Cortico-striatal networking deficits associated with advanced HIV disease and cocaine use.

Cocaine use is disproportionately prevalent in people with HIV (PWH) and is known to potentiate HIV neuropathogenesis. As both HIV and cocaine have well-documented cortico-striatal effects, PWH who use cocaine and have a history of immunosuppression may exhibit greater FC deficits compared to PWH without these conditions. However, research investigating the legacy effects of HIV immunosuppression (i.e., a history of AIDS) on cortico-striatal functional connectivity (FC) in adults with and without cocaine use is sparse. Resting-state functional magnetic resonance imaging (fMRI) and neuropsychological assessment data from 273 adults were analyzed to examine FC in relation to HIV disease: HIV-negative (n = 104), HIV-positive with nadir CD4 ≥ 200 (n = 96), HIV-positive with nadir CD4 < 200 (AIDS; n = 73), and cocaine use (83 COC and 190 NON). Using independent component analysis/dual regression, FC was assessed between the basal ganglia network (BGN) and five cortical networks: dorsal attention network (DAN), default mode network, left executive network, right executive network, and salience network. There were significant interaction effects such that AIDS-related BGN-DAN FC deficits emerged in COC but not in NON participants. Independent of HIV, cocaine effects emerged in FC between the BGN and executive networks. Disruption of BGN-DAN FC in AIDS/COC participants is consistent with cocaine potentiation of neuro-inflammation and may be indicative of legacy HIV immunosuppressive effects. The current study bolsters previous findings linking HIV and cocaine use with cortico-striatal networking deficits. Future research should consider the effects of the duration of HIV immunosuppression and early treatment initiation.

Structural and Functional Brain Abnormalities in Human Immunodeficiency Virus Disease Revealed by Multimodal Magnetic Resonance Imaging Fusion: Association With Cognitive Function.

BACKGROUND: Human immunodeficiency virus (HIV)-associated neurocognitive impairment remains a prevalent comorbidity that impacts daily functioning and increases morbidity. While HIV infection is known to cause widespread disruptions in the brain, different magnetic resonance imaging (MRI) modalities have not been effectively integrated. In this study, we applied 3-way supervised fusion to investigate how structural and functional coalterations affect cognitive function. METHODS: Participants (59 people living with HIV and 58 without HIV) completed comprehensive neuropsychological testing and multimodal MRI scanning to acquire high-resolution anatomical, diffusion-weighted, and resting-state functional images. Preprocessed data were reduced using voxel-based morphometry, probabilistic tractography, and regional homogeneity, respectively. We applied multimodal canonical correlation analysis with reference plus joint independent component analysis using global cognitive functioning as the reference. RESULTS: Compared with controls, participants living with HIV had lower global cognitive functioning. One joint component was both group discriminating and correlated with cognitive function. This component included the following covarying regions: fractional anisotropy in the corpus callosum, short and long association fiber tracts, and corticopontine fibers; gray matter volume in the thalamus, prefrontal cortex, precuneus, posterior parietal regions, and occipital lobe; and functional connectivity in frontoparietal and visual processing regions. Component loadings for fractional anisotropy also correlated with immunosuppression. CONCLUSIONS: These results suggest that coalterations in brain structure and function can distinguish people with and without HIV and may drive cognitive impairment. As MRI becomes more commonplace in HIV care, multimodal fusion may provide neural biomarkers to support diagnosis and treatment of cognitive impairment.

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.

Hub disruption in HIV disease and cocaine use: A connectomics analysis of brain function.

BACKGROUND: Cocaine use (CU) is prevalent in people with HIV (PWH). Both conditions are linked to changes in cognitive functioning and neural network topology. The current study utilizes graph theory to investigate functional connectomics associated with HIV and CU, focusing on disruption of densely connected nodes called hubs. METHODS: Resting state functional magnetic resonance imaging (fMRI) from 206 adults (ages 22-55 years) were analyzed. A HIV x CU factorial design was implemented with participants in four groups: HIV+CU (n= 41), HIV only (n= 88), CU only (n= 36), and controls (n= 41). Functional connectomes were constructed, and thresholded graph metrics were calculated. Network centrality metrics - betweenness centrality (BC), participation coefficient (PC), and within module degree (WD) - were quantified into hub disruption indices (HDI). For each index, a 2×2 ANCOVA was performed controlling for education. RESULTS: Participants were 68 % male and 74 % African-American with a mean age of 44.4 years. HIV and CU were associated with hub disruption in all three indices. Interactions were significant for HDI-PC and HDI-WD, such that HIV disease was associated with greater hub disruption among participants without CU, but not among participants with CU. Overall, lower global cognitive functioning was associated with greater hub disruption on all three indices. CONCLUSIONS: Widespread hub disruption was evident in HIV disease and CU, highlighting topological reorganization in both diseases with neurocognitive effects. Hub-related measures inform functional connectivity disruptions in HIV disease and CU, particularly with respect to changes in network topology throughout the connectome.

Function biomedical informatics research network recommendations for prospective multicenter functional MRI studies.

This report provides practical recommendations for the design and execution of multicenter functional MRI (MC-fMRI) studies based on the collective experience of the Function Biomedical Informatics Research Network (FBIRN). The study was inspired by many requests from the fMRI community to FBIRN group members for advice on how to conduct MC-fMRI studies. The introduction briefly discusses the advantages and complexities of MC-fMRI studies. Prerequisites for MC-fMRI studies are addressed before delving into the practical aspects of carefully and efficiently setting up a MC-fMRI study. Practical multisite aspects include: (i) establishing and verifying scan parameters including scanner types and magnetic fields, (ii) establishing and monitoring of a scanner quality program, (iii) developing task paradigms and scan session documentation, (iv) establishing clinical and scanner training to ensure consistency over time, (v) developing means for uploading, storing, and monitoring of imaging and other data, (vi) the use of a traveling fMRI expert, and (vii) collectively analyzing imaging data and disseminating results. We conclude that when MC-fMRI studies are organized well with careful attention to unification of hardware, software and procedural aspects, the process can be a highly effective means for accessing a desired participant demographics while accelerating scientific discovery.

Principal component analysis denoising improves sensitivity of MR diffusion to detect white matter injury in neuroHIV.

BACKGROUND AND PURPOSE: Diffusion-weighted imaging is able to capture important information about cerebral white matter (WM) structure. However, diffusion data can suffer from MRI and biological noise that degrades the quality of the images and makes finding important features difficult. We investigated how effectively local and nonlocal denoising increased the sensitivity to detect differences in cerebral WM in neuroHIV. METHODS: We utilized principal component analysis (PCA) denoising to detect WM differences using fractional anisotropy. Local and nonlocal PCA denoising paradigms were implemented that varied in search area and number of components. We examined different-sized WM tracts that consistently show differences between people living with Human Immunodeficiency Virus (HIV) (PWH) and HIV-negative individuals (corpus callosum, forceps minor, and right uncinate fasciculus), and size-matched tracts not typically associated with HIV-related differences (spinothalamic, right medial lemniscus, and left occipitopontine). We first conducted a full sample comparison of WM differences between groups, and then randomly reduced the sample to the point where we still found differences in WM. RESULTS: Nonlocal PCA denoising allowed us to detect differences after a sample reduction of 35% in the forceps minor, 17% in the right uncinate fasciculus, and 6% in the corpus callosum. CONCLUSIONS: PCA denoising had a beneficial effect on detecting significant differences in PWH after sample size reduction. The smaller forceps minor tract and right uncinate fasciculus showed greater sensitivity to PCA denoising than the larger corpus callosum. These results show the importance of identifying the most effective PCA denoising strategy when investigating WM in PWH.

Strengthened and posterior-shifted structural rich-club organization in people who use cocaine.

BACKGROUND: People with cocaine use disorder (CUD) often have abnormal cognitive function and brain structure. Cognition is supported by brain networks that typically have characteristics like rich-club organization, which is a group of regions that are highly connected across the brain and to each other, and small worldness, which is a balance between local and long-distance connections. However, it is unknown whether there are abnormalities in structural brain network connectivity of CUD. METHODS: Using diffusion-weighted imaging, we measured structural connectivity in 37 people with CUD and 38 age-matched controls. We identified differences in rich-club organization and whether such differences related to small worldness and behavior. We also tested whether rich-club reorganization was associated with caudate and putamen structural connectivity due to the relevance of the dopamine system to cocaine use. RESULTS: People with CUD had a higher normalized rich-club coefficient than controls, more edges connecting rich-club nodes to each other and to non-rich-club nodes, and fewer edges connecting non-rich-club nodes. Rich-club nodes were shifted posterior and lateral. Rich-club reorganization was related to lower clustered connectivity around individual nodes found in CUD, to increased impulsivity, and to a decrease in caudate connectivity. CONCLUSIONS: These findings are consistent with previous work showing increased rich-club connectivity in conditions associated with a hypofunctional dopamine system. The posterior shift in rich-club nodes in CUD suggests that the structural connectivity of posterior regions may be more impacted than previously recognized in models based on brain function and morphology.

Brain-performance correlates of working memory retrieval in schizophrenia: a cognitive modeling approach.

Correlations of cognitive functioning with brain activation during a sternberg item recognition paradigm (SIRP) were investigated in patients with schizophrenia and in healthy controls studied at 8 sites. To measure memory scanning times, 4 response time models were fit to SIRP data. The best fitting model assumed exhaustive serial memory scanning followed by self-terminating memory search and involved one intercept parameter to represent SIRP processes not contributing directly to memory scanning. Patients displayed significantly longer response times with increasing memory load and differed on the memory scanning, memory search, and intercept parameters of the best fitting probability model. Groups differed in the correlation between the memory scanning parameter and linear brain response to increasing memory load within left inferior and left middle frontal gyrus, bilateral caudate, and right precuneus. The pattern of findings in these regions indicated that high scanning capacity was associated with high neural capacity among healthy subjects but that scanning speed was uncoupled from brain response to increasing memory load among schizophrenia patients. Group differences in correlation of the best fitting model's scanning parameter with a quadratic trend in brain response to increasing memory load suggested inefficient or disordered patterns of neural inhibition among individuals with schizophrenia, especially in the left perirhinal and entorhinal cortices. The results show at both cognitive and neural levels that disordered memory scanning contributes to deficient SIRP performance among schizophrenia patients.

A general XML schema and SPM toolbox for storage of neuro-imaging results and anatomical labels.

With the increased frequency of multisite, large-scale collaborative neuro-imaging studies, the need for a general, self-documenting framework for the storage and retrieval of activation maps and anatomical labels becomes evident. To address this need, we have developed and extensible markup language (XML) schema and associated tools for the storage of neuro-imaging activation maps and anatomical labels. This schema, as part of the XML-based Clinical Experiment Data Exchange (XCEDE) schema, provides storage capabilities for analysis annotations, activation threshold parameters, and cluster and voxel-level statistics. Activation parameters contain information describing the threshold, degrees of freedom, FWHM smoothness, search volumes, voxel sizes, expected voxels per cluster, and expected number of clusters in the statistical map. Cluster and voxel statistics can be stored along with the coordinates, threshold, and anatomical label information. Multiple threshold types can be documented for a given cluster or voxel along with the uncorrected and corrected probability values. Multiple atlases can be used to generate anatomical labels and stored for each significant voxel or cluter. Additionally, a toolbox for Statistical Parametric Mapping software (http://www. fil. ion.ucl.ac.uk/spm/) was created to capture the results from activation maps using the XML schema that supports both SPM99 and SPM2 versions (http://nbirn.net/Resources/Users/ Applications/xcede/SPM_XMLTools.htm). Support for anatomical labeling is available via the Talairach Daemon (http://ric.uthscsa. edu/projects/talairachdaemon.html) and Automated Anatomical Labeling (http://www. cyceron.fr/freeware/).

XCEDE: an extensible schema for biomedical data.

The XCEDE (XML-based Clinical and Experimental Data Exchange) XML schema, developed by members of the BIRN (Biomedical Informatics Research Network), provides an extensive metadata hierarchy for storing, describing and documenting the data generated by scientific studies. Currently at version 2.0, the XCEDE schema serves as a specification for the exchange of scientific data between databases, analysis tools, and web services. It provides a structured metadata hierarchy, storing information relevant to various aspects of an experiment (project, subject, protocol, etc.). Each hierarchy level also provides for the storage of data provenance information allowing for a traceable record of processing and/or changes to the underlying data. The schema is extensible to support the needs of various data modalities and to express types of data not originally envisioned by the developers. The latest version of the XCEDE schema and manual are available from http://www.xcede.org/ .

Automated real-time behavioral and physiological data acquisition and display integrated with stimulus presentation for FMRI.

Functional magnetic resonance imaging (fMRI) is based on correlating blood oxygen-level dependent (BOLD) signal fluctuations in the brain with other time-varying signals. Although the most common reference for correlation is the timing of a behavioral task performed during the scan, many other behavioral and physiological variables can also influence fMRI signals. Variations in cardiac and respiratory functions in particular are known to contribute significant BOLD signal fluctuations. Variables such as skin conduction, eye movements, and other measures that may be relevant to task performance can also be correlated with BOLD signals and can therefore be used in image analysis to differentiate multiple components in complex brain activity signals. Combining real-time recording and data management of multiple behavioral and physiological signals in a way that can be routinely used with any task stimulus paradigm is a non-trivial software design problem. Here we discuss software methods that allow users control of paradigm-specific audio-visual or other task stimuli combined with automated simultaneous recording of multi-channel behavioral and physiological response variables, all synchronized with sub-millisecond temporal accuracy. We also discuss the implementation and importance of real-time display feedback to ensure data quality of all recorded variables. Finally, we discuss standards and formats for storage of temporal covariate data and its integration into fMRI image analysis. These neuroinformatics methods have been adopted for behavioral task control at all sites in the Functional Biomedical Informatics Research Network (FBIRN) multi-center fMRI study.

The influence of emotional distraction on verbal working memory: an fMRI investigation comparing individuals with schizophrenia and healthy adults.

The ability to maintain information over short periods of time (i.e., working memory) is critically important in a variety of cognitive functions including language, planning, and decision-making. Recent functional Magnetic Resonance Imaging (fMRI) research with healthy adults has shown that brain activations evoked during the delay interval of working memory tasks can be reduced by the presentation of distracting emotional events, suggesting that emotional events may take working-memory processes momentarily offline. Both executive function and emotional processing are disrupted in schizophrenia, and here we sought to elucidate the effect of emotional distraction upon brain activity in schizophrenic and healthy adults performing a verbal working memory task. During the delay period between the memoranda and memory probe items, emotional and neutral distractors differentially influenced brain activity in these groups. In healthy adults, the hemodynamic response from posterior cingulate, orbital frontal cortex, and the parietal lobe strongly differentiated emotional from neutral distractors. In striking contrast, schizophrenic adults showed no significant differences in brain activation when processing emotional and neutral distractors. Moreover, the influence of emotional distractors extended into the memory probe period in healthy, but not schizophrenic, adults. The results suggest that although emotional items are highly salient for healthy adults, emotional items are no more distracting than neutral ones to individuals with schizophrenia.

Derived Data Storage and Exchange Workflow for Large-Scale Neuroimaging Analyses on the BIRN Grid.

Organizing and annotating biomedical data in structured ways has gained much interest and focus in the last 30 years. Driven by decreases in digital storage costs and advances in genetics sequencing, imaging, electronic data collection, and microarray technologies, data is being collected at an ever increasing rate. The need to store and exchange data in meaningful ways in support of data analysis, hypothesis testing and future collaborative use is pervasive. Because trans-disciplinary projects rely on effective use of data from many domains, there is a genuine interest in informatics community on how best to store and combine this data while maintaining a high level of data quality and documentation. The difficulties in sharing and combining raw data become amplified after post-processing and/or data analysis in which the new dataset of interest is a function of the original data and may have been collected by multiple collaborating sites. Simple meta-data, documenting which subject and version of data were used for a particular analysis, becomes complicated by the heterogeneity of the collecting sites yet is critically important to the interpretation and reuse of derived results. This manuscript will present a case study of using the XML-Based Clinical Experiment Data Exchange (XCEDE) schema and the Human Imaging Database (HID) in the Biomedical Informatics Research Network's (BIRN) distributed environment to document and exchange derived data. The discussion includes an overview of the data structures used in both the XML and the database representations, insight into the design considerations, and the extensibility of the design to support additional analysis streams.