Neural Engineering

Neural Interfaces: Understanding, knowledge, and practical skills in the design, development, and application of advanced neural interfaces. Upon completion of the PhD program, students will be able to critically evaluate various neural interface technologies and methodologies. Students will demonstrate proficiency in analyzing neural signals and comparing single-unit to population activity signals in both the central and peripheral nervous system. Students will gain an understanding of biocompatibility as it relates to neural interfaces and will be able to discuss biocompatibility issues and how they relate to neural interface performance, methods for testing biocompatibility, and possible optimizations to increase biocompatibility. Finally, students will gain hands-on experience in the fabrication and testing of neural electrodes, biosensors, and microelectronic devices tailored for interfacing with the nervous system.

Neural Analysis and Modeling: Understanding, knowledge, and practical skills in the analysis of neural signals and the techniques used for neural modeling. Upon completion of this program, students will demonstrate proficiency in mathematical and computational techniques for modeling neural systems, including neural networks, neural circuits, and spiking neurons. Students will gain hands-on experience in computational neuroscience, enabling them to construct and analyze models that replicate neural behaviors and phenomena. Additionally, students will develop skills in data-driven modeling approaches, such as machine learning and statistical analysis, allowing them to extract meaningful insights from experimental neural data. Students will gain hands-on experience with simulation software and programming languages commonly used in neural analysis and modeling.

Neurophysiology: Understanding, knowledge, and practical skills in the structure and function of the nervous system. Upon completion of this PhD program, students will demonstrate proficiency in the anatomy and physiology of the brain, spinal cord, and peripheral nervous system, including the organization of neural systems and circuits and the mechanisms underlying neural signaling. Students will understand experimental techniques for studying neural activity, such as electrophysiology, optogenetics, and imaging methods like fMRI and PET. Through critical review and hands-on experience, students will gain expertise in applying basic physical and physiological principles to resolve questions related to systems or cellular processes in the nervous system.

Neuroprosthetics and Neurorobotics: Understanding, knowledge, and practical skills in the design, development, and implementation of robotic and prosthetic systems interfacing with the nervous system. Upon completion of this PhD program, students will demonstrate proficiency in various principles of biomechanics, robotics, mechatronics, and control as they relate to neuroprosthetic devices and neurorobotic systems. Students will have an understanding of neuroprosthetic devices that are tailored to individuals with neurological impairments, as well as experience in programming and controlling neurorobotic platforms using neural signals. Additionally, students will develop various hands-on skills in human-machine interaction, neural decoding, and closed-loop control, enabling them to create prosthetic and robotic systems that restore function and enhance quality of life for individuals with neurological dysfunction.

Neuroethics: Understanding of the ethical, legal, and societal implications associated with advancements in neurotechnology and neural engineering. Upon completion of this degree, students will demonstrate proficiency in critically evaluating ethical dilemmas and issues arising from the use of neurotechnologies in research, clinical practice, and everyday life. Students will gain insights into topics such as cognitive enhancement, privacy concerns, informed consent, data bias, and equitable access to neurotechnological interventions. Additionally, students will develop skills in ethical decision-making, interdisciplinary collaboration, and effective communication, enabling them to navigate complex ethical challenges and contribute to the responsible development and implementation of neurotechnology. Through coursework, case studies, and discussions with experts in the field, graduates will be prepared to address ethical considerations at the forefront of neurotechnology, promoting ethical practices and ensuring that advancements in the field benefit society as a whole.

Hands-on Project Experience: Practical skills applying neurotechnology knowledge to a hands-on project experience. The project can be achieved through approved project-intensive coursework for doctoral students, as they will not complete a separate project. PhD students will apply principles from neurotechnology to real problems or novel questions to provide tangible results such as software, hardware, or data analysis in project-intensive coursework. PhD students will also gain hands-on experience through their dissertation research.

Modern Research Topics: Understanding and knowledge of modern topics of research in neurotechnology. Students will engage in research presentations related to neurotechnology and neural engineering from faculty and advanced trainees. Students will synthesize and discuss research presentations. Additionally, students can participate in journal club discussions to engage in current research in neurotechnology.