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Diffusion magnetic resonance imaging (dmri) is a technique that can be used to examine the diffusion characteristics of water in the living brain. A recently developed application of this technique is tractography, in which information from brain images obtained using dmri is used to reconstruct the pathways which connect regions of the brain together. Proxy measures for the integrity, or coherence, of these pathways have also been defined using dmri-derived information. The disconnection hypothesis suggests that specific neurological impairments can arise from damage to these pathways as a consequence of the resulting interruption of information flow between relevant areas of cortex. The development of dmri and tractography have generated a considerable amount of renewed interest in the disconnectionist thesis, since they promise a means for testing the hypothesis in vivo in any number of pathological scenarios. However, in order to investigate the effects of pathology on particular pathways, it is necessary to be able to reliably locate them in three-dimensional dmri images. The aim of the work described in this thesis is to improve upon the robustness of existing methods for segmenting specific white matter tracts from image data, using tractography, and to demonstrate the utility of the novel methods for the comparative analysis of white matter integrity in groups of subjects. The thesis begins with an overview of probability theory, which will be a recurring theme throughout what follows, and its application to machine learning. After reviewing the principles of magnetic resonance in general, and dmri and tractography in particular, we then describe existing methods for segmenting particular tracts from group data, and introduce a novel approach. Our innovation is to use a reference tract to define the topological characteristics of the tract of interest, and then search a group of candidate tracts in the target brain volume for the best match to this reference. In order to assess how well two tracts match we define a heuristic but quantitative tract similarity measure. In later chapters we demonstrate that this method is capable of successfully segmenting tracts of interest in both young and old, healthy and unhealthy brains; and then describe a formalised version of the approach which uses machine learning methods to match tracts from different subjects. In this case the similarity between tracts is represented as a matching probability under an explicit model of topological variability between equivalent tracts in different brains. Finally, we examine the possibility of comparing the integrity of groups of white matter structures at a level more fine-grained than a whole tract.

Introduction: Schizotypy is a personality trait that shares some of the characteristics of clinical disorders such as schizophrenia. Similarities are found in expression of psychotic-like experiences and presence of attenuated negative signs. Furthermore, schizotypal samples are associated with impairments in cognitive tasks, albeit in a less comprised form. For these reasons and others, schizotypy is considered a part of the extended-phenotype of schizophrenia and as such can be utilised as an analogue sample without some of theconfounds associated with illness. Objective: The aim of the PhD is to examine the relationship of schizotypal features and brain function and structure in a sample of adolescents and young adults (age 16-25 years). This will attempt to provide further evidence for the placement of schizotypy on the continuum, along with insights into pathophysiological mechanisms involved in schizophrenia and related disorders. Methods: The study involved three main phases: recruitment via an online survey, further neuropsychological testing and brain imaging on selected high schizotypes and controls. The thesis comprises 5 papers/experiments. Paper 1 utilises confirmatory factor analysis (CFA) to examine the factorial structure of the schizotypal personality questionnaire (SPQ) in a community sample aged 16-25 years. It also examined the effects of demographics on schizotypal levels. Paper 2 examined the association between schizotypy and measures of sustained attention and spatial working memory both in a total sample, and in samples split by age and by sex. Paper 3 further examined the association between schizotypy and cognition laboratory tests of attention, executive function and verbal learning/memory. Paper 4 tested the same participants on measures of functional brain asymmetry. Paper 5 used diffusion tensor imaging (DTI) to examine white matter structures in a sample of high schizotypes and controls. Results: Paper 1 confirmed that the SPQ is most appropriately modelled by a four-factor structure in an adolescent and young adult sample. Demographic effects on SPQ subscales scores mirrored those seen in clinical samples. Paper 2 found that where small associations between schizotypy and sustained attention/spatial working memory function occurred, these were in relation to either age of sex. Paper 3 demonstrated an association between increased schizotypal features and a slight reduction in performance on verbal learning/memory, but no association with tasks of executive function or attention. In Paper 4, schizotypy was associated with a left-hemifield bias on a computerised line bisection task. Paper 5 found that a group of high schizotypes had an increase in tract coherence in the uncinate fasciculus compared to controls. Furthermore, increasing subclinical hallucinatory experiences were associated with increased tract coherence in the right hemisphere arcuate fasciculus. Conclusions: Schizotypy was associated with changes in brain function and structure similar to that demonstrated in more serious mental illness, although to a lesser degree. The current studies suggested that schizotypy is associated with relatively intact prefrontal function, but slight performance bias on measures of medial temporal lobe function. There was also evidence for structural brain changes in schizotypes, with these being indicative of either a protective factor, or a marker of a pathological process. Correlations between hallucinatory experiences and white matter tracts between language regions support theories implicating hyperconnectivity and presentation of symptoms in clinical groups. The functional and structural data collected from this study suggests that the ‘schizotypal’ brain may represent an ‘early’ stage of pathology, but which is likely to be compensated enough such that transition to serious mental illness is unlikely. Further studies could examine similarities and differences between the schizotypal profile and clinical conditions, which would provide further insights into aetiological mechanisms in schizophrenia/psychosis.

Diffusion Tensor Magnetic Resonance Imaging (DTI) is a recently-developed technique that can image in vivo the white matter pathways of the central nervous system. This study used 12-direction diffusion-weighted MRI data from nine stroke patients acquired as part of a three-year stroke rehabilitation study coordinated by the Movement Neuroscience Laboratory at the University of Auckland. DTI was used to investigate corticospinal connectivity. From the FA maps, it is found that in those patients whose motor connectivity has been compromised by the stroke to the extent that no motor evoked potential (MEP) can be elicited from a selected affected muscle group, the asymmetry in mean FA values in the posterior limbs of the internal capsules (PLICs) is correlated with functional recovery as measured by the Fugl-Meyer clinical score. Using probabilistic tractography in the contralesional hemisphere produced CST location and somatotopy results that were consistent with those of previous studies. However, in the ipsilesional hemisphere, connectivity results were highly variable. A measure of change in symmetry of mean connectivity is found to correlate with functional recovery as measured by change in FM score. This supports previous work which has correlated CST integrity and functional improvement and it supports the theory that functional recovery after stroke depends on the extent to which motor CNS symmetry can be regained in the new post-stroke architecture. It also suggests that the movement of the fMRI activations occurs in such a way as to make the most of the preserved white matter connectivity.

Diffusion Tensor Magnetic Resonance Imaging (DTI) is a recently-developed technique that can image in vivo the white matter pathways of the central nervous system. This study used 12-direction diffusion-weighted MRI data from nine stroke patients acquired as part of a three-year stroke rehabilitation study coordinated by the Movement Neuroscience Laboratory at the University of Auckland. DTI was used to investigate corticospinal connectivity. From the FA maps, it is found that in those patients whose motor connectivity has been compromised by the stroke to the extent that no motor evoked potential (MEP) can be elicited from a selected affected muscle group, the asymmetry in mean FA values in the posterior limbs of the internal capsules (PLICs) is correlated with functional recovery as measured by the Fugl-Meyer clinical score. Using probabilistic tractography in the contralesional hemisphere produced CST location and somatotopy results that were consistent with those of previous studies. However, in the ipsilesional hemisphere, connectivity results were highly variable. A measure of change in symmetry of mean connectivity is found to correlate with functional recovery as measured by change in FM score. This supports previous work which has correlated CST integrity and functional improvement and it supports the theory that functional recovery after stroke depends on the extent to which motor CNS symmetry can be regained in the new post-stroke architecture. It also suggests that the movement of the fMRI activations occurs in such a way as to make the most of the preserved white matter connectivity.

Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第17572号 / 工博第3731号 / 新制||工||1569(附属図書館) / 30338 / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 小林 哲生, 教授 土居 伸二, 教授 山川 宏 / 学位規則第4条第1項該当

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第20262号 / 医博第4221号 / 新制||医||1020(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 伊佐 正, 教授 松原 和夫, 教授 村井 俊哉 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(文学) / 甲第20828号 / 文博第758号 / 新制||文||655(附属図書館) / 京都大学大学院文学研究科行動文化学専攻 / (主査)教授 蘆田 宏, 教授 板倉 昭二, 教授 Anderson James Russell, 准教授 ALTMANN Christian / 学位規則第4条第1項該当 / Doctor of Letters / Kyoto University / DFAM

No description available.

Tractography is widely used in the brain connectivity study from diffusion magnetic resonance imaging data. However, lack of ground truth and plenty of anatomically implausible streamlines in the tractograms have caused challenges and concerns in the use of tractograms such as brain connectivity study. Tractogram filtering methods have been developed to remove the faulty connections. In this study, we focus on one of these filtering methods, Convex Optimization Modeling for Microstructure Informed Tractography (COMMIT), which tries to find a set of streamlines that best reconstruct the diffusion magnetic resonance imaging data with global optimization approach. There are biases with this method when assessing individual streamlines. So a method named randomized COMMIT(rCOMMIT) is proposed to obtain multiple assessments for each streamline. The acceptance rate from this method is introduced to the streamlines and divides them into three groups, which are regarded as pseudo ground truth from rCOMMIT. Therefore, the neural networks are able to train on the pseudo ground truth on classification tasks. The trained classifiers distinguish the obtained groups of plausible and implausible streamlines with accuracy around 77%. Following the same methodology, the results from rCOMMIT and randomized SIFT are compared. The intersections between two methods are analyzed with neural networks as well, which achieve accuracy around 87% in binary task between plausible and implausible streamlines.