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Description
A direct Magnetic Resonance (MR)-based neural activity mapping technique with high spatial and temporal resolution may accelerate studies of brain functional organization.

The most widely used technique for brain functional imaging is functional Magnetic Resonance Image (fMRI). The spatial resolution of fMRI is high. However, fMRI signals are highly influenced

A direct Magnetic Resonance (MR)-based neural activity mapping technique with high spatial and temporal resolution may accelerate studies of brain functional organization.

The most widely used technique for brain functional imaging is functional Magnetic Resonance Image (fMRI). The spatial resolution of fMRI is high. However, fMRI signals are highly influenced by the vasculature in each voxel and can be affected by capillary orientation and vessel size. Functional MRI analysis may, therefore, produce misleading results when voxels are nearby large vessels. Another problem in fMRI is that hemodynamic responses are slower than the neuronal activity. Therefore, temporal resolution is limited in fMRI. Furthermore, the correlation between neural activity and the hemodynamic response is not fully understood. fMRI can only be considered an indirect method of functional brain imaging.

Another MR-based method of functional brain mapping is neuronal current magnetic resonance imaging (ncMRI), which has been studied over several years. However, the amplitude of these neuronal current signals is an order of magnitude smaller than the physiological noise. Works on ncMRI include simulation, phantom experiments, and studies in tissue including isolated ganglia, optic nerves, and human brains. However, ncMRI development has been hampered due to the extremely small signal amplitude, as well as the presence of confounding signals from hemodynamic changes and other physiological noise.

Magnetic Resonance Electrical Impedance Tomography (MREIT) methods could have the potential for the detection of neuronal activity. In this technique, small external currents are applied to a body during MR scans. This current flow produces a magnetic field as well as an electric field. The altered magnetic flux density along the main magnetic field direction caused by this current flow can be obtained from phase images. When there is neural activity, the conductivity of the neural cell membrane changes and the current paths around the neurons change consequently. Neural spiking activity during external current injection, therefore, causes differential phase accumulation in MR data. Statistical analysis methods can be used to identify neuronal-current-induced magnetic field changes.
ContributorsFu, Fanrui (Author) / Sadleir, Rosalind (Thesis advisor) / Kodibagkar, Vikram (Committee member) / Kleim, Jeffrey (Committee member) / Muthuswamy, Jitendran (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2019
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Description
The reconstruction of piecewise smooth functions from non-uniform Fourier data arises in sensing applications such as magnetic resonance imaging (MRI). This thesis presents a new polynomial based resampling method (PRM) for 1-dimensional problems which uses edge information to recover the Fourier transform at its integer coefficients, thereby enabling the use

The reconstruction of piecewise smooth functions from non-uniform Fourier data arises in sensing applications such as magnetic resonance imaging (MRI). This thesis presents a new polynomial based resampling method (PRM) for 1-dimensional problems which uses edge information to recover the Fourier transform at its integer coefficients, thereby enabling the use of the inverse fast Fourier transform algorithm. By minimizing the error of the PRM approximation at the sampled Fourier modes, the PRM can also be used to improve on initial edge location estimates. Numerical examples show that using the PRM to improve on initial edge location estimates and then taking of the PRM approximation of the integer frequency Fourier coefficients is a viable way to reconstruct the underlying function in one dimension. In particular, the PRM is shown to converge more quickly and to be more robust than current resampling techniques used in MRI, and is particularly amenable to highly irregular sampling patterns.
ContributorsGutierrez, Alexander Jay (Author) / Platte, Rodrigo (Thesis director) / Gelb, Anne (Committee member) / Viswanathan, Adityavikram (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2013-05
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Description
Among electrical properties of living tissues, the differentiation of tissues or organs provided by electrical conductivity is superior. The pathological condition of living tissues is inferred from the spatial distribution of conductivity. Magnetic Resonance Electrical Impedance Tomography (MREIT) is a relatively new non-invasive conductivity imaging technique. The majority of

Among electrical properties of living tissues, the differentiation of tissues or organs provided by electrical conductivity is superior. The pathological condition of living tissues is inferred from the spatial distribution of conductivity. Magnetic Resonance Electrical Impedance Tomography (MREIT) is a relatively new non-invasive conductivity imaging technique. The majority of conductivity reconstruction algorithms are suitable for isotropic conductivity distributions. However, tissues such as cardiac muscle and white matter in the brain are highly anisotropic. Until recently, the conductivity distributions of anisotropic samples were solved using isotropic conductivity reconstruction algorithms. First and second spatial derivatives of conductivity (∇σ and ∇2σ ) are integrated to obtain the conductivity distribution. Existing algorithms estimate a scalar conductivity instead of a tensor in anisotropic samples.

Accurate determination of the spatial distribution of a conductivity tensor in an anisotropic sample necessitates the development of anisotropic conductivity tensor image reconstruction techniques. Therefore, experimental studies investigating the effect of ∇2σ on degree of anisotropy is necessary. The purpose of the thesis is to compare the influence of ∇2σ on the degree of anisotropy under two different orthogonal current injection pairs.

The anisotropic property of tissues such as white matter is investigated by constructing stable TX-151 gel layer phantoms with varying degrees of anisotropy. MREIT and Diffusion Magnetic Resonance Imaging (DWI) experiments were conducted to probe the conductivity and diffusion properties of phantoms. MREIT involved current injection synchronized to a spin-echo pulse sequence. Similarities and differences in the divergence of the vector field of ∇σ (∇2σ) among anisotropic samples subjected to two different current injection pairs were studied. DWI of anisotropic phantoms involved the application of diffusion-weighted magnetic field gradients with a spin-echo pulse sequence. Eigenvalues and eigenvectors of diffusion tensors were compared to characterize diffusion properties of anisotropic phantoms.

The orientation of current injection electrode pair and degree of anisotropy influence the spatial distribution of ∇2σ. Anisotropy in conductivity is preserved in ∇2σ subjected to non-symmetric electric fields. Non-symmetry in electric field is observed in current injections parallel and perpendicular to the orientation of gel layers. The principal eigenvalue and eigenvector in the phantom with maximum anisotropy display diffusion anisotropy.
ContributorsAshok Kumar, Neeta (Author) / Sadleir, Rosalind J (Thesis advisor) / Kodibagkar, Vikram (Committee member) / Muthuswamy, Jitendran (Committee member) / Arizona State University (Publisher)
Created2015