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Biomedical Signal Processing and Imaging
Clinical Decision Making
Computational Biophysics
Computational Genomics & Proteomics
Computational Neuroscience: These figures show the sequential inflation of the segmented cortical surfaces. Courtesy Bruce Fischi, MGH
Micro/Nanotechnology for Biology & Medicine
Quantitative Physiology
Sensory Communication
Synthetic Biology
Tissue Engineering

Computational Neuroscience

Courses: 6.555J, 6.556J

Polina Golland
Eric Grimson

Computational neuroscience focuses on computational models of brain activity and development, using a wide variety of measurement techniques, from cognitive experiments, to EEG, MEG and MRI. Research in this area builds heavily on control theory and signal processing. Probability and machine learning often prove useful in modeling noisy biomedical measurements. The courses in this area introduce computational models for various brain functions, from motor control to knowledge representation and cognition.


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