Characterising population variability in brain structure through models of whole-brain structural connectivity

Models of whole-brain connectivity are valuable for understanding neurological function. This thesis seeks to develop an optimal framework for extracting models of whole-brain connectivity from clinically acquired diffusion data. We propose new approaches for studying these models. The aim is to develop techniques which can take models of brain connectivity and use them to identify biomarkers or phenotypes of disease. The models of connectivity are extracted using a standard probabilistic tractography algorithm, modified to assess the structural integrity of tracts, through estimates of white matter anisotropy. Connections are traced between 77 regions of interest, automatically extracted by label propagation from multiple brain atlases followed by classifier fusion. The estimates of tissue integrity for each tract are input as indices in 77x77 ”connectivity” matrices, extracted for large populations of clinical data. These are compared in subsequent studies. To date, most whole-brain connectivity studies have characterised population differences using graph theory techniques. However these can be limited in their ability to pinpoint the locations of differences in the underlying neural anatomy. Therefore, this thesis proposes new techniques. These include a spectral clustering approach for comparing population differences in the clustering properties of weighted brain networks. In addition, machine learning approaches are suggested for the first time. These are particularly advantageous as they allow classification of subjects and extraction of features which best represent the differences between groups. One limitation of the proposed approach is that errors propagate from segmentation and registration steps prior to tractography. This can cumulate in the assignment of false positive connections, where the contribution of these factors may vary across populations, causing the appearance of population differences where there are none. The final contribution of this thesis is therefore to develop a common co-ordinate space approach. This combines probabilistic models of voxel-wise diffusion for each subject into a single probabilistic model of diffusion for the population. This allows tractography to be performed only once, ensuring that there is one model of connectivity. Cross-subject differences can then be identified by mapping individual subjects’ anisotropy data to this model. The approach is used to compare populations separated by age and gender

Impulsivity Relates to Relative Preservation of Mesolimbic Connectivity in Patients with Parkinson Disease.

IntroductionThe relationship between Parkinson Disease (PD) pathology, dopamine replacement therapy (DRT), and impulse control disorder (ICD) development is still incompletely understood. Given the sensorimotor-lateral substantia nigra (SN) selective degeneration associated with PD, we posit that a relative sparing of the limbic-medial SN in the context of DRT drives impulsive, reward-seeking behavior in PD patients with recent history of severe impulsivity.MethodsImpulsive and control participants were selected from a consecutive list of PD patients receiving pre-operative deep brain stimulation (DBS) planning scans including 3T structural MRI and 64 direction diffusion tensor imaging (DTI). Using previously identified substantia nigra (SN) subsegment network connectivity profiles to develop classification targets, split-hemisphere target-based SN segmentation with probabilistic tractography was performed. The relative subsegment volumes and strength of connectivity between the SN and the limbic, associative, and motor network targets were compared.ResultsOur results show that there is greater probability of connectivity between the SN and limbic network targets relative to motor and associative network targets in PD patients with recent history of severe impulsivity as compared to PD patients without impulsivity (P = 0.0075). We did not observe relative volumetric subsegment differences across groups.ConclusionFirstly, our results suggest that fine-grained, atlas-derived classification targets may be used in PD to parcellate and classify functionally distinct subsegments of the SN, with the apparent preservation of previously reported topographical limbic-medial SN, associative-ventral SN, and sensorimotor-lateral SN orientation. We suggest that relative, as opposed to absolute, degeneration amongst SN-associated dopaminergic networks relates to the impulsivity phenotype in PD

Confirmation of functional zones within the human subthalamic nucleus: Patterns of connectivity and sub-parcellation using diffusion weighted imaging

The subthalamic nucleus (STN) is a small, glutamatergic nucleus situated in the diencephalon. A critical component of normal motor function, it has become a key target for deep brain stimulation in the treatment of Parkinson's disease. Animal studies have demonstrated the existence of three functional sub-zones but these have never been shown conclusively in humans. In this work, a data driven method with diffusion weighted imaging demonstrated that three distinct clusters exist within the human STN based on brain connectivity profiles. The STN was successfully sub-parcellated into these regions, demonstrating good correspondence with that described in the animal literature. The local connectivity of each sub-region supported the hypothesis of bilateral limbic, associative and motor regions occupying the anterior, mid and posterior portions of the nucleus respectively. This study is the first to achieve in-vivo, non-invasive anatomical parcellation of the human STN into three anatomical zones within normal diagnostic scan times, which has important future implications for deep brain stimulation surgery

Parcellation of the human substantia nigra based on anatomical connectivity to the striatum

Substantia nigra/ventral tegmental area (SN/VTA) subregions, defined by dopaminergic projections to the striatum, are differentially affected by health (e.g. normal aging) and disease (e.g. Parkinson's disease). This may have an impact on reward processing which relies on dopaminergic regions and circuits. We acquired diffusion tensor imaging (DTI) with probabilistic tractography in 30 healthy older adults to determine whether subregions of the SN/VTA could be delineated based on anatomical connectivity to the striatum. We found that a dorsomedial region of the SN/VTA preferentially connected to the ventral striatum whereas a more ventrolateral region connected to the dorsal striatum. These SN/VTA subregions could be characterised by differences in quantitative structural imaging parameters, suggesting different underlying tissue properties. We also observed that these connectivity patterns differentially mapped onto reward dependence personality trait. We show that tractography can be used to parcellate the SN/VTA into anatomically plausible and behaviourally meaningful compartments, an approach that may help future studies to provide a more fine-grained synopsis of pathological changes in the dopaminergic midbrain and their functional impact

Neuroimaging biomarkers associated with clinical dysfunction in Parkinson disease

Parkinson disease (PD) is the second most common neurodegenerative disorder in the world, directly affecting 2-3% of the population over the age of 65. People diagnosed with the disorder can experience motor, autonomic, cognitive, sensory and neuropsychiatric symptoms that can significantly impact quality of life. Uncertainty still exists about the pathophysiological mechanisms that underlie a range of clinical features of the disorder, linked to structural as well as functional brain changes. This thesis thus aimed to uncover neuroimaging biomarkers associated with clinical dysfunction in PD. A 'hubs-and-spokes' neural circuit-based approach can contribute to this aim, by analysing the component elements and also the interconnections of important brain networks. This thesis focusses on structures within basal ganglia-thalamocortical neuronal circuits that are linked to a range functions impacted in the disorder, and that are vulnerable to the consequences of PD pathology. This thesis investigated neuronal 'hubs' by studying the morphology of the caudate nucleus, putamen, thalamus and neocortex. The caudate nucleus, putamen and thalamus are all vital subcortical 'hubs' that play important roles in a number of functional domains that are compromised in PD. The neocortex, on the other hand, has a range of 'hubs' spread across it, regions of the brain that are crucial for neuronal signalling and communication. The interconnections, or 'spokes', between these hubs and other brain regions were investigated using seed-based resting-state functional connectivity analyses. Finally, a morphological analysis was used to investigate possible structural changes to the corpus callosum, the major inter-hemispheric white matter tract of the brain, crucial to effective higher-order brain processes. This thesis demonstrates that the caudate nucleus, putamen, thalamus, corpus callosum and neocortex are all atrophied in PD participants with dementia. PD participants also demonstrated a significant correlation between volumes of the caudate nuclei and general cognitive functioning and speed, while putamina volumes were correlated with general motor function. Cognitively unimpaired PD participants demonstrated minimal morphological alterations compared to control participants, however they demonstrated significant increases in functional connectivity of the caudate nucleus, putamen and thalamus with areas across the frontal lobe, and decreases in functional connectivity with parietal and cerebellar regions. PD participants with mild cognitive impairment and dementia show decreased functional connectivity of the thalamus with paracingulate and posterior cingulate cortices, respectively. This thesis contributes a deeper understanding of the relationship between structures of basal ganglia-thalamocortical neuronal circuits, corpus callosal and neocortical morphology, and the clinical dysfunction associated with PD. This thesis suggests that functional connectivity changes are more common in early stages of the disorder, while morphological alterations are more pronounced in advanced disease stages

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Department of Biomedical EngineeringIn the brain, iron is an essential element in oxygen supply through blood vessels, energy metabolism, myelin formation, and neurotransmitter synthesis for brain development with maintaining homeostasis. However, even in healthy people, as they grow older, iron levels increase steadily in some regions of the brain. Among the inevitable iron deposits with aging, the unbound labile iron generates reactive oxygen and free radicals, which produce stress on the brain tissue and necrosis of cells, which are closely associated with neurodegenerative diseases. These finally promote neurodegenerative diseases, including Parkinson???s disease and Alzheimer???s disease, which accompany the damage in behavior and cognitive function. Therefore, developing magnetic resonance imaging-based biomarkers to detect various iron clusters deposited in the brain is crucial work for diagnosing and monitoring related diseases. However, it???s still impossible to classify the states of iron and separate the various forms of iron deposited in the brain. The aim of this study was to develop multi-color iron magnetic resonance imaging and the investigation of its in vivo feasibility through translation research from the preclinical trials including postmortem magnetic resonance imaging with histopathological validation to clinical application. In the first section, it was discovered that the neuromelanin pigment within the human substantia nigra is only sensitive to T2* than other magnetic resonance contrast due to its paramagnetic property. Subsequently, the technique for specific visualization of neuromelanin-iron clusters in postmortem substantia nigra tissue was developed using combined T2 and T2* (T2*/T2 or T2*/T22) with histopathological validation supported by the Monte Carlo simulation. Separate segmentations of the areas of iron detected in the T2 map and neuromelanin observed in the T2*/T2 map (or T2*/T22 map) were available within the substantia nigra. The dorsal linear mismatch of T2 and T2* was consistently detected in the brains of healthy controls. However, it was shortened in the diseased brains. In vivo feasibility and implication of developed technique as a clinical biomarker were quantitatively demonstrated in the patients of Parkinson???s disease compared to healthy subjects. In the second section, the iron deposition along the myelinated fiber of white matter was identified in the diseased brains. The iron-rich white matter at the frontal subcortical area contributes to the positive susceptibility in the patients of Adult-onset leukoencephalopathy with axonal spheroids and pigmented glia. Susceptibility-weighted imaging presented the noticeable phase signal showing the tree-like structure in the white matter of the frontal brain, with striking atrophy. This kind of rare tissue contrast in susceptibility-weighted imaging can aid to define Adult-onset leukoencephalopathy with axonal spheroids and pigmented glia. Besides, the deposited iron was verified on the myelinated fibers of the 3rd cranial nerve, which is the oculomotor nerve within the brain of progressive supranuclear palsy. Our results demonstrated the enhanced magnetic resonance susceptibility value between the area of substantia nigra and red nucleus shown in the brain of progressive supranuclear palsy derives from exaggerated iron concentration on the myelinated fibers of the nerves between two structures. In conclusion, the developed techniques of multi-color iron magnetic resonance imaging in this thesis can be useful imaging biomarkers to evaluate the progressive change of several iron-related neurodegenerative diseases, such as Perry syndrome, progressive supranuclear palsy, Parkinson???s disease, and Adult-onset leukoencephalopathy with axonal spheroids and pigmented glia. The advanced research will be implemented to validate the alteration of magnetic resonance signal with the presence of iron molecules chelated to beta-amyloid or tau with Alzheimer???s disease progression.ope