The human sense of smell plays an important role in appetite and food intake, detecting environmental threats, social interactions, and memory processing. However, little is known about the neural circuity supporting its function. The olfactory tracts project from the olfactory bulb along the base of the frontal cortex, branching into several striae to meet diverse cortical regions. Historically, using diffusion magnetic resonance imaging (dMRI) to reconstruct the human olfactory tracts has been prevented by susceptibility and motion artifacts. Here, we used a dMRI method with readout segmentation of long variable echo-trains (RESOLVE) to minimize image distortions and characterize the human olfactory tracts in vivo . We collected high-resolution dMRI data from 25 healthy human participants (12 male and 13 female) and performed probabilistic tractography using constrained spherical deconvolution (CSD). At the individual subject level, we identified the lateral, medial, and intermediate striae with their respective cortical connections to the piriform cortex and amygdala (AMY), olfactory tubercle (OT), and anterior olfactory nucleus (AON). We combined individual results across subjects to create a normalized, probabilistic atlas of the olfactory tracts. We then investigated the relationship between olfactory perceptual scores and measures of white matter integrity, including mean diffusivity (MD). Importantly, we foundmore »
Shape Analysis of White Matter Tracts via the Laplace-Beltrami Spectrum
Diffusion-weighted magnetic resonance imaging (dMRI) allows for non-invasive, detailed examination of the white matter structures of the brain. White matter tract-specific measures based on either the diffusion tensor model (e.g. FA, ADC, and MD) or tractography (e.g. volume, streamline count or density) are often compared between groups of subjects to localize differences within the white matter. Less commonly examined is the shape of the individual white matter tracts. In this paper, we propose to use the Laplace-Beltrami (LB) spectrum as a descriptor of the shape of white matter tracts. We provide an open, automated pipeline for the computation of the LB spectrum on segmented white matter tracts and demonstrate its efficacy through machine learning classification experiments. We show that the LB spectrum allows for distinguishing subjects diagnosed with bipolar disorder from age and sex-matched healthy controls, with classification accuracy reaching 95%. We further demonstrate that the results cannot be explained by traditional measures, such as tract volume, streamline count or mean and total length. The results indicate that there is valuable information in the anatomical shape of the human white matter tracts.
- Publication Date:
- NSF-PAR ID:
- 10073355
- Journal Name:
- MICCAI SHAPEMI
- Sponsoring Org:
- National Science Foundation
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Autism spectrum disorder (ASD) is currently viewed as a disorder of cortical systems connectivity, with a heavy emphasis being on the structural integrity of white matter tracts. However, the majority of the literature to date has focused on children with ASD. Understanding the integrity of white matter tracts in adults may help reveal the nature of ASD pathology in adulthood and the potential contributors to cognitive impairment. This study examined white matter water diffusion using diffusion tensor imaging in relation to neuropsychological measures of cognition in a sample of 45 adults with ASD compared to 20 age, gender, and full‐scale‐IQ‐matched healthy volunteers. Tract‐based spatial statistics were used to assess differences in diffusion along white matter tracts between groups using permutation testing. The following neuropsychological measures of cognition were assessed: processing speed, attention vigilance, working memory, verbal learning, visual learning, reasoning and problem solving, and social cognition. Results indicated that fractional anisotropy (FA) was significantly reduced in adults with ASD in the anterior thalamic radiation (
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