Observed differences in nutrition management at two time points spanning a decade in critically ill trauma patients with and without head injury.

BACKGROUND: Nutritional needs of trauma patients admitted to the intensive care unit may differ from general critically ill patients, but most current evidence is based on large clinical trials recruiting mixed populations. OBJECTIVE: The aim of the study was to investigate nutrition practices at two time points that span a decade in trauma patients with and without head injury. METHODS: This observational study recruited adult trauma patients receiving mechanical ventilation and artificial nutrition from a single-centre intensive care unit between February 2005 to December 2006 (cohort 1), and December 2018 to September 2020 (cohort 2). Patients were categorised into head injury and non-head injury subgroups. Data regarding energy and protein prescription and delivery were collected. Data are presented as median [interquartile range]. Wilcoxon rank-sum test assessed the differences between cohorts and subgroups, with a P value ≤ 0.05. The protocol was registered with the Australian and New Zealand Clinical Trials Registry (Trial ID: ACTRN12618001816246). RESULTS: Cohort 1 included 109 patients, and 112 patients were included in cohort 2 (age: 46 ± 19 vs 50 ± 19 y; 80 vs 79% M). Overall, nutrition practice did not differ between head-injured and non-head-injured subgroups (all P > 0.05). Energy prescription and delivery decreased from time point one to time point two, regardless of subgroup (Prescription: 9824 [8820-10 581] vs 8318 [7694-9071] kJ; Delivery: 6138 [5130-7188] vs 4715 [3059-5996] kJ; all P < 0.05). Protein prescription did not change from time point one to time point two. Although protein delivery remained constant from time point one to time point two in the head injury group, protein delivery reduced in the non-head injury subgroup (70 [56-82] vs 45 [26-64] g/d, P < 0.05). CONCLUSION: In this single-centre study, energy prescription and delivery in critically ill trauma patients reduced from time point one to time point two. Protein prescription did not change, but protein delivery reduced from time point one to time point two in non-head injury patients. Reasons for these differing trajectories require exploration. STUDY REGISTRATION: Trial registered at www.anzctr.org.au. TRIAL ID: ACTRN12618001816246.

Exercise Predicts a Good Night's Sleep: Preliminary Findings from a UCLA Study of First-Episode Schizophrenia.

BACKGROUND: Physical exercise can improve sleep quality in the general population. Understanding the negative impact of poor sleep quality on multiple domains of functioning among persons with schizophrenia is a new frontier of exploration. It is also imperative to investigate non-pharmacologic methods to improve sleep quality as these approaches may not carry the side effect burdens associated with medication. OBJECTIVE: We examined the relationship between regular physical exercise and sleep quality among participants in an intervention consisting of both cognitive training and exercise. METHODS: Participants (N = 48) were schizophrenia patients who had a first psychotic episode within two years of study entry. Participants received 4 h/week of internet-based cognitive training and an aerobic exercise program over a 6-month period. Sleep was assessed with the Pittsburgh Sleep Quality Index at baseline and six months later. RESULTS: During the 3 months prior to the 6-month follow-up sleep assessment, participants completed an average of 12.6 group exercise sessions and an average of 12.9 individual at-home exercise sessions. A significant relationship between the number of exercise sessions and global sleep quality was seen at month six, r = -0.44, df = 39, p < 0.01. Group exercise frequency was also associated with improvement in global sleep quality over the six-month intervention, t(34) = -2.84, p = 0.008. CONCLUSION: We demonstrated that a group of young adults with schizophrenia can be engaged in a regular exercise program, even during the tumultuous early course of the disorder. The number of exercise sessions in which they participated was associated with better sleep quality at six months and pre-postintervention improvement in sleep quality. KEY MESSAGE: Improved sleep quality appears to be a benefit of regular exercise among individuals with serious mental illness.

Treatment engagement in first-episode schizophrenia: Associations between intrinsic motivation and attendance during cognitive training and an aerobic exercise program.

Systematic cognitive training and aerobic exercise programs have emerged as promising interventions to improve cognitive deficits in first-episode schizophrenia, with successful outcomes closely linked with greater treatment engagement (e.g., higher attendance and homework completion rates). Unfortunately, treatment disengagement from these services remains a persistent issue. Intrinsic motivation, or the willingness to exert effort because a task is inherently interesting or meaningful, has emerged as a promising malleable personal factor to enhance treatment engagement. This study investigated whether early task-specific intrinsic motivation and its domains (e.g., interest, perceived competence, and value) predicted treatment engagement within the context of intensive cognitive training and aerobic exercise interventions over a 6-month period. Thirty-nine participants with first-episode schizophrenia were administered baseline measures of task-specific intrinsic motivation inventories, one for cognitive training and one for exercise, and completed a 6-month randomized clinical trial comparing a neuroplasticity-based cognitive training plus aerobic exercise program against the same cognitive training alone. Results indicated that higher baseline scores of intrinsic motivation for cognitive training, specifically early perceptions of task interest and value, were predictive of greater cognitive training and exercise group attendance. Scores for exercise-specific intrinsic motivation were generally unrelated to indices of exercise participation, with the exception that the gain over time in perceived choice for exercise was linked with greater exercise homework completion and a similar directional tendency for greater in-clinic exercise attendance. This study provides support for monitoring and enhancing motivation early during service delivery to maximize engagement and the likelihood of successful treatment outcomes.

Aerobic exercise enhances cognitive training effects in first-episode schizophrenia: randomized clinical trial demonstrates cognitive and functional gains.

BACKGROUND: Cognitive training (CT) and aerobic exercise both show promising moderate impact on cognition and everyday functioning in schizophrenia. Aerobic exercise is hypothesized to increase brain-derived neurotrophic factor (BDNF) and thereby synaptic plasticity, leading to increased learning capacity. Systematic CT should take advantage of increased learning capacity and be more effective when combined with aerobic exercise. METHODS: We examined the impact of a 6-month program of cognitive training & exercise (CT&E) compared to cognitive training alone (CT) in 47 first-episode schizophrenia outpatients. All participants were provided the same Posit Science computerized CT, 4 h/week, using BrainHQ and SocialVille programs. The CT&E group also participated in total body circuit training exercises to enhance aerobic conditioning. Clinic and home-based exercise were combined for a target of 150 min per week. RESULTS: The MATRICS Consensus Cognitive Battery Overall Composite improved significantly more with CT&E than with CT alone (p = 0.04), particularly in the first 3 months (6.5 v. 2.2 T-score points, p < 0.02). Work/school functioning improved substantially more with CT&E than with CT alone by 6 months (p < 0.001). BDNF gain tended to predict the amount of cognitive gain but did not reach significance. The cognitive gain by 3 months predicted the amount of work/school functioning improvement at 6 months. The amount of exercise completed was strongly associated with the degree of cognitive and work/school functioning improvement. CONCLUSIONS: Aerobic exercise significantly enhances the impact of CT on cognition and functional outcome in first-episode schizophrenia, apparently driven by the amount of exercise completed.

Multi-spatial-scale dynamic interactions between functional sources reveal sex-specific changes in schizophrenia.

We introduce an extension of independent component analysis (ICA), called multiscale ICA, and design an approach to capture dynamic functional source interactions within and between multiple spatial scales. Multiscale ICA estimates functional sources at multiple spatial scales without imposing direct constraints on the size of functional sources, overcomes the limitation of using fixed anatomical locations, and eliminates the need for model-order selection in ICA analysis. We leveraged this approach to study sex-specific and sex-common connectivity patterns in schizophrenia. Results show dynamic reconfiguration and interaction within and between multi-spatial scales. Sex-specific differences occur (a) within the subcortical domain, (b) between the somatomotor and cerebellum domains, and (c) between the temporal domain and several others, including the subcortical, visual, and default mode domains. Most of the sex-specific differences belong to between-spatial-scale functional interactions and are associated with a dynamic state with strong functional interactions between the visual, somatomotor, and temporal domains and their anticorrelation patterns with the rest of the brain. We observed significant correlations between multi-spatial-scale functional interactions and symptom scores, highlighting the importance of multiscale analyses to identify potential biomarkers for schizophrenia. As such, we recommend such analyses as an important option for future functional connectivity studies.

The Effects of Cardiorespiratory and Motor Skill Fitness on Intrinsic Functional Connectivity of Neural Networks in Individuals with Parkinson's Disease.

BACKGROUND: Studies in aging older adults have shown the positive association between cognition and exercise related fitness, particularly cardiorespiratory fitness. These reports have also demonstrated the association of high cardiorespiratory fitness, as well as other types of fitness, on the reversal of age-related decline in neural network connectivity, highlighting the potential role of fitness on age- and disease-related brain changes. While the clinical benefits of exercise are well-documented in Parkinson's disease (PD), the extent to which cardiorespiratory fitness (assessed by estimated VO2max testing) or motor skill fitness (assessed by the Physical Performance Test (PPT)) affects neural network connectivity in PD remains to be investigated. The purpose of this study was to explore the hypothesis that higher fitness level is associated with an increase in the intrinsic network connectivity of cognitive networks commonly affected in PD. METHODS: In this cross-sectional resting state fMRI, we used a multivariate statistical approach based on high-dimensional independent component analysis (ICA) to investigate the association between two independent fitness metrics (estimated VO2max and PPT) and resting state network connectivity. RESULTS: We found that increased estimated VO2max was associated with increased within network connectivity in cognitive networks known to be impaired in PD, including those sub-serving memory and executive function. There was a similar trend for high levels of PPT to be associated with increased within network connectivity in distinct resting state networks. The between functional network connectivity analysis revealed that cardiorespiratory fitness was associated with increased functional connectivity between somatosensory motor network and several cognitive networks sub-serving memory, attention, and executive function. CONCLUSION: This study provides important empirical data supporting the potential association between two forms of fitness and multiple resting state networks impacting PD cognition. Linking fitness to circuit specific modulation of resting state network connectivity will help establish a neural basis for the positive effects of fitness and specific exercise modalities and provide a foundation to identify underlying mechanisms to promote repair.

A systems-biology clinical trial of a personalized multimodal lifestyle intervention for early Alzheimer's disease.

INTRODUCTION: There is an urgent need to develop effective interventional treatments for people with Alzheimer's disease (AD). AD results from a complex multi-decade interplay of multiple interacting dysfunctional biological systems that have not yet been fully elucidated. Epidemiological studies have linked several modifiable lifestyle factors with increased incidence for AD. Because monotherapies have failed to prevent or ameliorate AD, interventional studies should deploy multiple, targeted interventions that address the dysfunctional systems that give rise to AD. METHODS: This randomized controlled trial (RCT) will examine the efficacy of a 12-month personalized, multimodal, lifestyle intervention in 60 mild cognitive impairment (MCI) and early stage AD patients (aged 50+, amyloid positivity). Both groups receive data-driven, lifestyle recommendations designed to target multiple systemic pathways implicated in AD. One group receives these personalized recommendations without coaching. The other group receives personalized recommendations with health coaching, dietary counseling, exercise training, cognitive stimulation, and nutritional supplements. We collect clinical, proteomic, metabolomic, neuroimaging, and genetic data to fuel systems-biology analyses. We will examine effects on cognition and hippocampal volume. The overarching goal of the study is to longitudinally track biological systems implicated in AD to reveal the dynamics between these systems during the intervention to understand differences in treatment response. RESULTS: We have developed and implemented a protocol for a personalized, multimodal intervention program for early AD patients. We began enrollment in September 2019; we have enrolled a third of our target (20 of 60) with a 95% retention and 86% compliance rate. DISCUSSION: This study presents a paradigm shift in designing multimodal, lifestyle interventions to reduce cognitive decline, and how to elucidate the biological systems being targeted. Analytical efforts to explain mechanistic or causal underpinnings of individual trajectories and the interplay between multi-omic variables will inform the design of future hypotheses and development of effective precision medicine trials.

Brain Density Clustering Analysis: A New Approach to Brain Functional Dynamics.

BACKGROUND: A number of studies in recent years have explored whole-brain dynamic connectivity using pairwise approaches. There has been less focus on trying to analyze brain dynamics in higher dimensions over time. METHODS: We introduce a new approach that analyzes time series trajectories to identify high traffic nodes in a high dimensional space. First, functional magnetic resonance imaging (fMRI) data are decomposed using spatial ICA to a set of maps and their associated time series. Next, density is calculated for each time point and high-density points are clustered to identify a small set of high traffic nodes. We validated our method using simulations and then implemented it on a real data set. RESULTS: We present a novel approach that captures dynamics within a high dimensional space and also does not use any windowing in contrast to many existing approaches. The approach enables one to characterize and study the time series in a potentially high dimensional space, rather than looking at each component pair separately. Our results show that schizophrenia patients have a lower dynamism compared to healthy controls. In addition, we find patients spend more time in nodes associated with the default mode network and less time in components strongly correlated with auditory and sensorimotor regions. Interestingly, we also found that subjects oscillate between state pairs that show opposite spatial maps, suggesting an oscillatory pattern. CONCLUSION: Our proposed method provides a novel approach to analyze the data in its native high dimensional space and can possibly provide new information that is undetectable using other methods.

Thalamic volume mediates associations between cardiorespiratory fitness (VO2max) and cognition in Parkinson's disease.

INTRODUCTION: Cognitive deficits occur in Parkinson's disease (PD). Cardiorespiratory fitness (CRF) is associated with better cognitive performance in aging especially in executive function (EF) and memory. The association between CRF and cognitive performance is understudied in people with PD. Brain structures underlying associations also remains unknown. This cross-sectional study examined the associations between CRF and cognitive performance in PD. We also examined associations between CRF and brain structures impacted in PD. Mediation analysis were conducted to examine whether brain structures impacted in PD mediate putative associations between CRF and cognitive performance. METHODS: Individuals with PD (N = 33) underwent magnetic resonance imaging (MRI), CRF evaluation (estimated VO2max), and neuropsychological assessment. Composite cognitive scores of episodic memory, EF, attention, language, and visuospatial functioning were generated. Structural equation models were constructed to examine whether MRI volume estimates (thalamus and pallidum) mediated associations between CRF and cognitive performance (adjusting for age, education, PD disease duration, sex, MDS-UPDRS motor score, and total intracranial volume). RESULTS: Higher CRF was associated with better episodic memory (Standardized ß = 0.391; p = 0.008), EF (Standardized ß = 0.324; p = 0.025), and visuospatial performance (Standardized ß = 0.570; p = 0.005). Higher CRF was associated with larger thalamic (Standardized ß = 0.722; p = 0.004) and pallidum (Standardized ß = 0.635; p = 0.004) volumes. Thalamic volume mediated the association between higher CRF and better EF (Indirect effect = 0.309) and episodic memory (Indirect effect = 0.209) performance (p < 0.05). The pallidum did not significantly mediate associations between CRF and cognitive outcomes. CONCLUSION: The thalamus plays an important role in the association between CRF and both EF and episodic memory in PD.

Changes in inflammation are related to depression and amount of aerobic exercise in first episode schizophrenia.

INTRODUCTION: Elevated levels of pro-inflammatory cytokines have been reported in meta-analyses of multi-episode schizophrenia patients when compared to controls. However, little is known about whether these same relationships are present in the early course of schizophrenia. OBJECTIVE: To assess first episode schizophrenia patients for depression and to assay blood samples collected at baseline and at 6 months for interleukin-6 (IL-6). MATERIALS AND METHODS: Trained raters used the Brief Psychiatric Rating Scale to assess depressive symptoms and a standard lab assay kit to assess for IL-6 levels in plasma. CONCLUSIONS: Decreases in pro-inflammatory IL-6 levels were significantly related to decreases in depressive symptoms. Within a subset of patients in a 6-month aerobic exercise protocol, the number of exercise sessions completed was significantly correlated with the amount of decrease in IL-6. The reductions observed in IL-6 with aerobic exercise suggest exercise is a promising intervention to reduce brain inflammation effects in schizophrenia patients.

Cross-paradigm connectivity: reliability, stability, and utility.

While functional neuroimaging studies typically focus on a particular paradigm to investigate network connectivity, the human brain appears to possess an intrinsic "trait" architecture that is independent of any given paradigm. We have previously proposed the use of "cross-paradigm connectivity (CPC)" to quantify shared connectivity patterns across multiple paradigms and have demonstrated the utility of such measures in clinical studies. Here, using generalizability theory and connectome fingerprinting, we examined the reliability, stability, and individual identifiability of CPC in a group of highly-sampled healthy traveling subjects who received fMRI scans with a battery of five paradigms across multiple sites and days. Compared with single-paradigm connectivity matrices, the CPC matrices showed higher reliability in connectivity diversity, lower reliability in connectivity strength, higher stability, and higher individual identification accuracy. All of these assessments increased as a function of number of paradigms included in the CPC analysis. In comparisons involving different paradigm combinations and different brain atlases, we observed significantly higher reliability, stability, and identifiability for CPC matrices constructed from task-only data (versus those from both task and rest data), and higher identifiability but lower stability for CPC matrices constructed from the Power atlas (versus those from the AAL atlas). Moreover, we showed that multi-paradigm CPC matrices likely reflect the brain's "trait" structure that cannot be fully achieved from single-paradigm data, even with multiple runs. The present results provide evidence for the feasibility and utility of CPC in the study of functional "trait" networks and offer some methodological implications for future CPC studies.

Covarying structural alterations in laterality of the temporal lobe in schizophrenia: A case for source-based laterality.

The human brain is asymmetrically lateralized for certain functions (such as language processing) to regions in one hemisphere relative to the other. Asymmetries are measured with a laterality index (LI). However, traditional LI measures are limited by a lack of consensus on metrics used for its calculation. To address this limitation, source-based laterality (SBL) leverages an independent component analysis for the identification of laterality-specific alterations, identifying covarying components between hemispheres across subjects. SBL is successfully implemented with simulated data with inherent differences in laterality. SBL is then compared with a voxel-wise analysis utilizing structural data from a sample of patients with schizophrenia and controls without schizophrenia. SBL group comparisons identified three distinct temporal regions and one cerebellar region with significantly altered laterality in patients with schizophrenia relative to controls. Previous work highlights reductions in laterality (ie, reduced left gray matter volume) in patients with schizophrenia compared with controls without schizophrenia. Results from this pilot SBL project are the first, to our knowledge, to identify covarying laterality differences within discrete temporal brain regions. The authors argue SBL provides a unique focus to detect covarying laterality differences in patients with schizophrenia, facilitating the discovery of laterality aspects undetected in previous work.

Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia.

OBJECTIVE: Multimodal measurements of the same phenomena provide complementary information and highlight different perspectives, albeit each with their own limitations. A focus on a single modality may lead to incorrect inferences, which is especially important when a studied phenomenon is a disease. In this paper, we introduce a method that takes advantage of multimodal data in addressing the hypotheses of disconnectivity and dysfunction within schizophrenia (SZ). METHODS: We start with estimating and visualizing links within and among extracted multimodal data features using a Gaussian graphical model (GGM). We then propose a modularity-based method that can be applied to the GGM to identify links that are associated with mental illness across a multimodal data set. Through simulation and real data, we show our approach reveals important information about disease-related network disruptions that are missed with a focus on a single modality. We use functional MRI (fMRI), diffusion MRI (dMRI), and structural MRI (sMRI) to compute the fractional amplitude of low frequency fluctuations (fALFF), fractional anisotropy (FA), and gray matter (GM) concentration maps. These three modalities are analyzed using our modularity method. RESULTS: Our results show missing links that are only captured by the cross-modal information that may play an important role in disconnectivity between the components. CONCLUSION: We identified multimodal (fALFF, FA and GM) disconnectivity in the default mode network area in patients with SZ, which would not have been detectable in a single modality. SIGNIFICANCE: The proposed approach provides an important new tool for capturing information that is distributed among multiple imaging modalities.

Weighted average of shared trajectory: A new estimator for dynamic functional connectivity efficiently estimates both rapid and slow changes over time.

BACKGROUND: Dynamic functional network connectivity (dFNC) of the brain has attracted considerable attention recently. Many approaches have been suggested to study dFNC with sliding window Pearson correlation (SWPC) being the most well-known. SWPC needs a relatively large sample size to reach a robust estimation but using large window sizes prevents us to detect rapid changes in dFNC. NEW METHOD: Here we first calculate the gradients of each time series pair and use the magnitude of these gradients to calculate weighted average of shared trajectory (WAST) as a new estimator for dFNC. RESULTS: Using WAST to compare healthy control and schizophrenia patients using a large dataset, we show disconnectivity between different regions associated with schizophrenia. In addition, WAST results reveals patients with schizophrenia stay longer in a connectivity state with negative connectivity between motor and sensory regions than do healthy controls. COMPARISON WITH EXISTING METHODS: We compare WAST with SWPC and multiplication of temporal derivatives (MTD) using different simulation scenarios. We show that WAST enables us to detect very rapid changes in dFNC (undetected by SWPC) while MTD performance is generally lower. CONCLUSIONS: As large window sizes are unable to detect short states, using shorter window size is desirable if the estimator is robust enough. We provide evidence that WAST requires fewer samples (compared to SWPC) to reach a robust estimation. As a result, we were able to identify rapidly varying dFNC patterns undetected by SWPC while still being able to robustly estimate slower dFNC patterns.

Mild cognitive impairment, psychiatric symptoms, and executive functioning in patients with Parkinson's disease.

OBJECTIVE: Mild cognitive impairment (MCI) and psychiatric symptoms (anxiety, depression, and apathy) are common in Parkinson's disease (PD). While studies have supported the association between psychiatric symptoms and cognitive performance in PD, it is unclear if the magnitude of link between psychiatric symptoms and cognitive health is stronger by MCI status. The purpose of this study was to examine the association between cognitive performance and psychiatric symptoms in PD and whether MCI status moderates this association. METHODS/DESIGN: Participants (N = 187) completed a comprehensive neuropsychological assessment that included measures of attention, language, executive function (EF), visuospatial ability, episodic memory, and psychiatric symptoms. Participants were classified as PD-MCI (N = 73) or PD-normal cognition (NC; N = 114). Linear regression analyses were conducted to examine the association between psychiatric symptoms and cognitive performance and the moderating effect of PD-MCI status. RESULTS: There were no differences in mean psychiatric symptoms between PD-MCI and PD-NC. Psychiatric symptoms were predominantly associated with worse EF. The magnitude of the association between anxiety and worse EF was larger in participants with PD-MCI compared with PD-NC. A multivariable regression analysis examining the independent contributions of each symptom demonstrated the most robust association between EF and anxiety. CONCLUSIONS: Symptoms of anxiety, depression, and apathy are associated with worse executive functioning in individuals with PD. PD-MCI may be important in moderating the association between cognitive performance, specifically anxiety, and EF. Factors that promote cognitive resilience may serve as key therapeutic modalities in managing neuropsychiatric symptoms in PD.

Progressive reconfiguration of resting-state brain networks as psychosis develops: Preliminary results from the North American Prodrome Longitudinal Study (NAPLS) consortium.

Mounting evidence has shown disrupted brain network architecture across the psychosis spectrum. However, whether these changes relate to the development of psychosis is unclear. Here, we used graph theoretical analysis to investigate longitudinal changes in resting-state brain networks in samples of 72 subjects at clinical high risk (including 8 cases who converted to full psychosis) and 48 healthy controls drawn from the North American Prodrome Longitudinal Study (NAPLS) consortium. We observed progressive reduction in global efficiency (P = 0.006) and increase in network diversity (P = 0.001) in converters compared with non-converters and controls. More refined analysis separating nodes into nine key brain networks demonstrated that these alterations were primarily driven by progressively diminished local efficiency in the default-mode network (P = 0.004) and progressively enhanced node diversity across all networks (P < 0.05). The change rates of network efficiency and network diversity were significantly correlated (P = 0.003), suggesting these changes may reflect shared neural mechanisms. In addition, change rates of global efficiency and node diversity were significantly correlated with change rate of cortical thinning in the prefrontal cortex in converters (P < 0.03) and could be predicted by visuospatial memory scores at baseline (P < 0.04). These results provide preliminary evidence for longitudinal reconfiguration of resting-state brain networks during psychosis development and suggest that decreased network efficiency, reflecting an increase in path length between nodes, and increased network diversity, reflecting a decrease in the consistency of functional network organization, may be implicated in the progression to full psychosis.

Dentate gyrus volume deficit in schizophrenia.

BACKGROUND: Schizophrenia is associated with robust hippocampal volume deficits but subregion volume deficits, their associations with cognition, and contributing genes remain to be determined. METHODS: Hippocampal formation (HF) subregion volumes were obtained using FreeSurfer 6.0 from individuals with schizophrenia (n = 176, mean age ± s.d. = 39.0 ± 11.5, 132 males) and healthy volunteers (n = 173, mean age ± s.d. = 37.6 ± 11.3, 123 males) with similar mean age, gender, handedness, and race distributions. Relationships between the HF subregion volume with the largest between group difference, neuropsychological performance, and single-nucleotide polymorphisms were assessed. RESULTS: This study found a significant group by region interaction on hippocampal subregion volumes. Compared to healthy volunteers, individuals with schizophrenia had significantly smaller dentate gyrus (DG) (Cohen's d = -0.57), Cornu Ammonis (CA) 4, molecular layer of the hippocampus, hippocampal tail, and CA 1 volumes, when statistically controlling for intracranial volume; DG (d = -0.43) and CA 4 volumes remained significantly smaller when statistically controlling for mean hippocampal volume. DG volume showed the largest between group difference and significant positive associations with visual memory and speed of processing in the overall sample. Genome-wide association analysis with DG volume as the quantitative phenotype identified rs56055643 (ß = 10.8, p < 5 × 10-8, 95% CI 7.0-14.5) on chromosome 3 in high linkage disequilibrium with MOBP. Gene-based analyses identified associations between SLC25A38 and RPSA and DG volume. CONCLUSIONS: This study suggests that DG dysfunction is fundamentally involved in schizophrenia pathophysiology, that it may contribute to cognitive abnormalities in schizophrenia, and that underlying biological mechanisms may involve contributions from MOBP, SLC25A38, and RPSA.

Altered Domain Functional Network Connectivity Strength and Randomness in Schizophrenia.

Functional connectivity is one of the most widely used tools for investigating brain changes due to schizophrenia. Previous studies have identified abnormal functional connectivity in schizophrenia patients at the resting state brain network level. This study tests the existence of functional connectivity effects at whole brain and domain levels. Domain level refers to the integration of data from several brain networks grouped by their functional relationship. Data integration provides more consistent and accurate information compared to an individual brain network. This work considers two domain level measures: functional connectivity strength and randomness. The first measure is simply an average of connectivities within the domain. The second measure assesses the unpredictability and lack of pattern of functional connectivity within the domain. Domains with less random connectivity have higher chance of exhibiting a biologically meaningful connectivity pattern. Consistent with prior observations, individuals with schizophrenia showed aberrant domain connectivity strength between subcortical, cerebellar, and sensorial brain areas. Compared to healthy volunteers, functional connectivity between cognitive and default mode domains showed less randomness, while connectivity between default mode-sensorial areas showed more randomness in schizophrenia patients. These differences in connectivity patterns suggest deleterious rewiring trade-offs among important brain networks.

Characterizing Whole Brain Temporal Variation of Functional Connectivity via Zero and First Order Derivatives of Sliding Window Correlations.

Brain functional connectivity has been shown to change over time during resting state fMRI experiments. Close examination of temporal changes have revealed a small set of whole-brain connectivity patterns called dynamic states. Dynamic functional network connectivity (dFNC) studies have demonstrated that it is possible to replicate the dynamic states across several resting state experiments. However, estimation of states and their temporal dynamicity still suffers from noisy and imperfect estimations. In regular dFNC implementations, states are estimated by comparing connectivity patterns through the data without considering time, in other words only zero order changes are examined. In this work we propose a method that includes first order variations of dFNC in the searching scheme of dynamic connectivity patterns. Our approach, referred to as temporal variation of functional network connectivity (tvFNC), estimates the derivative of dFNC, and then searches for reoccurring patterns of concurrent dFNC states and their derivatives. The tvFNC method is first validated using a simulated dataset and then applied to a resting-state fMRI sample including healthy controls (HC) and schizophrenia (SZ) patients and compared to the standard dFNC approach. Our dynamic approach reveals extra patterns in the connectivity derivatives complementing the already reported state patterns. State derivatives consist of additional information about increment and decrement of connectivity among brain networks not observed by the original dFNC method. The tvFNC shows more sensitivity than regular dFNC by uncovering additional FNC differences between the HC and SZ groups in each state. In summary, the tvFNC method provides a new and enhanced approach to examine time-varying functional connectivity.

Cortical abnormalities in youth at clinical high-risk for psychosis: Findings from the NAPLS2 cohort.

In a recent machine learning study classifying "brain age" based on cross-sectional neuroanatomical data, clinical high-risk (CHR) individuals were observed to show deviation from the normal neuromaturational pattern, which in turn was predictive of greater risk of conversion to psychosis and a pattern of stably poor functional outcome. These effects were unique to cases who were between 12 and 17 years of age when their prodromal and psychotic symptoms began, suggesting that neuroanatomical deviance observable at the point of ascertainment of a CHR syndrome marks risk for an early onset form of psychosis. In the present study, we sought to clarify the pattern of neuroanatomical deviance linked to this "early onset" form of psychosis and whether this deviance is associated with poorer premorbid functioning. T1 MRI scans from 378 CHR individuals and 190 healthy controls (HC) from the North American Prodrome Longitudinal Study (NAPLS2) were analyzed. Widespread smaller cortical volume was observed among CHR individuals compared with HC at baseline evaluation, particularly among the younger group (i.e., those who were 12 to 17 years of age). Moreover, the younger CHR individuals who converted or presented worsened clinical symptoms at follow-up (within 2 years) exhibited smaller surface area in rostral anterior cingulate, lateral and medial prefrontal regions, and parahippocampal gyrus relative to the younger CHR individuals who remitted or presented a stable pattern of prodromal symptoms at follow-up. In turn, poorer premorbid functioning in childhood was associated with smaller surface area in medial orbitofrontal, lateral frontal, rostral anterior cingulate, precuneus, and temporal regions. Together with our prior report, these results are consistent with the view that neuroanatomical deviance manifesting in early adolescence marks vulnerability to a form of psychosis presenting with poor premorbid adjustment, an earlier age of onset (generally prior to the age of 18 years), and poor long-term outcome.