Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Images

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel regression is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. Unlike many previous partial differential equation based approaches involving diffusion, our approach represents the solution of diffusion analytically, reducing numerical inaccuracy and slow convergence. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, we have applied the method in characterizing the localized growth pattern of mandible surfaces obtained in CT images from subjects between ages 0 and 20 years by regressing the length of displacement vectors with respect to the template surface.Comment: Accepted in Medical Image Analysi

Abnormal Brain Activation in Neurofibromatosis Type 1: A Link between Visual Processing and the Default Mode Network

Neurofibromatosis type 1 (NF1) is one of the most common single gene disorders affecting the human nervous system with a high incidence of cognitive deficits, particularly visuospatial. Nevertheless, neurophysiological alterations in low-level visual processing that could be relevant to explain the cognitive phenotype are poorly understood. Here we used functional magnetic resonance imaging (fMRI) to study early cortical visual pathways in children and adults with NF1. We employed two distinct stimulus types differing in contrast and spatial and temporal frequencies to evoke relatively different activation of the magnocellular (M) and parvocellular (P) pathways. Hemodynamic responses were investigated in retinotopically-defined regions V1, V2 and V3 and then over the acquired cortical volume. Relative to matched control subjects, patients with NF1 showed deficient activation of the low-level visual cortex to both stimulus types. Importantly, this finding was observed for children and adults with NF1, indicating that low-level visual processing deficits do not ameliorate with age. Moreover, only during M-biased stimulation patients with NF1 failed to deactivate or even activated anterior and posterior midline regions of the default mode network. The observation that the magnocellular visual pathway is impaired in NF1 in early visual processing and is specifically associated with a deficient deactivation of the default mode network may provide a neural explanation for high-order cognitive deficits present in NF1, particularly visuospatial and attentional. A link between magnocellular and default mode network processing may generalize to neuropsychiatric disorders where such deficits have been separately identified

Age differences in the motor control of speech : an fMRI study of healthy aging

Healthy aging is associated with a decline in cognitive, executive, and motor processes that are concomitant with changes in brain activation patterns, particularly at high complexity levels. While speech production relies on all these processes, and is known to decline with age, the mechanisms that underlie these changes remain poorly understood, despite the importance of communication on everyday life. In this cross‐sectional group study, we investigated age differences in the neuromotor control of speech production by combining behavioral and functional magnetic resonance imaging (fMRI) data. Twenty‐seven healthy adults underwent fMRI while performing a speech production task consisting in the articulation of nonwords of different sequential and motor complexity. Results demonstrate strong age differences in movement time (MT), with longer and more variable MT in older adults. The fMRI results revealed extensive age differences in the relationship between BOLD signal and MT, within and outside the sensorimotor system. Moreover, age differences were also found in relation to sequential complexity within the motor and attentional systems, reflecting both compensatory and de‐differentiation mechanisms. At very high complexity level (high motor complexity and high sequence complexity), age differences were found in both MT data and BOLD response, which increased in several sensorimotor and executive control areas. Together, these results suggest that aging of motor and executive control mechanisms may contribute to age differences in speech production. These findings highlight the importance of studying functionally relevant behavior such as speech to understand the mechanisms of human brain aging

Spatial accuracy of fMRI activation influenced by volume- and surface-based spatial smoothing techniques

As improvements in cortical surface modeling allowed accurate cortical topology in brain imaging studies, surface-based methods for the analysis of functional magnetic resonance imaging (fMRI) were introduced to overcome the topological deficiency of commonly used volume-based methods. The difference between the two methods is mainly due to the smoothing techniques applied. For practical applications, the surface-based methods need to quantitatively validate the accuracy of localizing activation. In this study, we evaluated the spatial accuracy of activation detected by the volume- and surface-based methods using simulated blood oxygenation level-dependent (BOLD) signals and MRI phantoms focusing on the influence of their smoothing techniques. T1- and T2-weighted phantoms were acquired from BrainWeb () and used to extract cortical surfaces and to generate echo planar imaging (EPI) data. Simulated BOLD signals as the gold standard of activation in our experiment were applied to the surfaces and projected to the volume space with random noise. Three-dimensional isotropic Gaussian kernel smoothing and two-dimensional heat kernel smoothing were applied to the volume- and surface-based methods. Sensitivity and 1-specificity, which are truly and falsely detected activations, and similarity measures, which are spatially and statistically similar for the gold standard and detected activations, were calculated. In the results, the surface-based method showed the sensitivity and similarity scores of about 12% higher than the volume-based method. In conclusion, the surface-based method guarantees better spatial accuracy for the localization of BOLD signal sources within the cortex than the volume-based method

Brain encoding of saltatory velocity-scaled somatosensory array in glabrous hand among neurotypical adults

Neurons in human somatosensory cortex are somatotopically organized, with sensation from the lower limbs mediated by neurons near the midline of the brain, whereas sensations from the upper body, hands and orofacial surfaces are mediated by neurons located more laterally in a sequential map. Neurons in Brodmann\u27s area (BA) 3b are exquisitely sensitive to tactile stimulation of these skin surfaces. Moreover, the location, velocity and direction of tactile stimuli on the skin\u27s surface are discriminable features of somatosensory processing, however their role in fine motor control and passive detection are poorly understood in health, and as a neurotherapeutic agent in sensorimotor rehabilitation. To better understand the representation and processing of dynamic saltatory tactile arrays in the human somatosensory cortex, high resolution functional magnetic resonance (fMRI) is utilized to delineate neural networks involved in processing these complex somatosensory events to the glabrous surface of the hand. The principal goal of this dissertation is to map the relation between a dynamic saltatory pneumatic stimulus array delivered at 3 different velocities on the glabrous hand and the evoked blood-oxygen level-dependent (BOLD) brain response, hypothesized to involve a network consisting of primary and secondary somatosensory cortices (S1 and S2), insular cortex, posterior parietal cortex (PPC), and cerebellar nuclei. A random-balanced block design with fMRI will be used to record the BOLD response in healthy right-handed adults. Development of precise stimulus velocities, rapid rise-fall transitions, salient amplitude, is expected to optimize the BOLD response. Advisor: Steven M. Barlo

Assessment of the potentials and limitations of cortical-based analysis for the integration of structure and function in normal and pathological brains using MRI

The software package Brainvisa (www.brainvisa.tnfo) offers a wide range of possibilities for cortical analysis using its automatic sulci recognition feature. Automated sulci identification is an attractive feature as the manual labelling of the cortical sulci is often challenging even for the experienced neuro-radiologists. This can also be of interest in fMRI studies of individual subjects where activated regions of the cortex can simply be identified using sulcal labels without the need for normalization to an atlas. As it will be explained later in this thesis, normalization to atlas can especially be problematic for pathologic brains. In addition, Brainvisa allows for sulcal morphometry from structural MR images by estimating a wide range of sulcal properties such as size, coordinates, direction, and pattern. Morphometry of abnormal brains has gained huge interest and has been widely used in finding the biomarkers of several neurological diseases or psychiatric disorders. However mainly because of its complexity, only a limited use of sulcal morphometry has been reported so far. With a wide range of possibilities for sulcal morphometry offered by Brainvisa, it is possible to thoroughly investigate the sulcal changes due to the abnormality. However, as any other automated method, Brainvisa can be susceptible to limitations associated with image quality. Factors such as noise, spatial resolution, and so on, can have an impact on the detection of the cortical folds and estimation of their attributes. Hence the robustness of Brainvisa needs to be assessed. This can be done by estimating the reliability and reproducibility of results as well as exploring the changes in results caused by other factors. This thesis is an attempt to investigate the possible benefits of sulci identification and sulcal morphometry for functional and structural MRI studies as well as the limitations of Brainvisa. In addition, the possibility of improvement of activation localization with functional MRI studies is further investigated. This investigation was motivated by a review of other cortical-based analysis methods, namely the cortical surface-based methods, which are discussed in the literature review chapter of this thesis. The application of these approaches in functional MRI data analysis and their potential benefits is used in this investigation

Developing advanced MR imaging to assess spinal cord function and tract integrity.

The overall purpose of this thesis is to develop a way to match diffusion and functional acquisition techniques in the spinal cord (SC) in order to offer a comprehensive assessment of factors responsible for functional and structural integrity. I began by optimising a pipeline to acquire and process spinal functional data and I finished by matching the functional information with that derived from diffusion imaging (DI) performed during the same scan session as fM RI. In order to characterize the interactions between local structural connections (derived from DI) and functional activation of the SC it has been necessary to develop an imaging protocol that acquires transverse SC images with both modalities, matching their spatial and geometrical characteristics. This is because transverse cord images possess the relevant anatomical information in terms of grey-white matter structure and allow better localisation of the functional response and structural properties within the spinal cord. My main contribution to the field has been: 1. To demonstrate that it is possible to use the “ZOOM” sequence for spinal fM RI 2. To characterize the signal obtained and the comparison of different image analysis approaches 3. To propose a final pipeline for acquisition and analysis of spinal fM RI 4. To demonstrate that there is a dependency of pathological functional and structural changes The same ZOOM-EPI sequence has been applied for all the functional studies reported in this thesis. The outcome of the optimisation for spinal fMRI has been matched by a DI protocol, using standard DI parameters for spinal microstructural characterization and constitutes the final MR protocol used in a pilot study including a group of healthy controls and a group of patients affected by multiple sclerosis (MS). Based on the gathered experience and results from data acquired and analysed over the years I have concluded with some recommendations for future studies and development strategies for structural and functional MRI of the spinal cor

Evidence for Extreme Cortical Flexibility: Higher Cognitive Functions in "Visual" Cortices of Blind Individuals

Are structure and function inextricably linked in the brain? In the early 19th century, phrenologists endeavored to localize cognition to areas of the brain. Though neuroscientists have updated the methodology and the notion of what constitutes a mental process, the goal remains the same: to map functions to locations. But how flexible are these structure-to- function mappings? Studying adaptations of the “visual” cortex to blindness offers insight on the extent to which brain structures can carry out functions for which they did not evolve. In this dissertation, I ask how flexible visual cortices are in the absence of expected visual information. I examine the ability of blind individuals’ occipital cortices to take on functions that are higher cognitive and, therefore, radically different from vision. First, Chapter 2 explores the extent of higher cognitive takeover of “visual” cortices in blindness. Using naturalistic stimuli, I find that “visual” cortices of blind individuals synchronize to a shared interpretive, rather than a shared perceptual, experience. This suggests systematic and widespread repurposing of “visual” cortices for higher-cognitive functions. Next, Chapter 3 asks whether “visual” cortices of blind individuals are repurposed for higher cognitive functions other than language, and executive functions in particular. I find evidence for executive functions in primarily right-lateralized “visual” cortices using both a non-verbal response-inhibition task and by examining functional connectivity at rest. Finally, Chapter 4 examines the functional relevance of previously observed language and executive function responses in the “visual” cortices of blind individuals. I find that blind individuals are better than matched sighted controls at comprehending syntactically complex sentences and at inhibiting prepotent button pressing. This suggests that repurposed “visual” cortices may confer a behavioral advantage. Taken together, this dissertation demonstrates that “visual” cortices of blind individuals are meaningfully repurposed for higher cognitive functions. Though brain structures may seem particularly suited to implement a particular function, such structure- to-function mappings are not evidence of functional rigidity. In contrast, evidence from blindness suggests that human cortex is highly flexible at birth

Into the Multiverse: Methods for Studying Developmental Neuroscience

One major challenge in developmental neuroscience research is the sheer number of choices researchers face when addressing even a single research question. Even once data collection is complete, the journey from raw data to interpretation of findings may depend on numerous decisions. To address this issue, this dissertation explores “multiverse” analysis techniques for following many analytical paths at once in the same dataset. In chapter 1, multiverses are used to examine which analyses of age-related change in amygdala-medial prefrontal cortex circuitry are robust versus sensitive to researcher decisions. Chapter 2 uses multiverse analysis to identify optimal solutions for mitigating breathing-induced artifacts in resting-state functional magnetic resonance imaging data. Chapter 3 uses a variety of model specifications to characterize simultaneous reward learning strategies in youth contingent on both visual task cues and spatial-motor information. Despite varied approaches and goals, each of the three studies highlight the benefits of conducting multiple parallel analyses for both addressing questions in developmental neuroscience and deepening understanding of the methods used to address them