Relationship of neurite architecture to brain activity during task-based fMRI

Functional MRI (fMRI) has been widely used to examine changes in neuronal activity during cognitive tasks. Commonly used measures of gray matter macrostructure (e.g., cortical thickness, surface area, volume) do not consistently appear to serve as structural correlates of brain function. In contrast, gray matter microstructure, measured using neurite orientation dispersion and density imaging (NODDI), enables the estimation of indices of neurite density (neurite density index; NDI) and organization (orientation dispersion index; ODI) in gray matter. Our study explored the relationship among neurite architecture, BOLD (blood-oxygen-level-dependent) fMRI, and cognition, using a large sample (n = 750) of young adults of the human connectome project (HCP) and two tasks that index more cortical (working memory) and more subcortical (emotion processing) targeting of brain functions. Using NODDI, fMRI, structural MRI and task performance data, hierarchical regression analyses revealed that higher working memory- and emotion processing-evoked BOLD activity was related to lower ODI in the right DLPFC, and lower ODI and NDI values in the right and left amygdala, respectively. Common measures of brain macrostructure (i.e., DLPFC thickness/surface area and amygdala volume) did not explain any additional variance (beyond neurite architecture) in BOLD activity. A moderating effect of neurite architecture on the relationship between emotion processing task-evoked BOLD response and performance was observed. Our findings provide evidence that neuro-/social-affective cognition-related BOLD activity is partially driven by the local neurite organization and density with direct impact on emotion processing. In vivo gray matter microstructure represents a new target of investigation providing strong potential for clinical translation

Microstructural abnormalities in deep and superficial white matter in youths with mild traumatic brain injury

BACKGROUND: Diffusion Tensor Imaging (DTI) studies of traumatic brain injury (TBI) have focused on alterations in microstructural features of deep white matter fibers (DWM), though post-mortem studies have demonstrated that injured axons are often observed at the gray-white matter interface where superficial white matter fibers (SWM) mediate local connectivity. OBJECTIVES: To examine microstructural alterations in SWM and DWM in youths with a history of mild TBI and examine the relationship between white matter alterations and attention. METHODS: Using DTIDWM fractional anisotropy (FA) and SWM FA in youths with mild TBI (TBI, n=63) were compared to typically developing and psychopathology matched control groups (n=63 each). Following tract-based spatial statistics, SWM FA was assessed by applying a probabilistic tractography derived SWM mask, and DWM FA was captured with a white matter fiber tract mask. Voxel-wise z-score calculations were used to derive a count of voxels with abnormally high and low FA for each participant. Analyses examined DWM and SWM FA differences between TBI and control groups, the relationship between attention and DWM and SWM FA and the relative susceptibility of SWM compared to DWM FA to alterations associated with mild TBI. RESULTS: Case-based comparisons revealed more voxels with low FA and fewer voxels with high FA in SWM in youths with mild TBI compared to both control groups. Equivalent comparisons in DWM revealed a similar pattern of results, however, no group differences for low FA in DWM were found between mild TBI and the control group with matched psychopathology. Slower processing speed on the attention task was correlated with the number of voxels with low FA in SWM in youths with mild TBI. CONCLUSIONS: Within a sample of youths with a history of mild TBI, this study identified abnormalities in SWM microstructure associated with processing speed. The majority of DTI studies of TBI have focused on long-range DWM fiber tracts, often overlooking the SWM fiber type

Sex and Diffusion Tensor Imaging of White Matter in Schizophrenia: A Systematic Review Plus Meta-analysis of the Corpus Callosum

Sex is considered an understudied variable in health research. Schizophrenia is a brain disorder with known sex differences in epidemiology and clinical presentation. We systematically reviewed the literature for sex-based differences of diffusion properties of white matter tracts in schizophrenia. We then conducted a meta-analysis examining sex-based differences in the genu and splenium of the corpus callosum in schizophrenia. Medline and Embase were searched to identify relevant papers. Studies fulfilling the following criteria were included: (1) included individuals with a diagnosis of schizophrenia, (2) included a control group of healthy individuals, (3) included both sexes in the patient and the control groups, (4) used diffusion tensor imaging, and (5) involved analyzing metrics of white matter microstructural integrity. Fractional anisotropy (FA) was used as the measure of interest in the meta-analysis. Of 730 studies reviewed, 75 met the inclusion criteria. Most showed no effect of sex, however, those that did found either that females have lower FA than males, or that the effect of disease in females is larger than that in males. The findings of the meta-analysis in the corpus callosum supported this result. There is a recognized need for studies on schizophrenia with a sufficient sample of female patients. Lack of power undermines the ability to detect sex-based differences. Understanding the sex-specific impact of illness on neural circuits may help inform development of new treatments, and improvement of existing interventions

Personality Goes a Long a Way: An Interhemispheric Connectivity Study

Throughout the development of psychology the delineation of personality has played a central role. Together with the NEO-PI-R, a questionnaire derived from the Five Factor Model of Personality, and recent advances in research technology it is now possible to investigate the relationship between personality features and neurophysiological brain processes. The NEO-FFI, the short version of the NEO-PI-R, reliably measures five main personality traits: Neuroticism, Extraversion, Openness to experience, Agreeableness, and Conscientiousness. As behavior and some psychiatric disorders have been related to interhemispheric connectivity, the present study used the combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to measure frontal interhemispheric connectivity and its association with personality as indexed by the NEO-FFI. Results demonstrated that prefrontal interhemispheric connectivity between the left and right dorsolateral prefrontal cortex correlates with Agreeableness in healthy subjects. This is the first study to relate personality features to interhemispheric connectivity through TMS–EEG and suggests that Agreeableness relates to the effectiveness of prefrontal communication between hemispheres

Myelin-Associated Glycoprotein Gene and Brain Morphometry in Schizophrenia

Myelin and oligodendrocyte disruption may be a core feature of schizophrenia pathophysiology. The purpose of the present study was to localize the effects of previously identified risk variants in the myelin-associated glycoprotein (MAG) gene on brain morphometry in schizophrenia patients and healthy controls. Forty-five schizophrenia patients and 47 matched healthy controls underwent clinical, structural magnetic resonance imaging, and genetics procedures. Gray and white matter cortical lobe volumes along with hippocampal volumes were calculated from T1-weighted MRI scans. Each subject was also genotyped for the two disease-associated MAG single nucleotide polymorphisms (rs720308 and rs720309). Repeated measures general linear model (GLM) analysis found significant region by genotype and region by genotype by diagnosis interactions for the effects of MAG risk variants on lobar gray matter volumes. No significant associations were found with lobar white matter volumes or hippocampal volumes. Follow-up univariate GLMs found the AA genotype of rs720308 predisposed schizophrenia patients to left temporal and parietal gray matter volume deficits. These results suggest that the effects of the MAG gene on cortical gray matter volume in schizophrenia patients can be localized to temporal and parietal cortices. Our results support a role for MAG gene variation in brain morphometry in schizophrenia, align with other lines of evidence implicating MAG in schizophrenia, and provide genetically based insight into the heterogeneity of brain imaging findings in this disorder

Manual-protocol inspired technique for improving automated MR image segmentation during label fusion

Recent advances in multi-atlas based algorithms address many of the previous limitations in model-based and probabilistic segmentation methods. However, at the label fusion stage, a majority of algorithms focus primarily on optimizing weight-maps associated with the atlas library based on a theoretical objective function that approximates the segmentation error. In contrast, we propose a novel method-Autocorrecting Walks over Localized Markov Random Fields (AWoL-MRF)-that aims at mimicking the sequential process of manual segmentation, which is the gold-standard for virtually all the segmentation methods. AWoL-MRF begins with a set of candidate labels generated by a multi-atlas segmentation pipeline as an initial label distribution and refines low confidence regions based on a localized Markov random field (L-MRF) model using a novel sequential inference process (walks). We show that AWoL-MRF produces state-of-the-art results with superior accuracy and robustness with a small atlas library compared to existing methods. We validate the proposed approach by performing hippocampal segmentations on three independent datasets: (1) Alzheimer\u27s Disease Neuroimaging Database (ADNI); (2) First Episode Psychosis patient cohort; and (3) A cohort of preterm neonates scanned early in life and at term-equivalent age. We assess the improvement in the performance qualitatively as well as quantitatively by comparing AWoL-MRF with majority vote, STAPLE, and Joint Label Fusion methods. AWoL-MRF reaches a maximum accuracy of 0.881 (dataset 1), 0.897 (dataset 2), and 0.807 (dataset 3) based on Dice similarity coefficient metric, offering significant performance improvements with a smaller atlas library (\u3c 10) over compared methods. We also evaluate the diagnostic utility of AWoL-MRF by analyzing the volume differences per disease category in the ADNI1: Complete Screening dataset. We have made the source code for AWoL-MRF public at: https://github.com/CobraLab/AWoL-MRF

Mortality after the First Diagnosis of Schizophrenia-Spectrum Disorders: A Population-based Retrospective Cohort Study

There is emerging evidence of high mortality rates after the first diagnosis of psychotic disorder. The objective of this study was to estimate the standardized mortality ratio (SMR) in a population-based cohort of individuals with a first diagnosis of schizophrenia-spectrum psychotic disorder (SSD). The cohort included a population-based sample of individuals with a first diagnosis of SSD based on the first diagnosis occurring during hospitalization or in an outpatient setting between 2007 and 2010 in Ontario, Canada. All patients were followed for 5 years after the first diagnosis. The primary outcome was SMR, including all-cause, suicide-related, accidental, and other causes. Between 2007 and 2010, there were 2382 patients in the hospitalization cohort and 11 003 patients in the outpatient cohort. Over the 5-year observation period, 97 (4.1%) of the hospitalization cohort and 292 (2.7%) of the outpatient cohort died, resulting in an SMR of 13.6 and 9.1, respectively. In both cohorts, suicide was the most common cause of death. Approximately 1 in 25 patients with a first diagnosis of SSD during hospitalization, and 1 in 40 patients with a first diagnosis of SSD in an outpatient setting, died within 5 years of first diagnosis in Ontario, Canada. This mortality rate is between 9 and 13 times higher than would be expected in the age-matched general population. Based on these data, timely access to services should be a public health priority to reduce mortality following a first diagnosis of an SSD

Cortico-amygdalar connectivity and externalizing/internalizing behavior in children with neurodevelopmental disorders

Background: Externalizing and internalizing behaviors contribute to clinical impairment in children with neurodevelopmental disorders (NDDs). Although associations between externalizing or internalizing behaviors and cortico-amygdalar connectivity have been found in clinical and non-clinical pediatric samples, no previous study has examined whether similar shared associations are present across children with different NDDs. Methods: Multi-modal neuroimaging and behavioral data from the Province of Ontario Neurodevelopmental Disorders (POND) Network were used. POND participants aged 6–18 years with a primary diagnosis of autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) or obsessive–compulsive disorder (OCD), as well as typically developing children (TDC) with T1-weighted, resting-state fMRI or diffusion weighted imaging (DWI) and parent-report Child Behavioral Checklist (CBCL) data available, were analyzed (total n = 346). Associations between externalizing or internalizing behavior and cortico-amygdalar structural and functional connectivity indices were examined using linear regressions, controlling for age, gender, and image-modality specific covariates. Behavior-by-diagnosis interaction effects were also examined. Results: No significant linear associations (or diagnosis-by-behavior interaction effects) were found between CBCL-measured externalizing or internalizing behaviors and any of the connectivity indices examined. Post-hoc bootstrapping analyses indicated stability and reliability of these null results. Conclusions: The current study provides evidence towards an absence of a shared linear relationship between internalizing or externalizing behaviors and cortico-amygdalar connectivity properties across a transdiagnostic sample of children with different primary NDD diagnoses and TDC. Different methodological approaches, including incorporation of multi-dimensional behavioral data (e.g., task-based fMRI) or clustering approaches may be needed to clarify complex brain-behavior relationships relevant to externalizing/internalizing behaviors in heterogeneous clinical NDD populations

Multivariate brain functional connectivity through regularized estimators

Functional connectivity analyses are typically based on matrices containing bivariate measures of covariability, such as correlations. Although this has been a fruitful approach, it may not be the optimal strategy to fully explore the complex associations underlying brain activity. Here, we propose extending connectivity to multivariate functions relating to the temporal dynamics of a region with the rest of the brain. The main technical challenges of such an approach are multidimensionality and its associated risk of overfitting or even the non-uniqueness of model solutions. To minimize these risks, and as an alternative to the more common dimensionality reduction methods, we propose using two regularized multivariate connectivity models. On the one hand, simple linear functions of all brain nodes were fitted with ridge regression. On the other hand, a more flexible approach to avoid linearity and additivity assumptions was implemented through random forest regression. Similarities and differences between both methods and with simple averages of bivariate correlations (i.e., weighted global brain connectivity) were evaluated on a resting state sample of N = 173 healthy subjects. Results revealed distinct connectivity patterns from the two proposed methods, which were especially relevant in the age-related analyses where both ridge and random forest regressions showed significant patterns of age-related disconnection, almost completely absent from the much less sensitive global brain connectivity maps. On the other hand, the greater flexibility provided by the random forest algorithm allowed detecting sex-specific differences. The generic framework of multivariate connectivity implemented here may be easily extended to other types of regularized models

Effect of Continuing Olanzapine vs Placebo on Relapse Among Patients With Psychotic Depression in Remission: The STOP-PD II Randomized Clinical Trial

Importance: Psychotic depression is a severely disabling and potentially lethal disorder. Little is known about the efficacy and tolerability of continuing antipsychotic medication for patients with psychotic depression in remission. Objective: To determine the clinical effects of continuing antipsychotic medication once an episode of psychotic depression has responded to combination treatment with an antidepressant and antipsychotic agent. Design, Setting, and Participants: Thirty-six week randomized clinical trial conducted at 4 academic medical centers. Patients aged 18 years or older had an episode of psychotic depression acutely treated with sertraline plus olanzapine for up to 12 weeks and met criteria for remission of psychosis and remission or near-remission of depressive symptoms for 8 weeks before entering the clinical trial. The study was conducted from November 2011 to June 2017, and the final date of follow-up was June 13, 2017. Interventions: Participants were randomized either to continue olanzapine (n = 64) or switch from olanzapine to placebo (n = 62). All participants continued sertraline. Main Outcomes and Measures: The primary outcome was risk of relapse. Main secondary outcomes were change in weight, waist circumference, lipids, serum glucose, and hemoglobin A1c (HbA1c). Results: Among 126 participants who were randomized (mean [SD] age, 55.3 years [14.9 years]; 78 women [61.9%]), 114 (90.5%) completed the trial. At the time of randomization, the median dosage of sertraline was 150 mg/d (interquartile range [IQR], 150-200 mg/d) and the median dosage of olanzapine was 15 mg/d (IQR, 10-20 mg/d). Thirteen participants (20.3%) randomized to olanzapine and 34 (54.8%) to placebo experienced a relapse (hazard ratio, 0.25; 95% CI, 0.13 to 0.48; P \u3c .001). The effect of olanzapine on the daily rate of anthropometric and metabolic measures significantly differed from placebo for weight (0.13 lb; 95% CI, 0.11 to 0.15), waist circumference (0.009 inches; 95% CI, 0.004 to 0.014), and total cholesterol (0.29 mg/dL; 95% CI, 0.13 to 0.45) but was not significantly different for low-density lipoprotein cholesterol (0.04 mg/dL; 95% CI, -0.01 to 0.10), high-density lipoprotein cholesterol (-0.01 mg/dL; 95% CI, -0.03 to 0.01), triglyceride (-0.153 mg/dL; 95% CI, -0.306 to 0.004), glucose (-0.02 mg/dL; 95% CI, -0.12 to 0.08), or HbA1c levels (-0.0002 mg/dL; 95% CI, -0.0021 to 0.0016). Conclusions and Relevance: Among patients with psychotic depression in remission, continuing sertraline plus olanzapine compared with sertraline plus placebo reduced the risk of relapse over 36 weeks. This benefit needs to be balanced against potential adverse effects of olanzapine, including weight gain. Trial Registration: ClinicalTrials.gov Identifier: NCT01427608