Specialization in Computational, Neurorehabilitation and Neuroimaging neuroscience

About the Programs

Students pursuing this neuroscience specialization will acquire a foundational background in computational modeling, neurorehabilitation and/or neuroimaging.

Computational modeling

Explores processes from single neurons to neuronal networks including neural interconnections, neural signal processing, and synaptic plasticity.

Neurorehabilitation

Explores the mechanisms and clinical and laboratory methods for studying neural disorders and the treatment strategies to address them.

Neuroimaging neuroscience

Explores imaging physics, mathematics, and methods towards problems in basic and applied neuroscience.

Areas of focus

Statistical models for magnetic resonance imaging, computational models of gene regulatory networks, predictive models of neurophysiological processes and clinical outcomes, human visuo-motor processing, functional neuroimaging, brain structural and functional connectivity, spinal cord imaging and human motor control, neural and neurodevelopmental disorders, neurodegenerative diseases, and rehabilitative strategies.

Course Requirements

Students admitted to the program are required to complete a minimum of 41 to 49 credit hours, depending on their specialization. All students will complete the following courses:

Course number Course title Credit hours
NRSC 8001 Neuroscience Foundations I 4
NRSC 8002 Neuroscience Foundations II 4
BISC 5140 Functional Neuroanatomy 3
NRSC 8096 First year lab rotations 3 rotations, 1 credit each
Graduate Statistics 3
NRSC 8003 Independent Development Program Seminar 1
NRSC 8004 Science Writing & Ethics Instruction I 1
NRSC 8005 Science Writing & Ethics Instruction II 1
NRSC 8999 Dissertation 12

Students in the Computational, Neurorehabilitation & Neuroimaging specialization must complete at least three courses from within the following domains:

Domain 1 - Computational

Course number Course title Credit hours
MSCS 5780 Regression 3
MSCS 5760 Time Series 3
MSCS 6010 Probability 3
MSCS 6020 Simulation 3
MSCS 6230 Advanced Multivariate Data Analytics 3
MSCS 6240 Design of Experiments and Data Analysis 3
MSCS 5600 Fundamentals of Artificial Intelligence 3
MSCS 5610 Data Mining 3
MSCS 5800 Principles of Database Systems 3
MSCS 6050 Elements of Software Development 3
MSCS 6060 Parallel and Distributed Systems 3
MSCS 6030 Applied Mathematical Analysis 3
MSCS 6040 Applied Linear Algebra 3
MSCS 6110 Applied Discrete Mathematics 3
MSCS 6120 Optimization 3
MSCS 6130 Dynamical Systems 3

Domain 2 - Neuroimaging and Neuroengineering

Course number Course title Credit hours
BIEN 5600 Neural Engineering 3
BIEN 6600 Neuromotor Control 3
BIEN 6200 Biomedical Signal Processing 3
BIEN 6210 Advanced Biomedical Signal Processing 3
BIEN 6220 Multidimensional Time Series Analysis 3
BIEN 5230 Intelligent Biosystems 3
BIEN 5710 Analysis of Physiologic Models 3
BIEN 5500 Medical Imaging Physics 3
BIEN 5510 Image Processing for the Biomedical Sciences 3
BIEN 6500 Mathematics of Medical Imaging 3

Domain 3 - Neurorehabilitation

Course number Course title Credit hours
CTRH 6001 Applied & Rehabilitative Systems Physiology 3
CTRH 6201 Neurophysiological Principles of Disease & Rehab 3
CTRH 6030 Advanced Principles of Instrumentation in Biomechanics 3

An additional 3 to 6 credits of electives may be chosen from the courses and seminars offered in any of the specializations or other doctoral level courses offered by participating departments, as appropriate to individual plans of study.

Application Deadline

January 15 for the following fall semester.

Application Requirements

Financial Aid

Research and teaching assistantships are available.

Private scholarships may also be available. U.S. citizens and permanent residents may be eligible to apply for need-based federal aid (loans) to help fund their educational expenses as well.

More Information and Scheduling a Visit

Ready to learn more about Marquette's Neuroscience PH.D. program? Request more information now or schedule an on-campus visit.