# Statistics and Neuroscience Track

New technologies for measuring the brain are revolutionizing our understanding of the brain, and the revolution is data-driven. This track focuses on the statistical problems in neuroscience, including neural data analysis and neuroimaging. It is ideal for students interested in data science with an emphasis on brain and behavior or in neuroscience with an emphasis on data analysis.

# Major Requirements

Course Topic/Title Course Number Units Prerequisites Theory Requirements Calculus 21-111 and 112, or 21-120 20 or 10 Multivariate 21-256, 21-259, or 21-268 9–10 21-112 or 21-120 Linear/Matrix Algebra 21-240, 21-241, or 21-242 10 Probability 36-217, 21-325, 15-359, or 36-225 9 21-112, 21-122, 21-123, 21-256, or 21-259 Statistical Inference 36-226 or 36-326 9 C or higher in 36-217, 36-225, 21-325, or 15-359 Data-Analysis Requirements Beginning Data Analysis 36-201 9 Intermediate Data Analysis 36-202, 36-208, or 36-309 9 Advanced Elective 36-315, 36-303, 36-46x 9 36-202, 36-208, or 36-309 Special Topics 36-46x 9 various Modern Regression 36-401 9 C or higher in 36-226, 36-326, or 36-625 and pass 21-240 or 21-241 Advanced Methods for Data Analysis 36-402 9 C or higher in 36-401 Time Series Analysis 36-428 6 36-226 Statistical Models of the Brain 36-459 9 36-226 Computing Requirements Statistical Computing 36-350 or 36-650/750 9 36-202, 36-208, 36-309, 70-208, or equivalent Neuroscience Requirements Cognitive Psychology or Human Information Processing and AI 85-211 or 85-219 9 Biological Foundations of Behavior 85-219 9 85-100 or instructor approval Three Neuroscience Electives With at least one selected from each list(A) Methodology and Analysis and(B) Neuroscientific Background. 27 List of Approved Neuroscience Electives A: Methodology and Analysis Probability and Mathematical Statistics I 36-625 9 21-118, 21-122, 21-123, or 21-256 Probability and Mathematical Statistics II 36-625 9 36-625 Machine Learning 10-601 12 15-122 and (15-151 or 21-127) Systems Neuroscience 18-290 12 18-100 Cognitive Science Research Methods 85-314 12 36-309 Neural Data Analysis 85-631 or 42-631 12 List of Approved Neuroscience Electives B: Neuroscientific Background Cellular Neuroscience 03-362 9 85-219, 42-202, 03-161, or 03-240 Systems Neuroscience 03-363 9 85-219, 42-202, 03-161, or 03-240 Neural Computation 15-386 9 21-122 and 15-122 Intro to Cognitive Neuroscience 85-355 9 85-219 or 85-211 Cognitive Neuropsychology 85-414 9 85-219 or 85-211 Intro to Parallel Distributed Processing 85-419 9 85-213 or 85-211