John Bodenschatz

Education

• 2021 - Present      Ph.D. Candidate in Computational Sciences, Marquette University, Milwaukee, WI
• 2021 - 2023          M.S. Applied Statistics, Marquette University, Milwaukee, WI
• 2017 - 2021          B.S. Mathematics, Physics, University of Cincinnati, Cincinnati, OH

Experience

• 08/2024 - Present :   Research Assistant, Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI
• 08/2021 - 05/2024 :  Teaching Assistant, Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI
• Calculus 1
• Calculus 2
• Multivariable Calculus
• Differential Equations
• Elements of Calculus
• Biostatistical Methods and Models

Research

1. Simulation and Harmonic Analysis of k-Space Readout (SHAKER)

Running fMRI experiments with human subjects is a temporally and financially costly task. Many researchers turn to simulated data to develop and refine models as a result. This aim of this research project was to develop a comprehensive MATLAB package for simulating complex-valued fMRI time series data, which we call SHAKER. SHAKER simulates fMRI data in a physically accurate representation, using steady-state solutions of the Bloch equations to generate k-space measurements. SHAKER allows for users to adjust any relevant MR parameters, including custom pulse sequences and k-space trajectories. Some common statistical analysis tools are also built-in, with templates for custom applications to be inserted as well.

A draft manustript for SHAKER can be found on arXiv. This manuscript is currently under review for a scientific journal. The lateset version of SHAKER can be found on GitHub. If you have any features that you would like to see added, please reach out!

The below picture is a screenshot of the SHAKER GUI. The top left pane is where the phantom can be viewed and a slice can be selected. The bottom left pane is where MR and fMRI xperimental parameters are adjusted. The top right pane is where simulated data can be viewed. The bottom right pane is where some statistical analysis can be conducted on the simulated data.



2. Bayesian Magnitude and Phase Estimation of Non-Cartesian k-Space for FMRI

It is well known in fMRI studies that the first three or so images in a time series have much higher signal than the remainder of the time series.

A manuscript of this work is in submission for review for a scientific journal.

The below picture is a screenshot of the SHAKER GUI. The top left pane is where the phantom can be viewed and a slice can be selected. The bottom left pane is where MR and fMRI xperimental parameters are adjusted. The top right pane is where simulated data can be viewed. The bottom right pane is where some statistical analysis can be conducted on the simulated data.



3. Increased Brain Activation Power from A Mathematically Accurate Angular Phase Model

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4. Bayesian Estimation and Reconstruction of Subsampled Non-Cartesian k-Space for FMRI

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