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.

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.

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.

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.

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.

Toward Leveraging Human Connectomic Data in Large Consortia: Generalizability of fMRI-Based Brain Graphs Across Sites, Sessions, and Paradigms.

While graph theoretical modeling has dramatically advanced our understanding of complex brain systems, the feasibility of aggregating connectomic data in large imaging consortia remains unclear. Here, using a battery of cognitive, emotional and resting fMRI paradigms, we investigated the generalizability of functional connectomic measures across sites and sessions. Our results revealed overall fair to excellent reliability for a majority of measures during both rest and tasks, in particular for those quantifying connectivity strength, network segregation and network integration. Processing schemes such as node definition and global signal regression (GSR) significantly affected resulting reliability, with higher reliability detected for the Power atlas (vs. AAL atlas) and data without GSR. While network diagnostics for default-mode and sensori-motor systems were consistently reliable independently of paradigm, those for higher-order cognitive systems were reliable predominantly when challenged by task. In addition, based on our present sample and after accounting for observed reliability, satisfactory statistical power can be achieved in multisite research with sample size of approximately 250 when the effect size is moderate or larger. Our findings provide empirical evidence for the generalizability of brain functional graphs in large consortia, and encourage the aggregation of connectomic measures using multisite and multisession data.

A framework for linking resting-state chronnectome/genome features in schizophrenia: A pilot study.

Multimodal, imaging-genomics techniques offer a platform for understanding genetic influences on brain abnormalities in psychiatric disorders. Such approaches utilize the information available from both imaging and genomics data and identify their association. Particularly for complex disorders such as schizophrenia, the relationship between imaging and genomic features may be better understood by incorporating additional information provided by advanced multimodal modeling. In this study, we propose a novel framework to combine features corresponding to functional magnetic resonance imaging (functional) and single nucleotide polymorphism (SNP) data from 61 schizophrenia (SZ) patients and 87 healthy controls (HC). In particular, the features for the functional and genetic modalities include dynamic (i.e., time-varying) functional network connectivity (dFNC) features and the SNP data, respectively. The dFNC features are estimated from component time-courses, obtained using group independent component analysis (ICA), by computing sliding-window functional network connectivity, and then estimating subject specific states from this dFNC data using a k-means clustering approach. For each subject, both the functional (dFNC states) and SNP data are selected as features for a parallel ICA (pICA) based imaging-genomic framework. This analysis identified a significant association between a SNP component (defined by large clusters of functionally related SNPs statistically correlated with phenotype components) and time-varying or dFNC component (defined by clusters of related connectivity links among distant brain regions distributed across discrete dynamic states, and statistically correlated with genomic components) in schizophrenia. Importantly, the polygenetic risk score (PRS) for SZ (computed as a linearly weighted sum of the genotype profiles with weights derived from the odds ratios of the psychiatric genomics consortium (PGC)) was negatively correlated with the significant dFNC component, which were mostly present within a state that exhibited a lower occupancy rate in individuals with SZ compared with HC, hence identifying a potential dFNC imaging biomarker for schizophrenia. Taken together, the current findings provide preliminary evidence for a link between dFNC measures and genetic risk, suggesting the application of dFNC patterns as biomarkers in imaging genetic association study.

The spatial chronnectome reveals a dynamic interplay between functional segregation and integration.

The brain is highly dynamic, reorganizing its activity at different interacting spatial and temporal scales, including variation within and between brain networks. The chronnectome is a model of the brain in which nodal activity and connectivity patterns change in fundamental and recurring ways over time. Most literature assumes fixed spatial nodes/networks, ignoring the possibility that spatial nodes/networks may vary in time. Here, we introduce an approach to calculate a spatially fluid chronnectome (called the spatial chronnectome for clarity), which focuses on the variations of networks coupling at the voxel level, and identify a novel set of spatially dynamic features. Results reveal transient spatially fluid interactions between intra- and internetwork relationships in which brain networks transiently merge and separate, emphasizing dynamic segregation and integration. Brain networks also exhibit distinct spatial patterns with unique temporal characteristics, potentially explaining a broad spectrum of inconsistencies in previous studies that assumed static networks. Moreover, we show anticorrelative connections to brain networks are transient as opposed to constant across the entire scan. Preliminary assessments using a multi-site dataset reveal the ability of the approach to obtain new information and nuanced alterations that remain undetected during static analysis. Patients with schizophrenia (SZ) display transient decreases in voxel-wise network coupling within visual and auditory networks, and higher intradomain coupling variability. In summary, the spatial chronnectome represents a new direction of research enabling the study of functional networks which are transient at the voxel level, and the identification of mechanisms for within- and between-subject spatial variability.

Parallel group ICA+ICA: Joint estimation of linked functional network variability and structural covariation with application to schizophrenia.

There is growing evidence that rather than using a single brain imaging modality to study its association with physiological or symptomatic features, the field is paying more attention to fusion of multimodal information. However, most current multimodal fusion approaches that incorporate functional magnetic resonance imaging (fMRI) are restricted to second-level 3D features, rather than the original 4D fMRI data. This trade-off is that the valuable temporal information is not utilized during the fusion step. Here we are motivated to propose a novel approach called "parallel group ICA+ICA" that incorporates temporal fMRI information from group independent component analysis (GICA) into a parallel independent component analysis (ICA) framework, aiming to enable direct fusion of first-level fMRI features with other modalities (e.g., structural MRI), which thus can detect linked functional network variability and structural covariations. Simulation results show that the proposed method yields accurate intermodality linkage detection regardless of whether it is strong or weak. When applied to real data, we identified one pair of significantly associated fMRI-sMRI components that show group difference between schizophrenia and controls in both modalities, and this linkage can be replicated in an independent cohort. Finally, multiple cognitive domain scores can be predicted by the features identified in the linked component pair by our proposed method. We also show these multimodal brain features can predict multiple cognitive scores in an independent cohort. Overall, results demonstrate the ability of parallel GICA+ICA to estimate joint information from 4D and 3D data without discarding much of the available information up front, and the potential for using this approach to identify imaging biomarkers to study brain disorders.

Spatial dynamics within and between brain functional domains: A hierarchical approach to study time-varying brain function.

The analysis of time-varying activity and connectivity patterns (i.e., the chronnectome) using resting-state magnetic resonance imaging has become an important part of ongoing neuroscience discussions. The majority of previous work has focused on variations of temporal coupling among fixed spatial nodes or transition of the dominant activity/connectivity pattern over time. Here, we introduce an approach to capture spatial dynamics within functional domains (FDs), as well as temporal dynamics within and between FDs. The approach models the brain as a hierarchical functional architecture with different levels of granularity, where lower levels have higher functional homogeneity and less dynamic behavior and higher levels have less homogeneity and more dynamic behavior. First, a high-order spatial independent component analysis is used to approximate functional units. A functional unit is a pattern of regions with very similar functional activity over time. Next, functional units are used to construct FDs. Finally, functional modules (FMs) are calculated from FDs, providing an overall view of brain dynamics. Results highlight the spatial fluidity within FDs, including a broad spectrum of changes in regional associations, from strong coupling to complete decoupling. Moreover, FMs capture the dynamic interplay between FDs. Patients with schizophrenia show transient reductions in functional activity and state connectivity across several FDs, particularly the subcortical domain. Activity and connectivity differences convey unique information in many cases (e.g., the default mode) highlighting their complementarity information. The proposed hierarchical model to capture FD spatiotemporal variations provides new insight into the macroscale chronnectome and identifies changes hidden from existing approaches.

Multisite reliability of MR-based functional connectivity.

Recent years have witnessed an increasing number of multisite MRI functional connectivity (fcMRI) studies. While multisite studies provide an efficient way to accelerate data collection and increase sample sizes, especially for rare clinical populations, any effects of site or MRI scanner could ultimately limit power and weaken results. Little data exists on the stability of functional connectivity measurements across sites and sessions. In this study, we assess the influence of site and session on resting state functional connectivity measurements in a healthy cohort of traveling subjects (8 subjects scanned twice at each of 8 sites) scanned as part of the North American Prodrome Longitudinal Study (NAPLS). Reliability was investigated in three types of connectivity analyses: (1) seed-based connectivity with posterior cingulate cortex (PCC), right motor cortex (RMC), and left thalamus (LT) as seeds; (2) the intrinsic connectivity distribution (ICD), a voxel-wise connectivity measure; and (3) matrix connectivity, a whole-brain, atlas-based approach to assessing connectivity between nodes. Contributions to variability in connectivity due to subject, site, and day-of-scan were quantified and used to assess between-session (test-retest) reliability in accordance with Generalizability Theory. Overall, no major site, scanner manufacturer, or day-of-scan effects were found for the univariate connectivity analyses; instead, subject effects dominated relative to the other measured factors. However, summaries of voxel-wise connectivity were found to be sensitive to site and scanner manufacturer effects. For all connectivity measures, although subject variance was three times the site variance, the residual represented 60-80% of the variance, indicating that connectivity differed greatly from scan to scan independent of any of the measured factors (i.e., subject, site, and day-of-scan). Thus, for a single 5min scan, reliability across connectivity measures was poor (ICC=0.07-0.17), but increased with increasing scan duration (ICC=0.21-0.36 at 25min). The limited effects of site and scanner manufacturer support the use of multisite studies, such as NAPLS, as a viable means of collecting data on rare populations and increasing power in univariate functional connectivity studies. However, the results indicate that aggregation of fcMRI data across longer scan durations is necessary to increase the reliability of connectivity estimates at the single-subject level.

The Function Biomedical Informatics Research Network Data Repository.

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical data sets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 data set consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 T scanners. The FBIRN Phase 2 and Phase 3 data sets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN's multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data.

Reliability of an fMRI paradigm for emotional processing in a multisite longitudinal study.

Multisite neuroimaging studies can facilitate the investigation of brain-related changes in many contexts, including patient groups that are relatively rare in the general population. Though multisite studies have characterized the reliability of brain activation during working memory and motor functional magnetic resonance imaging tasks, emotion processing tasks, pertinent to many clinical populations, remain less explored. A traveling participants study was conducted with eight healthy volunteers scanned twice on consecutive days at each of the eight North American Longitudinal Prodrome Study sites. Tests derived from generalizability theory showed excellent reliability in the amygdala ( Eρ2 = 0.82), inferior frontal gyrus (IFG; Eρ2 = 0.83), anterior cingulate cortex (ACC; Eρ2 = 0.76), insula ( Eρ2 = 0.85), and fusiform gyrus ( Eρ2 = 0.91) for maximum activation and fair to excellent reliability in the amygdala ( Eρ2 = 0.44), IFG ( Eρ2 = 0.48), ACC ( Eρ2 = 0.55), insula ( Eρ2 = 0.42), and fusiform gyrus ( Eρ2 = 0.83) for mean activation across sites and test days. For the amygdala, habituation ( Eρ2 = 0.71) was more stable than mean activation. In a second investigation, data from 111 healthy individuals across sites were aggregated in a voxelwise, quantitative meta-analysis. When compared with a mixed effects model controlling for site, both approaches identified robust activation in regions consistent with expected results based on prior single-site research. Overall, regions central to emotion processing showed strong reliability in the traveling participants study and robust activation in the aggregation study. These results support the reliability of blood oxygen level-dependent signal in emotion processing areas across different sites and scanners and may inform future efforts to increase efficiency and enhance knowledge of rare conditions in the population through multisite neuroimaging paradigms.

Prefrontal and Hippocampal Brain Volume Deficits: Role of Low Physical Activity on Brain Plasticity in First-Episode Schizophrenia Patients.

UNLABELLED: Our objective in the present study was to conduct the first empirical study of the effects of regular physical activity habits and their relationship with brain volume and cortical thickness in patients in the early phase of schizophrenia. Relationships between larger brain volumes and higher physical activity levels have been reported in samples of healthy and aging populations, but have never been explored in first-episode schizophrenia patients. METHOD: We collected MRI structural scans in 14 first-episode schizophrenia patients with either self-reported low or high physical activity levels. We found a reduction in total gray matter volume, prefrontal cortex (PFC), and hippocampal gray matter volumes in the low physical activity group compared to the high activity group. Cortical thickness in the dorsolateral and orbitofrontal PFC were also significantly reduced in the low physical activity group compared to the high activity group. In the combined sample, greater overall physical activity levels showed a non-significant tendency with better performance on tests of verbal memory and social cognition. Together these pilot study findings suggest that greater amounts of physical activity may have a positive influence on brain health and cognition in first-episode schizophrenia patients and support the implementation of physical exercise interventions in this patient population to improve brain plasticity and cognitive functioning.

Reliability of functional magnetic resonance imaging activation during working memory in a multi-site study: analysis from the North American Prodrome Longitudinal Study.

Multi-site neuroimaging studies offer an efficient means to study brain functioning in large samples of individuals with rare conditions; however, they present new challenges given that aggregating data across sites introduces additional variability into measures of interest. Assessing the reliability of brain activation across study sites and comparing statistical methods for pooling functional data are critical to ensuring the validity of aggregating data across sites. The current study used two samples of healthy individuals to assess the feasibility and reliability of aggregating multi-site functional magnetic resonance imaging (fMRI) data from a Sternberg-style verbal working memory task. Participants were recruited as part of the North American Prodrome Longitudinal Study (NAPLS), which comprises eight fMRI scanning sites across the United States and Canada. In the first study sample (n=8), one participant from each home site traveled to each of the sites and was scanned while completing the task on two consecutive days. Reliability was examined using generalizability theory. Results indicated that blood oxygen level-dependent (BOLD) signal was reproducible across sites and was highly reliable, or generalizable, across scanning sites and testing days for core working memory ROIs (generalizability ICCs=0.81 for left dorsolateral prefrontal cortex, 0.95 for left superior parietal cortex). In the second study sample (n=154), two statistical methods for aggregating fMRI data across sites for all healthy individuals recruited as control participants in the NAPLS study were compared. Control participants were scanned on one occasion at the site from which they were recruited. Results from the image-based meta-analysis (IBMA) method and mixed effects model with site covariance method both showed robust activation in expected regions (i.e. dorsolateral prefrontal cortex, anterior cingulate cortex, supplementary motor cortex, superior parietal cortex, inferior temporal cortex, cerebellum, thalamus, basal ganglia). Quantification of the similarity of group maps from these methods confirmed a very high (96%) degree of spatial overlap in results. Thus, brain activation during working memory function was reliable across the NAPLS sites and both the IBMA and mixed effects model with site covariance methods appear to be valid approaches for aggregating data across sites. These findings indicate that multi-site functional neuroimaging can offer a reliable means to increase power and generalizability of results when investigating brain function in rare populations and support the multi-site investigation of working memory function in the NAPLS study, in particular.

Reliability of neuroanatomical measurements in a multisite longitudinal study of youth at risk for psychosis.

Multisite longitudinal neuroimaging designs are used to identify differential brain structural change associated with onset or progression of disease. The reliability of neuroanatomical measurements over time and across sites is a crucial aspect of power in such studies. Prior work has found that while within-site reliabilities of neuroanatomical measurements are excellent, between-site reliability is generally more modest. Factors that may increase between-site reliability include standardization of scanner platform and sequence parameters and correction for between-scanner variations in gradient nonlinearities. Factors that may improve both between- and within-site reliability include use of registration algorithms that account for individual differences in cortical patterning and shape. In this study 8 healthy volunteers were scanned twice on successive days at 8 sites participating in the North American Prodrome Longitudinal Study (NAPLS). All sites employed 3 Tesla scanners and standardized acquisition parameters. Site accounted for 2 to 30% of the total variance in neuroanatomical measurements. However, site-related variations were trivial (<1%) among sites using the same scanner model and 12-channel coil or when correcting for between-scanner differences in gradient nonlinearity and scaling. Adjusting for individual differences in sulcal-gyral geometries yielded measurements with greater reliabilities than those obtained using an automated approach. Neuroimaging can be performed across multiple sites at the same level of reliability as at a single site, achieving within- and between-site reliabilities of 0.95 or greater for gray matter density in the majority of voxels in the prefrontal and temporal cortical surfaces as well as for the volumes of most subcortical structures.

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.

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.

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.