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Biostats & bioengineering

Introduction to Magnetic Resonance Imaging and Neuroimaging (ENGN 1930N, Fall, Deoni):

Magnetic resonance imaging (MRI) is a powerful tool for investigating the biological structure and functional dynamics across an incredibly broad spatial and temporal scale. This course will provide an understanding of the basic physical principles of magnetic resonance; including signal generation, detection and contrast mechanisms; as well as image acquisition techniques and reconstruction methods. This course is aimed at undergraduate and graduate students from a variety of disciplines, including: Engineering, Computer Science, Applied Mathematics, Physics, Cognitive Science and Neuroscience as well as medical students and residents. Students should have a basic understanding of matrix mathematics and familiarity with the concepts of magnetism and waves. Graduate, Undergraduate

Neuroengineering (ENGN 1220, Spring, Nurmikko & Hochberg):

To develop an advanced understanding of how signals are generated and propagated in neurons and neuronal circuits, and how this knowledge can be harnessed to design devices to assist people with neurologic disease or injury. Fundamental topics in neuronal and neural signal generation, recording methods, and stimulation methods. Clinical/Translational topics include multiple clinically available and emerging neurotechnologies. Graduate, Undergraduate

    Academic Resources at Brown
  1. Recommended coursework for undergraduate students
  2. Faculty with computational neuroscience research
    Recommended Courses on Computational Modeling
  1. Methods & programming
  2. Biostats & bioengineering
  3. Methods & data analysis
  4. Computational vision
  5. Computational cognitive science / neuroscience
  6. Neuroscience
  7. Mathematical & Computations