Detection of Postmortem Human Cerebellar Cortex and White Matter Pathways Using High Angular Resolution Diffusion Tractography: A feasibility study.
ABSTRACT Imaging three-dimensional cerebellar connectivity using diffusion tractography is challenging because of the ubiquitous features of crossing axonal pathways within a folium as well as intersecting pathways from neighboring folia. We applied high-angular resolution diffusion imaging (HARDI) tractography to intact postmortem adult brainstem and cerebellum to examine the 3-dimensional white matter and local gray matter pathways. The middle cerebellar peduncles conveyed fibers from the rostral pons to the lateral and caudal aspects of the cerebellar hemisphere, and from the caudal pons to medial and rostral parts of the cerebellar hemisphere. In the cerebellar cortex, tractography detected tangential coherence superficially in the cerebellar cortex and revealed fibers coursing parallel to the long axis of the folia. These fibers were consistent with the location and direction of parallel fibers in the molecular layer. Crossing with these parallel fibers were tangential fibers running perpendicular to the long axis of the folia, consistent with axons othe cortical interneurons - stellate cells and basket cells. These tangential fibers within the cerebellar cortex were distinct from fibers linking the cerebellar cortex with the deep cerebellar nuclei and the brainstem. Our results show the potential for HARDI tractography to resolve axonal pathways from different neuronal elements within the cerebellar cortex, and improve our understanding of adult cerebellar neural circuitry and connectivity in both white and gray matter.
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ABSTRACT: Connectome is a term with a short history but a long past. Since the origins of neuroscience the concept of a 'map of neural connections' has been a constant inspiring idea for those who believed the brain as the organ of intellect. A myriad of protoconnectome maps have been produced throughout the centuries, each one reflecting the theory and method of investigation that prevailed at the time. Even contemporary definitions of the connectome rest upon the formulation of a neuronal theory that has been proposed over a hundred years ago. So, what is new? In this article we attempt to trace the development of certain anatomical and physiological concepts at the origins of modern definitions of the connectome. We argue that compared to previous attempts current connectomic approaches benefit from a wealth of imaging methods that in part could justify the enthusiasm for finally succeeding in achieving the goal. One of the unique advantages of contemporary approaches is the possibility of using quantitative methods to define measures of connectivity where structure, function and behaviour are integrated and correlated. We also argue that many contemporary maps are inaccurate surrogates of the true anatomy and a comprehensive connectome of the human brain remains a far distant point in the history to come.NeuroImage 06/2013; 80. DOI:10.1016/j.neuroimage.2013.05.109 · 6.36 Impact Factor
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ABSTRACT: Abnormal white matter development in patients with tuberous sclerosis complex, a multisystem hamartomatous disorder caused by aberrant neural proliferation and axonal maturation, may be associated with poorer neurocognitive outcomes. The purpose of this study is to identify predictors of longitudinal changes in diffusion properties of white matter tracts in patients with tuberous sclerosis complex. Diffusion magnetic resonance imaging was carried out in 17 subjects with tuberous sclerosis complex (mean age, 7.2 ± 4.4 years) with at least two magnetic resonance imaging scans (mean number of days between scans, 419.4 ± 105.4). There were 10 males; 5 of 17 had autism spectrum disorder and 10 of 17 had epilepsy. Regions of interest were placed to delineate the internal capsule/corona radiata, cingulum, and corpus callosum. The outcomes were mean change in apparent diffusion coefficient and fractional anisotropy. Data were analyzed using Pearson's correlation and multiple linear regression analyses. Gender was a significant predictor of mean change in apparent diffusion coefficient in the left internal capsule, right and left cingulum bundles, and corpus callosum and a significant predictor of mean change in fractional anisotropy in the corpus callosum. Epilepsy was a significant predictor of mean change in apparent diffusion coefficient in the left internal capsule. Autism spectrum disorder was not predictive of diffusion changes in any of the studied pathways. Clinical variables, including gender and epilepsy, have an effect on the development of white matter pathways. These variables should be taken into consideration when counseling tuberous sclerosis complex patients and in future imaging studies in this population. Copyright © 2015 Elsevier Inc. All rights reserved.Radiological Society of North America 2013 Scientific Assembly and Annual Meeting; 12/2013
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ABSTRACT: High-resolution diffusion MRI (dMRI) is useful for resolving complex microstructures in the mouse brain, but technically challenging for in vivo studies due to the long scan time. In this study, selective excitation and a three-dimensional fast imaging sequence were used to achieve in vivo high-resolution dMRI of the mouse brain at 11.7Tesla. By reducing the field of view using spatially selective radio frequency pulses, we were able to focus on targeted brain structures and acquire high angular resolution diffusion imaging (HARDI) data at an isotropic resolution of 0.1mm and 30 diffusion encoding directions in approximately one hour. We investigated the complex tissue microstructures of the mouse hippocampus, cerebellum, and several cortical areas using this localized dMRI approach, and compared the results with histological sections stained with several axonal and dendritic markers. In the mouse visual cortex, the results showed predominately radially arranged structures in an outer layer and tangentially arranged structures in an inner layer, similar to observations from postmortem human brain specimens.NeuroImage 01/2014; 91. DOI:10.1016/j.neuroimage.2014.01.014 · 6.36 Impact Factor