Data and Tools Integration in the Canadian Open Neuroscience Platform.

We present the Canadian Open Neuroscience Platform (CONP) portal to answer the research community's need for flexible data sharing resources and provide advanced tools for search and processing infrastructure capacity. This portal differs from previous data sharing projects as it integrates datasets originating from a number of already existing platforms or databases through DataLad, a file level data integrity and access layer. The portal is also an entry point for searching and accessing a large number of standardized and containerized software and links to a computing infrastructure. It leverages community standards to help document and facilitate reuse of both datasets and tools, and already shows a growing community adoption giving access to more than 60 neuroscience datasets and over 70 tools. The CONP portal demonstrates the feasibility and offers a model of a distributed data and tool management system across 17 institutions throughout Canada.

Digitization of Measurement-Based Care Pathways in Mental Health Through REDCap and Electronic Health Record Integration: Development and Usability Study.

BACKGROUND: The delivery of standardized self-report assessments is essential for measurement-based care in mental health. Paper-based methods of measurement-based care data collection may result in transcription errors, missing data, and other data quality issues when entered into patient electronic health records (EHRs). OBJECTIVE: This study aims to help address these issues by using a dedicated instance of REDCap (Research Electronic Data Capture; Vanderbilt University)-a free, widely used electronic data capture platform-that was established to enable the deployment of digitized self-assessments in clinical care pathways to inform clinical decision making. METHODS: REDCap was integrated with the primary clinical information system to facilitate the real-time transfer of discrete data and PDF reports from REDCap into the EHR. Both technical and administrative components were required for complete implementation. A technology acceptance survey was also administered to capture physicians' and clinicians' attitudes toward the new system. RESULTS: The integration of REDCap with the EHR transitioned clinical workflows from paper-based methods of data collection to electronic data collection. This resulted in significant time savings, improved data quality, and valuable real-time information delivery. The digitization of self-report assessments at each appointment contributed to the clinic-wide implementation of the major depressive disorder integrated care pathway. This digital transformation facilitated a 4-fold increase in the physician adoption of this integrated care pathway workflow and a 3-fold increase in patient enrollment, resulting in an overall significant increase in major depressive disorder integrated care pathway capacity. Physicians' and clinicians' attitudes were overall positive, with almost all respondents agreeing that the system was useful to their work. CONCLUSIONS: REDCap provided an intuitive patient interface for collecting self-report measures and accessing results in real time to inform clinical decisions and an extensible backend for system integration. The approach scaled effectively and expanded to high-impact clinics throughout the hospital, allowing for the broad deployment of complex workflows and standardized assessments, which led to the accumulation of harmonized data across clinics and care pathways. REDCap is a flexible tool that can be effectively leveraged to facilitate the automatic transfer of self-report data to the EHR; however, thoughtful governance is required to complement the technical implementation to ensure that data standardization, data quality, patient safety, and privacy are maintained.

The CAMH Neuroinformatics Platform: A Hospital-Focused Brain-CODE Implementation.

Investigations of mental illness have been enriched by the advent and maturation of neuroimaging technologies and the rapid pace and increased affordability of molecular sequencing techniques, however, the increased volume, variety and velocity of research data, presents a considerable technical and analytic challenge to curate, federate and interpret. Aggregation of high-dimensional datasets across brain disorders can increase sample sizes and may help identify underlying causes of brain dysfunction, however, additional barriers exist for effective data harmonization and integration for their combined use in research. To help realize the potential of multi-modal data integration for the study of mental illness, the Centre for Addiction and Mental Health (CAMH) constructed a centralized data capture, visualization and analytics environment-the CAMH Neuroinformatics Platform-based on the Ontario Brain Institute (OBI) Brain-CODE architecture, towards the curation of a standardized, consolidated psychiatric hospital-wide research dataset, directly coupled to high performance computing resources.

Age and gender interactions in white matter of schizophrenia and obsessive compulsive disorder compared to non-psychiatric controls: commonalities across disorders.

Schizophrenia (SCZ) and obsessive-compulsive disorder (OCD) are psychiatric disorders with abnormalities in white matter structure. These disorders share high comorbidity and family history of OCD is a risk factor for SCZ which suggests some shared neurobiology. White matter was examined using diffusion tensor imaging in relativity large samples of SCZ (N = 48), OCD (N = 38) and non-psychiatric controls (N = 45). Fractional anisotropy (FA) was calculated and tract based spatial statistics were used to compare groups. In a whole brain analysis, SCZ and OCD both showed small FA reductions relative to controls in the corpus callosum. Both SCZ and OCD showed accelerated reductions in FA with age; specifically in the left superior longitudinal fasciculus in OCD, while the SCZ group demonstrated a more widespread pattern of FA reduction. Patient groups did not differ from each other in total FA or age effects in any regions. A general linear model using 13 a-priori regions of interest showed marginal group, group*gender, and group*age interactions. When OCD and SCZ groups were analyzed together, these marginal effects became significant (p < 0.05), suggesting commonalities exist between these patient groups. Overall, our results demonstrate a similar pattern of accelerated white matter decline with age and greater white matter deficit in females in OCD and SCZ, with overlap in the spatial pattern of deficits. There was no evidence for statistical differences in overall white matter between OCD and SCZ. Taken together, the results support the notion of shared neurobiology in SCZ and OCD.

Limited Evidence for Association of Genome-Wide Schizophrenia Risk Variants on Cortical Neuroimaging Phenotypes.

BACKGROUND: There are now over 100 established genetic risk variants for schizophrenia; however, their influence on brain structure and circuitry across the human lifespan are not known. METHODS: We examined healthy individuals 8-86 years of age, from the Centre for Addiction and Mental Health, the Zucker Hillside Hospital, and the Philadelphia Neurodevelopmental Cohort. Following thorough quality control procedures, we investigated associations of established genetic risk variants with heritable neuroimaging phenotypes relevant to schizophrenia, namely thickness of frontal and temporal cortical regions (n = 565) and frontotemporal and interhemispheric white matter tract fractional anisotropy (FA) (n = 530). RESULTS: There was little evidence for association of risk variants with imaging phenotypes. No association with cortical thickness of any region was present. Only rs12148337, near a long noncoding RNA region, was associated with white matter FA (splenium of corpus callosum) following multiple comparison correction (corrected p = .012); this single nucleotide polymorphism was also associated with genu FA and superior longitudinal fasciculus FA at p <.005 (uncorrected). There was no association of polygenic risk score with white matter FA or cortical thickness. CONCLUSIONS: In sum, our findings provide limited evidence for association of schizophrenia risk variants with cortical thickness or diffusion imaging white matter phenotypes. When taken with recent lack of association of these variants with subcortical brain volumes, our results either suggest that structural neuroimaging approaches at current resolution are not sufficiently sensitive to detect effects of these risk variants or that multiple comparison correction in correlated phenotypes is too stringent, potentially "eliminating" biologically important signals.

Superficial white matter as a novel substrate of age-related cognitive decline.

Studies of diffusion tensor imaging have focused mainly on the role of deep white matter tract microstructural abnormalities associated with aging and age-related cognitive decline. However, the potential role of superficial white matter (SWM) in aging and, by extension, cognitive-aging, is less clear. Healthy individuals (n = 141; F/M: 66/75 years) across the adult lifespan (18-86 years) underwent diffusion tensor imaging and a battery of cognitive testing. SWM was assessed via a combination of probabilistic tractography and tract-based spatial statistics (TBSS). A widespread inverse relationship of fractional anisotropy (FA) values in SWM with age was observed. SWM-FA adjacent to the precentral gyri was associated with fine-motor-speed, whereas performance in visuomotor-attention/processing speed correlated with SWM-FA in all 4 lobes of the left-hemisphere and in right parieto-occipital SWM-FA (family-wise error corrected p < 0.05). Independent of deep white matter-FA, right frontal and right occipital SWM-FA-mediated age effects on motor-speed and visuomotor-attention/processing speed, respectively. Altogether, our results indicate that SWM-FA contributes uniquely to age-related cognitive performance, and should be considered as a novel biomarker of cognitive-aging.

Functional consequences of neurite orientation dispersion and density in humans across the adult lifespan.

As humans age, a characteristic pattern of widespread neocortical dendritic disruption coupled with compensatory effects in hippocampus and other subcortical structures is shown in postmortem investigations. It is now possible to address age-related effects on gray matter (GM) neuritic organization and density in humans using multishell diffusion-weighted MRI and the neurite-orientation dispersion and density imaging (NODDI) model. In 45 healthy individuals across the adult lifespan (21-84 years), we used a multishell diffusion imaging and the NODDI model to assess the intraneurite volume fraction and neurite orientation-dispersion index (ODI) in GM tissues. We also determined the functional correlates of variations in GM microstructure by obtaining resting-state fMRI and behavioral data. We found a significant age-related deficit in neocortical ODI (most prominently in frontoparietal regions), whereas increased ODI was observed in hippocampus and cerebellum with advancing age. Neocortical ODI outperformed cortical thickness and white matter fractional anisotropy for the prediction of chronological age in the same individuals. Higher GM ODI sampled from resting-state networks with known age-related susceptibility (default mode and visual association networks) was associated with increased functional connectivity of these networks, whereas the task-positive networks tended to show no association or even decreased connectivity. Frontal pole ODI mediated the negative relationship of age with executive function, whereas hippocampal ODI mediated the positive relationship of age with executive function. Our in vivo findings align very closely with the postmortem data and provide evidence for vulnerability and compensatory neural mechanisms of aging in GM microstructure that have functional and cognitive impact in vivo.

Quantitative imaging of neuroinflammation in human white matter: a positron emission tomography study with translocator protein 18 kDa radioligand, [18F]-FEPPA.

The ability to quantify translocator protein 18 kDa (TSPO) in white matter (WM) is important to understand the role of neuroinflammation in neurological disorders with WM involvement. This article aims to extend the utility of TSPO imaging in WM using a second-generation radioligand, [18F]-FEPPA, and high-resolution research tomograph (HRRT) positron emission tomography (PET) camera system. Four WM regions of interests (WM-ROI), relevant to the study of aging and neuroinflammatory diseases, were examined. The corpus callosum, cingulum bundle, superior longitudinal fasciculus, and posterior limb of internal capsule were delineated automatically onto subject's T1 -weighted magnetic resonance image using a diffusion tensor imaging-based WM template. The TSPO polymorphism (rs6971) stratified individuals to three genetic groups: high-affinity binders (HAB), mixed-affinity binders (MAB), and low-affinity binders. [18F]-FEPPA PET scans were acquired on 32 healthy subjects and analyzed using a full kinetic compartment analysis. The two-tissue compartment model showed moderate identifiability (coefficient of variation 15-19%) for [18F]-FEPPA total volume distribution (VT ) in WM-ROIs. Noise affects VT variability, although its effect on bias was small (6%). In a worst-case scenario, ≤6% of simulated data did not fit reliably. A simulation of increased TSPO density exposed minimal effect on variability and identifiability of [18F]-FEPPA VT in WM-ROIs. We found no association between age and [18F]-FEPPA VT in WM-ROIs. The VT values were 15% higher in HAB than in MAB, although the difference was not statistically significant. This study provides evidence for the utility and limitations of [18F]-FEPPA PET to measure TSPO expression in WM.

Brain white matter development is associated with a human-specific haplotype increasing the synthesis of long chain fatty acids.

The genetic and molecular pathways driving human brain white matter (WM) development are only beginning to be discovered. Long chain polyunsaturated fatty acids (LC-PUFAs) have been implicated in myelination in animal models and humans. The biosynthesis of LC-PUFAs is regulated by the fatty acid desaturase (FADS) genes, of which a human-specific haplotype is strongly associated with ω-3 and ω-6 LC-PUFA concentrations in blood. To investigate the relationship between LC-PUFA synthesis and human brain WM development, we examined whether this FADS haplotype is associated with age-related WM differences across the life span in healthy individuals 9-86 years of age (n = 207). Diffusion tensor imaging was performed to measure fractional anisotropy (FA), a putative measure of myelination, of the cerebral WM tracts. FADS haplotype status was determined with a single nucleotide polymorphism (rs174583) that tags this haplotype. Overall, normal age-related WM differences were observed, including higher FA values in early adulthood compared with childhood, followed by lower FA values across older age ranges. However, individuals homozygous for the minor allele (associated with lower LC-PUFA concentrations) did not display these normal age-related WM differences (significant age × genotype interactions, p(corrected) < 0.05). These findings suggest that LC-PUFAs are involved in human brain WM development from childhood into adulthood. This haplotype and LC-PUFAs may play a role in myelin-related disorders of neurodevelopmental origin.

Real-time correction by optical tracking with integrated geometric distortion correction for reducing motion artifacts in functional MRI.

Head motion artifacts are a major problem in functional MRI that limit its use in neuroscience research and clinical settings. Real-time scan-plane correction by optical tracking has been shown to correct slice misalignment and nonlinear spin-history artifacts; however, residual artifacts due to dynamic magnetic field nonuniformity may remain in the data. A recently developed correction technique, Phase Labeling for Additional Coordinate Encoding, can correct for absolute geometric distortion using only the complex image data from two echo planar images with slightly shifted k-space trajectories. An approach is presented that integrates Phase Labeling for Additional Coordinate Encoding into a real-time scan-plane update system by optical tracking, applied to a tissue-equivalent phantom undergoing complex motion and an functional MRI finger tapping experiment with overt head motion to induce dynamic field nonuniformity. Experiments suggest that such integrated volume-by-volume corrections are very effective at artifact suppression, with potential to expand functional MRI applications.

Spin-history artifact during functional MRI: potential for adaptive correction.

PURPOSE: Functional magnetic resonance imaging (fMRI) is limited by sensitivity to millimetre-scale head motion. Adaptive correction is a strategy to adjust the imaging plane in response to measured head motion, thereby suppressing motion artifacts. This strategy should correct for motion in all six degrees of freedom and also holds promise for through-plane motion that creates "spin-history" artifact that cannot easily be removed by postprocessing methods. Improved quantitative understanding of the MRI signal behavior associated with spin-history artifact would be useful for implementing adaptive correction robustly. METHODS: A numerical simulation was developed to predict MRI artifact signal amplitude in a single-slice for simple motions, implemented with and without adaptive correction, and compared with experiment by imaging a phantom at 3.0 T. Functional MRI was also performed of a human volunteer to illustrate adaptive correction in the presence of spin-history artifact. RESULTS: Good agreement was achieved between simulation and experimental results. Although time-averaged artifact signal amplitude was observed to correlate linearly with motion speed, artifact time-courses were nonlinearly related to motion waveforms. In addition, experimental results demonstrated effective adaptive correction of spin-history artifact when the phantom underwent complex motions. Adaptive correction during human fMRI suppressed spin-history artifacts and spurious activations associated with task-correlated motion. CONCLUSIONS: Overall, this work suggests that adaptive correction, especially when implemented with minimal lag between motion measurement and scan plane update, may help to expand the populations for which fMRI can be performed robustly.