MR Imaging Biomarkers in HIV associated Neurocognitive Impairment in the Era of cART

HIV associated neurocognitive disorder (HAND) continues to occur despite virally suppressive combination of antiretroviral therapy. The viral toxins, neuroinflammation secondary to host factor (ARV toxicity, immune reconstitution are additional factors) and the comorbidities in combination or individually appear to drive the ongoing HAND. Although in the pre-cART era the biomarkers of HIV dementia were clearly laid out in terms of clinical, biochemical and imaging criteria, in the cART era this has become more blurred. Some of the observations drawn from the imaging studies to identify the pathological underpinnings have shown conflicting results by different authors. The cause of these contradictory imaging observations are multifocal but principally linked to the observation that “HIV neural injury is not a one-time event”. Therefore, the paradigm of imaging should be tailored to the diversity of the disease spectrum. I have used the advanced imaging techniques to identify if there are any imaging techniques which can demonstrate the ongoing neural injury as well as monitor the response to the therapy in this research using both cross sectional and longitudinal experiments. I have also explored if there is any imaging equivalent to identify the neuroinflammation

Comparison of resting state functional networks in HIV infected and uninfected children at age 9 years

Over 2.5 million children are infected with HIV, the majority of whom reside in Sub-Saharan Africa. Treatment coverage is steadily gaining momentum, reducing mortality and morbidity. Yet little is known about brain development in HIV-infected (HIV+) children who are on highly-active antiretroviral therapy (ART), with viral load suppression from a young age. Here, we use resting state fMRI (rs-fMRI) to examine the impact of HIV and ART on the development of functional networks in 9-year-old vertically HIV-infected children compared to age-matched controls of similar socioeconomic status. We present analyses for a sample of 40 HIV+ (9.2 ± 0.20 years; 16 males) children from the Children with HIV Early Antiretroviral (CHER) clinical trial (Cotton et al. 2013; Violari et al. 2008) and 24 uninfected (12 exposed; 12 males; 9.6 ± 0.52 years) controls from an interlinking vaccine trial (Madhi et al. 2010). Scans were performed at the Cape Universities Body Imaging Centre (CUBIC) in Cape Town, South Africa. We investigated HIV-related differences in within- and between-network functional connectivity (FC) using independent component analysis(ICA) and seed-based correlation analysis (SCA). For SCA, seeds were placed in the structural core, in regions implicated in HIV-related between-group differences at age 7 years, and in regions associated with neuropsychological domains impaired in our cohort. In addition, we evaluated associations of past and present immune health measures with within-network connectivity using ICA. We found no HIV-related intra-network FC differences within any ICA-generated RSNs at age 9 years, perhaps as a result of within-network connectivity not being sufficiently robust at this age. We found a positive association of CD4%, both current and in infancy, with functional integration of left lobule 7 into the cerebellum network at age 9 years. Long-term impact of early immune health supports recently-revised policies of commencing ART immediately in HIV+ neonates. ii Compared to uninfected children, HIV+ children had increased FC to several seeds. Firstly, to seeds associated with the planning and visual perception neuropsychological domains. Secondly, to structural core seeds in the extrastriate visual cortex (of the medial visual network) and the right angular gyrus (of the temporoparietal network). Finally, to left paracentral (somatosensory network) and right precuneus (posterior DMN) seeds previously revealing between-group differences at age 7 years. The connections with greater FC in HIV+ children may variously indicate functional recruitment of additional brain capacity, immature excess of short-range connections, and/or immature excess of between-network connections. In conclusion, despite early ART and early virologic suppression, HIV+ children demonstrate instances of abnormal FC at age 9 years. Disruption to visual cortex is marked, consistent with indications from neuropsychological testing that visual perception is disrupted. The profile of HIV- and/or ART-related effects on FC differs considerably between the two ages of 7 and 9 years, but both show characteristics of immature functional organisation compared with age-matched controls

The effects of perceived discrimination on the resting state connectivity of the brain in older adults

Over the last 20 years, there has been increasing research on the negative effects of discrimination on the mental and physical health of people of color. As mental health has an important relationship with the functional connectivity of brain networks, it is vital to further understand this. One way to measure functional brain connectivity is by observing the activity of the brain’s resting state networks (RSN) while a participant is at rest. Previous studies investigating connectivity have demonstrated a relationship between altered connectivity of RSNs and neuropsychiatric disorders, including Alzheimer’s disease, depression, and anxiety. The RSN of interest in this analysis is the salience network (SN). This network, anchored in the anterior insula and dorsal anterior cingulate cortex, is involved in the responses to “salient” stimuli that are infrequent in space or time, compete for an individual’s attention, and are surprising or emotionally engaging, such as an act of discrimination. The aim of this study was to use a seed-based correlation analysis to examine the relationship between perceived discrimination and the functional connectivity of the SN in black and white participants and to evaluate the differences in SN functional connectivity between black and white participants. Resting state functional connectivity was measured by using the functional magnetic resonance imaging (fMRI) data collected from 18 healthy older adults partaking in two different studies investigating aging, cognition, and the accompanying changes in neuroanatomy. The Analysis of Functional NeuroImages (AFNI) software was used to examine the correlations in activation in the primary nodes of the SN with activation in clusters in the other primary nodes. Perceived discrimination was measured using the Experiences of Discrimination Scale (EOD), a self-report measuring the frequency of instances of discrimination and the perceived reason behind the discrimination. Preliminary results from this analysis demonstrated that black participants, when compared to the white participants, demonstrated greater functional connectivity between the left and right insula and decreased functional connectivity between the right anterior cingulate cortex and the right insula. Black participants demonstrated a positive association between perceived overall discrimination and functional connectivity between the right and left insula and a negative association between perceived overall discrimination and functional connectivity between the right anterior cingulate cortex and the left insula. The white participants demonstrated a negative association between perceived overall discrimination and functional connectivity between the left and the right insula. Considering the inability for these results to survive correction for multiple comparisons, a larger sample size is necessary to obtain true statistical significance. Although existing research has implicated functional connectivity changes in the regions of the salience network in populations experiencing social exclusion, anxiety, and depression, further analyses are necessary to expand the limited research available regarding the effects of overall and race-based discrimination on the resting state functional connectivity of neural networks involved in emotional processing

Biomarker discovery and statistical modeling with applications in childhood epilepsy and Angelman syndrome

Biomarker discovery and statistical modeling reveals the brain activity that supports brain function and dysfunction. Detecting abnormal brain activity is critical for developing biomarkers of disease, elucidating disease mechanisms and evolution, and ultimately improving disease course. In my thesis, we develop statistical methodology to characterize neural activity in disease from noisy electrophysiological recordings. First, we develop a modification of a classic statistical modeling approach - multivariate Granger causality - to infer coordinated activity between brain regions. Assuming the signaling dependencies vary smoothly, we propose to write the history terms in autoregressive models of the signals using a lower dimensional spline basis. This procedure requires fewer parameters than the standard approach, thus increasing the statistical power. we show that this procedure accurately estimates brain dynamics in simulations and examples of physiological recordings from a patient with pharmacoresistant epilepsy. This work provides a statistical framework to understand alternations in coordinated brain activity in disease. Second, we demonstrate that sleep spindles, thalamically-driven neural rhythms (9-15 Hz) associated with sleep-dependent learning, are a reliable biomarker for Rolandic epilepsy. Rolandic epilepsy is the most common form of childhood epilepsy and characterized by nocturnal focal epileptic discharges as well as neurocognitive deficits. We show that sleep spindle rate is reduced regionally across cortex and correlated with poor cognitive performance in epilepsy. These results provide evidence for a regional disruption to the thalamocortical circuit in Rolandic epilepsy, and a potential mechanistic explanation for the cognitive deficits observed. Finally, we develop a procedure to utilize delta rhythms (2-4 Hz), a sensitive biomarker for Angelman syndrome, as a non-invasive measure of treatment efficacy in clinical trials. Angelman syndrome is a rare neurodevelopmental disorder caused by reduced expression of the UBE3A protein. Many disease-modifying treatments are being developed to reinstate UBE3A expression. To aid in clinical trials, we propose a procedure that detects therapeutic improvements in delta power outside of the natural variability over age by developing a longitudinal natural history model of delta power. These results demonstrate the utility of biomarker discovery and statistical modeling for elucidating disease course and mechanisms with the long-term goal of improving patient outcomes

Fluctuations of attention network activation during the resting state reflect fluctuations in subjective attentional state.

peer reviewe

A multimodal approach to investigate brain reorganization after spinal cord injury using functional magnetic resonance imaging and functional near-infrared spectroscopy

Traumatic Spinal Cord Injury (SCI) results in structural and functional neurological changes at both the brain and the level of the spinal cord. Anatomical studies indicate decreased grey matter volume in sensorimotor and non-sensorimotor regions of the cortex following SCI; whereas, neurophysiological findings mostly report altered functional activity in the sensorimotor nodes of the cortex, subcortex, and cerebellum. Therefore, it is currently unknown whether tissue atrophy observed in non-motor related areas has any concomitant functional consequences. Furthermore, the neural underpinnings of adaptive neuroplasticity after SCI is not well-defined in the current literature. Hence, this dissertation is a pioneer study investigating the structural and functional changes in the whole brain after SCI, with particular focus on subcortical regions, using a multimodal approach employing magnetic resonance imaging (MRI), resting-state functional MRI (fMRI) and functional near-infrared spectroscopy (fNIRS), that may take best advantage of each of these three tools. MRI scans from 23 healthy controls (HC) and 36 individuals with complete SCI within two years of injury were used to demonstrate that both injury level and duration since injury are important factors contributing to recovery. Specifically, cervical level injury when compared to thoracolumbar level injury exhibits a greater loss of cortical grey matter volume in the orbitofrontal cortex, insula, and anterior cingulate cortex. Next, using the fMRI scans of the same participants during a resting-state scan, the intrinsic functional connectivity of the mediodorsal, pulvinar and ventrolateral nuclei of the thalamus to the regions of salient network and the fronto-parietal network is observed to be dynamic and altered in the SCI group. Lastly, a continuous-wave fNIRS is used to reliably measure brain function in individuals with SCI during both dynamic and static tasks while accounting for cerebrovascular reactivity. Five min of resting-state data and 26 min of motor data including finger tapping, finger tapping imagery and ankle tapping were acquired to identify the spatial activation pattern unique to each of the movement type. A breath-hold paradigm is also used to quantify cerebrovascular reactivity as a means to calibrate task activity from neurovascular constraints. Sixteen HC were scanned at two separate visits to determine the sensitivity and test-retest reliability of fNIRS data from the sensorimotor cortex. Following validation, the same procedure was repeated in 13 individuals with paraplegia resulting from SCI and 13 HC to quantify alterations in the cortical activity of the motor cortex and cerebrovascular reactivity between the two groups. Results indicate that SCI group exhibit altered cerebrovascular reactivity with greater delay in response and greater pre-stimulus undershoot. As hypothesized, the hemodynamic response to ankle movement resulted in only a small change in oxyhemoglobin concentration in the sensorimotor cortex of SCI group when compared to HC. The application of fNIRS to assess cortical reorganization following SCI is unique and expands our understanding of the neurophysiology after SCI. It paves the groundwork for extending the implementation of fNIRS to rehabilitation research and other clinical populations with vascular dysfunction. This dissertation is one of the first studies to comprehensively examine both the structural and functional alterations of the brain in humans with complete SCI and opens promising avenues for SCI research using fNIRS modality

Multi-level characterization and information extraction in directed and node-labeled functional brain networks

Current research in computational neuroscience puts great emphasis on the computation and analysis of the functional connectivity of the brain. The methodological developments presented in this work are concerned with a group-specific comprehensive analysis of networks that represent functional interaction patterns. Four application studies are presented, in which functional brain network samples of different clinical background were analyzed in different ways, using combinations of established approaches and own methodological developments. Study I is concerned with a sample-specific decomposition of the functional brain networks of depressed subjects and healthy controls into small functionally important and recurring subnetworks (motifs) using own developments. Study II investigates whether lithium treatment effects are reflected in the functional brain networks of HIV-positive subjects with diagnosed cognitive impairment. For it, microscopic and macroscopic structural properties were analyzed. Study III explores spatially highly resolved functional brain networks with regard to a functional segmentation given by identified module (community) structure. Also, ground truth networks with known module structure were generated using own methodological developments. They formed the basis of a comprehensive simulation study that quantified module structure quality and preservation in order to evaluate the effects of a novel approach for the identification of connectivity (lsGCI). Study IV tracks the time-evolution of module structure and introduces a newly developed own approach for the determination of edge weight thresholds based on multicriteria optimization. The methodological challenges that underly these different topological analyses, but also the various opportunities to gain an improved understanding of neural information processing among brain areas were highlighted by this work and the presented results