for 47 individuals with chronic SSDs, 28 FEP individuals, 52 older healthy controls, and 27 younger healthy controls. Tractography analysis was performed between the hippocampus and three targets involved in hippocampal-prefrontal connectivity (thalamus, amygdala, nucleus accumbens). Measures of WM microstructure were then examined in relation to episodic memory performance separately across each group. Both those with FEP and chronic SSDs demonstrated impaired episodic memory performance. However, abnormal WM microstructure was only observed in individuals with chronic SSDs. Abnormal WM microstructure in the hippocampal-thalamic pathway in the right hemisphere was associated with poorer memory performance in individuals with chronic SSDs. These findings suggest that disruptions in WM microstructure in the hippocampal-prefrontal pathway may contribute to memory impairments in individuals with chronic SSDs but not FEP.

Cognitive behavioral markers of neurodevelopmental trajectories in rodents.

Between adolescence and adulthood, the brain critically undergoes maturation and refinement of synaptic and neural circuits that shape cognitive processing. Adolescence also represents a vulnerable period for the onset of symptoms in neurodevelopmental psychiatric disorders. Despite the wide use of rodent models to unravel neurobiological mechanisms underlying neurodevelopmental disorders, there is a surprising paucity of rigorous studies focusing on normal cognitive-developmental trajectories in such models. Here, we sought to behaviorally capture maturational changes in cognitive trajectories during adolescence and into adulthood in male and female mice using distinct behavioral paradigms. C57 BL/6J mice (4.5, 6, and 12 weeks of age) were assessed on three behavioral paradigms: drug-induced locomotor hyperactivity, prepulse inhibition, and a novel validated version of a visuospatial paired-associate learning touchscreen task. We show that the normal maturational trajectories of behavioral performance on these paradigms are dissociable. Responses in drug-induced locomotor hyperactivity and prepulse inhibition both displayed a 'U-shaped' developmental trajectory; lower during mid-adolescence relative to early adolescence and adulthood. In contrast, visuospatial learning and memory, memory retention, and response times indicative of motivational processing progressively improved with age. Our study offers a framework to investigate how insults at different developmental stages might perturb normal trajectories in cognitive development. We provide a brain maturational approach to understand resilience factors of brain plasticity in the face of adversity and to examine pharmacological and non-pharmacological interventions directed at ameliorating or rescuing perturbed trajectories in neurodevelopmental and neuropsychiatric disorders.

Changes in negative symptoms are linked to white matter changes in superior longitudinal fasciculus in individuals at ultra-high risk for psychosis.

AIM: Growing evidence suggests that subtle white matter (WM) alterations are associated with psychopathology in individuals at ultra-high risk for psychosis (UHR). However, the longitudinal relationship between symptom progression and WM changes over time remains under-explored. Here, we examine associations between changes in clinical symptoms and changes in WM over six months in a large UHR-cohort. METHODS: 110 UHR-individuals and 59 healthy controls underwent diffusion weighted imaging at baseline and after six months. Group × time effects on fractional anisotropy (FA) were tested globally and in four predefined regions of interest (ROIs) bilaterally using linear modelling with repeated measures. Correlations between the changes in clinical symptoms and FA changes in the ROIs were examined with Pearson's correlation. A partial least squares correlation-technique (PLS-C) explored multivariate associations between patterns of changes in psychopathology, regional FA and additional WM indices. RESULTS: At baseline, UHR-individuals displayed significantly lower FA globally (p = 0.018; F = 12.274), in right superior longitudinal fasciculus (p = 0.02; Adj R2 = 0.07) and in left uncinate fasciculus (p = 0.048; Adj R2 = 0.058) compared to controls (corrected). We identified a group × time interaction in global FA and right superior longitudinal fasciculus, but the finding did not survive multiple comparisons. However, an increase of negative symptoms in UHR-individuals correlated with FA increase in right superior longitudinal fasciculus (p = 0.048, corrected, r = 0.357), and this finding was supported by the multivariate PLS-C. CONCLUSION: We found a positive correlation with a moderate effect between change in negative symptoms and FA change over 6 months in right superior longitudinal fasciculus. This link appeared mainly to reflect a subgroup of UHR-individuals, which already at baseline presented as vulnerable.

Global fractional anisotropy predicts transition to psychosis after 12 months in individuals at ultra-high risk for psychosis.

OBJECTIVE: Psychosis spectrum disorders are associated with cerebral changes, but the prognostic value and clinical utility of these findings are unclear. Here, we applied a multivariate statistical model to examine the predictive accuracy of global white matter fractional anisotropy (FA) for transition to psychosis in individuals at ultra-high risk for psychosis (UHR). METHODS: 110 UHR individuals underwent 3 Tesla diffusion-weighted imaging and clinical assessments at baseline, and after 6 and 12 months. Using logistic regression, we examined the reliability of global FA at baseline as a predictor for psychosis transition after 12 months. We tested the predictive accuracy, sensitivity and specificity of global FA in a multivariate prediction model accounting for potential confounders to FA (head motion in scanner, age, gender, antipsychotic medication, parental socioeconomic status and activity level). In secondary analyses, we tested FA as a predictor of clinical symptoms and functional level using multivariate linear regression. RESULTS: Ten UHR individuals had transitioned to psychosis after 12 months (9%). The model reliably predicted transition at 12 months (χ2  = 17.595, p = 0.040), accounted for 15-33% of the variance in transition outcome with a sensitivity of 0.70, a specificity of 0.88 and AUC of 0.87. Global FA predicted level of UHR symptoms (R2  = 0.055, F = 6.084, p = 0.016) and functional level (R2  = 0.040, F = 4.57, p = 0.036) at 6 months, but not at 12 months. CONCLUSION: Global FA provided prognostic information on clinical outcome and symptom course of UHR individuals. Our findings suggest that the application of prediction models including neuroimaging data can inform clinical management on risk for psychosis transition.

Longitudinal hippocampal volumetric changes in mice following brain infarction.

Hippocampal atrophy is increasingly described in many neurodegenerative syndromes in humans, including stroke and vascular cognitive impairment. However, the progression of brain volume changes after stroke in rodent models is poorly characterized. We aimed to monitor hippocampal atrophy occurring in mice up to 48-weeks post-stroke. Male C57BL/6J mice were subjected to an intraluminal filament-induced middle cerebral artery occlusion (MCAO). At baseline, 3-days, and 1-, 4-, 12-, 24-, 36- and 48-weeks post-surgery, we measured sensorimotor behavior and hippocampal volumes from T2-weighted MRI scans. Hippocampal volume-both ipsilateral and contralateral-increased over the life-span of sham-operated mice. In MCAO-subjected mice, different trajectories of ipsilateral hippocampal volume change were observed dependent on whether the hippocampus contained direct infarction, with a decrease in directly infarcted tissue and an increase in non-infarcted tissue. To further investigate these volume changes, neuronal and glial cell densities were assessed in histological brain sections from the subset of MCAO mice lacking hippocampal infarction. Our findings demonstrate previously uncharacterized changes in hippocampal volume and potentially brain parenchymal cell density up to 48-weeks in both sham- and MCAO-operated mice.