Development of a tool for automatic segmentation of the cerebellum in MR images of children

The human cerebellar cortex is a highly foliated structure that supports both motor and complex cognitive functions in humans. Magnetic Resonance Imaging (MRI) is commonly used to explore structural alterations in patients with psychiatric and neurological diseases. The ability to detect regional structural differences in cerebellar lobules may provide valuable insights into disease biology, progression and response to treatment, but has been hampered by the lack of appropriate tools for performing automated structural cerebellar segmentation and morphometry. In this thesis, time intensive manual tracings by an expert neuroanatomist of 16 cerebellar regions on high-resolution T1-weighted MR images of 18 children aged 9-13 years were used to generate the Cape Town Pediatric Cerebellar Atlas (CAPCA18) in the age-appropriate National Institute of Health Pediatric Database (NIHPD) asymmetric template space. An automated pipeline was developed to process the MR images and generate lobule-wise segmentations, as well as a measure of the uncertainty of the label assignments. Validation in an independent group of children with ages similar to those of the children used in the construction of the atlas, yielded spatial overlaps with manual segmentations greater than 70% in all lobules, except lobules VIIb and X. Average spatial overlap of the whole cerebellar cortex was 86%, compared to 78% using the alternative Spatially Unbiased Infra-tentorial Template (SUIT), which was developed using adult images

Heschl's gyrus is more sensitive to tone level than non-primary auditory cortex

Previous neuroimaging studies generally demonstrate a growth in the cortical response with an increase in sound level. However, the details of the shape and topographic location of such growth remain largely unknown. One limiting methodological factor has been the relatively sparse sampling of sound intensities. Additionally, most studies have either analysed the entire auditory cortex without differentiating primary and non-primary regions or have limited their analyses to Heschl's gyrus (HG). Here, we characterise the pattern of responses to a 300-Hz tone presented in 6-dB steps from 42 to 96 dB sound pressure level as a function of its sound level, within three anatomically defined auditory areas; the primary area, on HG, and two non-primary areas, consisting of a small area lateral to the axis of HG (the anterior lateral area, ALA) and the posterior part of auditory cortex (the planum temporale, PT). Extent and magnitude of auditory activation increased non-linearly with sound level. In HG, the extent and magnitude were more sensitive to increasing level than in ALA and PT. Thus, HG appears to have a larger involvement in sound-level processing than does ALA or PT

Three-Dimensional Atlas System for Mouse and Rat Brain Imaging Data

Tomographic neuroimaging techniques allow visualization of functionally and structurally specific signals in the mouse and rat brain. The interpretation of the image data relies on accurate determination of anatomical location, which is frequently obstructed by the lack of structural information in the data sets. Positron emission tomography (PET) generally yields images with low spatial resolution and little structural contrast, and many experimental magnetic resonance imaging (MRI) paradigms give specific signal enhancements but often limited anatomical information. Side-by-side comparison of image data with conventional atlas diagram is hampered by the 2-D format of the atlases, and by the lack of an analytical environment for accumulation of data and integrative analyses. We here present a method for reconstructing 3-D atlases from digital 2-D atlas diagrams, and exemplify 3-D atlas-based analysis of PET and MRI data. The reconstruction procedure is based on two seminal mouse and brain atlases, but is applicable to any stereotaxic atlas. Currently, 30 mouse brain structures and 60 rat brain structures have been reconstructed. To exploit the 3-D atlas models, we have developed a multi-platform atlas tool (available via The Rodent Workbench, http://rbwb.org) which allows combined visualization of experimental image data within the 3-D atlas space together with 3-D viewing and user-defined slicing of selected atlas structures. The tool presented facilitates assignment of location and comparative analysis of signal location in tomographic images with low structural contrast

A Longitudinal Study of Closed Head Injury: Neuropsychological Outcome and Structural Analysis using Region of Interest Measurements and Voxel-Based Morphometry

Background: The hippocampus and corpus callosum have been shown to be vulnerable in head injury. Various neuroimaging modalities and quantitative measurement techniques have been employed to investigate pathological changes in these structures. Cognitive and behavioural deficiencies have also been well documented in head injury. Aims: The aim of this research project was to investigate structural changes in the hippocampus and corpus callosum. Two different quantitative methods were used to measure physical changes and neuropsychological assessment was performed to determine cognitive and behavioural deficit. It was also intended to investigate the relationship between structural change and neuropsychology at 1 and 6 months post injury. Method: Forty-seven patients with head injury (ranging from mild to severe) had undergone a battery of neuropsychological tests and an MRI scan at 1 and 6 months post injury. T1-weighted MRI scans were obtained and analysis of hippocampus and corpus callosum was performed using region-of-interest techniques and voxel-based morphometry which also included comparison to 18 healthy volunteers. The patients completed neuropsychological assessment at 1 and 6 months post injury and data obtained was analysed with respect to each assessment and with structural data to determine cognitive decline and correlation with neuroanatomy. Results: Voxel-based morphometry illustrated reduced whole scan signal differences between patients and controls and changes in patients between 1 and 6 months post injury. Reduced grey matter concentration was also found using voxel-based morphometry and segmented images between patients and controls. A number of neuropsychological aspects were related to injury severity and correlations with neuroanatomy were present. Voxel-based morphometry provided a greater number of associations than region-of-interest analysis. No longitudinal changes were found in the hippocampus or corpus callosum using region-of-interest methodology or voxel-based morphometry. Conclusions: Decreased grey matter concentration identified with voxel-based morphometry illustrated that structural deficit was present in the head injured patients and does not change between 1 and 6 months. Voxel-based morphometry appears more sensitive for detecting structural changes after head injury than region- of-interest methods. Although the majority of patients had suffered mild head injury, cognitive and neurobehavioural deficits were evidenced by a substantial number of patients reporting increased anxiety and depression levels. Also, the findings of relationships between reduced grey matter concentration and cognitive test scores are indicative of the effects of diffuse brain damage in the patient group

The natverse, a versatile toolbox for combining and analysing neuroanatomical data.

To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open-source R packages called the natverse. The natverse allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community

Magnetic Resonance Imaging in Huntington's Disease.

Magnetic resonance imaging (MRI) is a noninvasive technique used routinely to image the body in both clinical and research settings. Through the manipulation of radio waves and static field gradients, MRI uses the principle of nuclear magnetic resonance to produce images with high spatial resolution, appropriate for the investigation of brain structure and function

An in vivo MRI Template Set for Morphometry, Tissue Segmentation, and fMRI Localization in Rats

Over the last decade, several papers have focused on the construction of highly detailed mouse high field magnetic resonance image (MRI) templates via non-linear registration to unbiased reference spaces, allowing for a variety of neuroimaging applications such as robust morphometric analyses. However, work in rats has only provided medium field MRI averages based on linear registration to biased spaces with the sole purpose of approximate functional MRI (fMRI) localization. This precludes any morphometric analysis in spite of the need of exploring in detail the neuroanatomical substrates of diseases in a recent advent of rat models. In this paper we present a new in vivo rat T2 MRI template set, comprising average images of both intensity and shape, obtained via non-linear registration. Also, unlike previous rat template sets, we include white and gray matter probabilistic segmentations, expanding its use to those applications demanding prior-based tissue segmentation, e.g., statistical parametric mapping (SPM) voxel-based morphometry. We also provide a preliminary digitalization of latest Paxinos and Watson atlas for anatomical and functional interpretations within the cerebral cortex. We confirmed that, like with previous templates, forepaw and hindpaw fMRI activations can be correctly localized in the expected atlas structure. To exemplify the use of our new MRI template set, were reported the volumes of brain tissues and cortical structures and probed their relationships with ontogenetic development. Other in vivo applications in the near future can be tensor-, deformation-, or voxel-based morphometry, morphological connectivity, and diffusion tensor-based anatomical connectivity. Our template set, freely available through the SPM extension website, could be an important tool for future longitudinal and/or functional extensive preclinical studies

Multimodal Investigation of Brain Network Systems: From Brain Structure and Function to Connectivity and Neuromodulation

The field of cognitive neuroscience has benefited greatly from multimodal investigations of the human brain, which integrate various tools and neuroimaging data to understand brain functions and guide treatments for brain disorders. In this dissertation, we present a series of studies that illustrate the use of multimodal approaches to investigate brain structure and function, brain connectivity, and neuromodulation effects. Firstly, we propose a novel landmark-guided region-based spatial normalization technique to accurately quantify brain morphology, which can improve the sensitivity and specificity of functional imaging studies. Subsequently, we shift the investigation to the characteristics of functional brain activity due to visual stimulations. Our findings reveal that the task-evoked positive blood-oxygen-level dependent (BOLD) response is accompanied by sustained negative BOLD responses in the visual cortex. These negative BOLD responses are likely generated through subcortical neuromodulatory systems with distributed ascending projections to the cortex. To further explore the cortico-subcortical relationship, we conduct a multimodal investigation that involves simultaneous data acquisition of pupillometry, electroencephalography (EEG), and functional magnetic resonance imaging (fMRI). This investigation aims to examine the connectivity of brain circuits involved in the cognitive processes of salient stimuli. Using pupillary response as a surrogate measure of activity in the locus coeruleus-norepinephrine system, we find that the pupillary response is associated with the reorganization of functional brain networks during salience processing. In addition, we propose a cortico-subcortical integrated network reorganization model with potential implications for understanding attentional processing and network switching. Lastly, we employ a multimodal investigation that involves concurrent transcranial magnetic stimulation (TMS), EEG, and fMRI to explore network perturbations and measurements of the propagation effects. In a preliminary exploration on brain-state dependency of TMS-induced effects, we find that the propagation of left dorsolateral prefrontal cortex TMS to regions in the lateral frontoparietal network might depend on the brain-state, as indexed by the EEG prefrontal alpha phase. Overall, the studies in this dissertation contribute to the understanding of the structural and functional characteristics of brain network systems, and may inform future investigations that use multimodal methodological approaches, such as pupillometry, brain connectivity, and neuromodulation tools. The work presented in this dissertation has potential implications for the development of efficient and personalized treatments for major depressive disorder, attention deficit hyperactivity disorder, and Alzheimer's disease