Front Neuroanat
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The cingulum bundle (CB) is a critical white matter fiber tract in the brain, which forms connections between the frontal lobe, parietal lobe and temporal lobe. In non-human primates, the CB is actually divided into distinct subcomponents on the basis of corticocortical connections. However, at present, no study has verified similar distinct subdivisions in the human brain. ⋯ CB-IV was a relatively minor subcomponent from the SPL and precuneus to the frontal region. CB-V, the para-hippocampal cingulum, stemmed from the medial temporal lobe and fanned out to the occipital lobes. Our findings not only provide a more accurate and detailed description on the associated architecture of the subcomponents within the CB, but also offer new insights into the functional role of the CB in the human brain.
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3D printing is a form of rapid prototyping technology, which has led to innovative new applications in biomedicine. It facilitates the production of highly accurate three dimensional objects from substrate materials. The inherent accuracy and other properties of 3D printing have allowed it to have exciting applications in anatomy education and surgery, with the specialty of neurosurgery having benefited particularly well. ⋯ A number of applications within these fields were found, with many significantly improving the quality of anatomy and surgical education, and the practice of neurosurgery. They also offered advantages over existing approaches and practices. It is envisaged that the number of useful applications will rise in the coming years, particularly as the costs of this technology decrease and its uptake rises.
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The definitive structure and functional role of the inferior fronto-occipital fasciculus (IFOF) are still controversial. In this study, we aimed to investigate the connectivity, asymmetry, and segmentation patterns of this bundle. High angular diffusion spectrum imaging (DSI) analysis was performed on 10 healthy adults and a 90-subject DSI template (NTU-90 Atlas). ⋯ The most common connection patterns of the subcomponents were as follows: IFOF-I, from frontal polar cortex to occipital pole, inferior occipital lobe, middle occipital lobe, superior occipital lobe, and pericalcarine; IFOF-II, from orbito-frontal cortex to occipital pole, inferior occipital lobe, middle occipital lobe, superior occipital lobe, and pericalcarine; IFOF-III, from inferior frontal gyrus to inferior occipital lobe, middle occipital lobe, superior occipital lobe, occipital pole, and pericalcarine; IFOF-IV, from middle frontal gyrus to occipital pole, and inferior occipital lobe; IFOF-V, from superior frontal gyrus to occipital pole, inferior occipital lobe, and middle occipital lobe. Our work demonstrates the feasibility of high resolution diffusion tensor tractography with sufficient sensitivity to elucidate more anatomical details of the IFOF. And we provides a new framework for subdividing the IFOF for better understanding its functional role in the human brain.
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Despite exciting advances in the functional imaging of the brain, it remains a challenge to define regions of interest (ROIs) that do not require investigator supervision and permit examination of change in networks over time (or plasticity). Plasticity is most readily examined by maintaining ROIs constant via seed-based and anatomical-atlas based techniques, but these approaches are not data-driven, requiring definition based on prior experience (e.g., choice of seed-region, anatomical landmarks). These approaches are limiting especially when functional connectivity may evolve over time in areas that are finer than known anatomical landmarks or in areas outside predetermined seeded regions. ⋯ In this paper we propose an approach, aggregate-initialized label propagation (AILP), which allows for data at separate time points to be compared for examining developmental processes resulting in network change (plasticity). To do so, we use a whole-brain modularity approach to parcellate the brain into anatomically constrained functional modules at separate time points and then apply the AILP algorithm to form a consensus set of ROIs for examining change over time. To demonstrate its utility, we make use of a known dataset of individuals with traumatic brain injury sampled at two time points during the first year of recovery and show how the AILP procedure can be applied to select regions of interest to be used in a graph theoretical analysis of plasticity.
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Postherpetic neuralgia (PHN) is a common and exceptionally drug-resistant neuropathic pain condition. In this cross-sectional skin biopsy study, seeking information on the responsible pathophysiological mechanisms we assessed how ophthalmic PHN affects sensory and autonomic skin innervation. We took 2-mm supraorbital punch skin biopsies from the affected and unaffected sides in 10 patients with ophthalmic PHN. ⋯ Although skin biopsy showed reduced epidermal and dermal myelinated fiber density in specimens from the affected side, the epidermal/dermal myelinated nerve fiber ratio was lower in the affected than in the unaffected side (p < 0.001), thus suggesting a predominant epidermal unmyelinated nerve fiber loss. Conversely, autonomic skin innervation was spared. Our study showing that ophthalmic PHN predominantly affects unmyelinated nerve fiber and spares autonomic nerve fiber might help to understand the pathophysiological mechanisms underlying this difficult-to-treat condition.