44,489 research outputs found
Diffeomorphic Metric Mapping of High Angular Resolution Diffusion Imaging based on Riemannian Structure of Orientation Distribution Functions
In this paper, we propose a novel large deformation diffeomorphic
registration algorithm to align high angular resolution diffusion images
(HARDI) characterized by orientation distribution functions (ODFs). Our
proposed algorithm seeks an optimal diffeomorphism of large deformation between
two ODF fields in a spatial volume domain and at the same time, locally
reorients an ODF in a manner such that it remains consistent with the
surrounding anatomical structure. To this end, we first review the Riemannian
manifold of ODFs. We then define the reorientation of an ODF when an affine
transformation is applied and subsequently, define the diffeomorphic group
action to be applied on the ODF based on this reorientation. We incorporate the
Riemannian metric of ODFs for quantifying the similarity of two HARDI images
into a variational problem defined under the large deformation diffeomorphic
metric mapping (LDDMM) framework. We finally derive the gradient of the cost
function in both Riemannian spaces of diffeomorphisms and the ODFs, and present
its numerical implementation. Both synthetic and real brain HARDI data are used
to illustrate the performance of our registration algorithm
Angular Upsampling in Infant Diffusion MRI Using Neighborhood Matching in x-q Space
Diffusion MRI requires sufficient coverage of the diffusion wavevector space,
also known as the q-space, to adequately capture the pattern of water diffusion
in various directions and scales. As a result, the acquisition time can be
prohibitive for individuals who are unable to stay still in the scanner for an
extensive period of time, such as infants. To address this problem, in this
paper we harness non-local self-similar information in the x-q space of
diffusion MRI data for q-space upsampling. Specifically, we first perform
neighborhood matching to establish the relationships of signals in x-q space.
The signal relationships are then used to regularize an ill-posed inverse
problem related to the estimation of high angular resolution diffusion MRI data
from its low-resolution counterpart. Our framework allows information from
curved white matter structures to be used for effective regularization of the
otherwise ill-posed problem. Extensive evaluations using synthetic and infant
diffusion MRI data demonstrate the effectiveness of our method. Compared with
the widely adopted interpolation methods using spherical radial basis functions
and spherical harmonics, our method is able to produce high angular resolution
diffusion MRI data with greater quality, both qualitatively and quantitatively.Comment: 15 pages, 12 figure
Axon diameters and myelin content modulate microscopic fractional anisotropy at short diffusion times in fixed rat spinal cord
Mapping tissue microstructure accurately and noninvasively is one of the
frontiers of biomedical imaging. Diffusion Magnetic Resonance Imaging (MRI) is
at the forefront of such efforts, as it is capable of reporting on microscopic
structures orders of magnitude smaller than the voxel size by probing
restricted diffusion. Double Diffusion Encoding (DDE) and Double Oscillating
Diffusion Encoding (DODE) in particular, are highly promising for their ability
to report on microscopic fractional anisotropy ({\mu}FA), a measure of the pore
anisotropy in its own eigenframe, irrespective of orientation distribution.
However, the underlying correlates of {\mu}FA have insofar not been studied.
Here, we extract {\mu}FA from DDE and DODE measurements at ultrahigh magnetic
field of 16.4T in the aim to probe fixed rat spinal cord microstructure. We
further endeavor to correlate {\mu}FA with Myelin Water Fraction (MWF) derived
from multiexponential T2 relaxometry, as well as with literature-based
spatially varying axonal diameters. In addition, a simple new method is
presented for extracting unbiased {\mu}FA from three measurements at different
b-values. Our findings reveal strong anticorrelations between {\mu}FA (derived
from DODE) and axon diameter in the distinct spinal cord tracts; a moderate
correlation was also observed between {\mu}FA derived from DODE and MWF. These
findings suggest that axonal membranes strongly modulate {\mu}FA, which - owing
to its robustness towards orientation dispersion effects - reflects axon
diameter much better than its typical FA counterpart. The {\mu}FA exhibited
modulations when measured via oscillating or blocked gradients, suggesting
selective probing of different parallel path lengths and providing insight into
how those modulate {\mu}FA metrics. Our findings thus shed light into the
underlying microstructural correlates of {\mu}FA and are (...
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The role of HG in the analysis of temporal iteration and interaural correlation
Diffusion imaging and tractography of congenital brain malformations.
Diffusion imaging is an MRI modality that measures the microscopic molecular motion of water in order to investigate white matter microstructure. The modality has been used extensively in recent years to investigate the neuroanatomical basis of congenital brain malformations. We review the basic principles of diffusion imaging and of specific techniques, including diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI). We show how DTI and HARDI, and their application to fiber tractography, has elucidated the aberrant connectivity underlying a number of congenital brain malformations. Finally, we discuss potential uses for diffusion imaging of developmental disorders in the clinical and research realms
How can neuroscience contribute to moral philosophy, psychology and education based on Aristotelian virtue ethics?
The present essay discusses the relationship between moral philosophy, psychology and education based on virtue ethics, contemporary neuroscience, and how neuroscientific methods can contribute to studies of moral virtue and character. First, the present essay considers whether the mechanism of moral motivation and developmental model of virtue and character are well supported by neuroscientific evidence. Particularly, it examines whether the evidence provided by neuroscientific studies can support the core argument of virtue ethics, that is, motivational externalism. Second, it discusses how experimental methods of neuroscience can be applied to studies in human morality. Particularly, the present essay examines how functional and structural neuroimaging methods can contribute to the development of the fields by reviewing the findings of recent social and developmental neuroimaging experiments. Meanwhile, the present essay also considers some limitations embedded in such discussions regarding the relationship between the fields and suggests directions for future studies to address these limitations
Local modes, phonons, and mass transport in solid He
We propose a model to treat the local motion of atoms in solid He as a
local mode. In this model, the solid is assumed to be described by the Self
Consistent Harmonic approximation, combined with an array of local modes. We
show that in the bcc phase the atomic local motion is highly directional and
correlated, while in the hcp phase there is no such correlation. The correlated
motion in the bcc phase leads to a strong hybridization of the local modes with
the T phonon branch, which becomes much softer than that obtained
through a Self Consistent Harmonic calculation, in agreement with experiment.
In addition we predict a high energy excitation branch which is important for
self-diffusion. Both the hybridization and the presence of a high energy branch
are a consequence of the correlation, and appear only in the bcc phase. We
suggest that the local modes can play the role in mass transport usually
attributed to point defects (vacancies). Our approach offers a more overall
consistent picture than obtained using vacancies as the predominant point
defect. In particular, we show that our approach resolves the long standing
controversy regarding the contribution of point defects to the specific heat of
solid He.Comment: 10 pages, 10 figure
Magnetic susceptibility anisotropy of myocardium imaged by cardiovascular magnetic resonance reflects the anisotropy of myocardial filament α-helix polypeptide bonds.
BackgroundA key component of evaluating myocardial tissue function is the assessment of myofiber organization and structure. Studies suggest that striated muscle fibers are magnetically anisotropic, which, if measurable in the heart, may provide a tool to assess myocardial microstructure and function.MethodsTo determine whether this weak anisotropy is observable and spatially quantifiable with cardiovascular magnetic resonance (CMR), both gradient-echo and diffusion-weighted data were collected from intact mouse heart specimens at 9.4 Tesla. Susceptibility anisotropy was experimentally calculated using a voxelwise analysis of myocardial tissue susceptibility as a function of myofiber angle. A myocardial tissue simulation was developed to evaluate the role of the known diamagnetic anisotropy of the peptide bond in the observed susceptibility contrast.ResultsThe CMR data revealed that myocardial tissue fibers that were parallel and perpendicular to the magnetic field direction appeared relatively paramagnetic and diamagnetic, respectively. A linear relationship was found between the magnetic susceptibility of the myocardial tissue and the squared sine of the myofiber angle with respect to the field direction. The multi-filament model simulation yielded susceptibility anisotropy values that reflected those found in the experimental data, and were consistent that this anisotropy decreased as the echo time increased.ConclusionsThough other sources of susceptibility anisotropy in myocardium may exist, the arrangement of peptide bonds in the myofilaments is a significant, and likely the most dominant source of susceptibility anisotropy. This anisotropy can be further exploited to probe the integrity and organization of myofibers in both healthy and diseased heart tissue
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