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

Theory Requirements
Course Topic/Title Course Number Units Prerequisites
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
Course Topic/Title Course Number Units Prerequisites
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
Course Topic/Title Course Number Units Prerequisites
Statistical Computing 36-350 or 36-650/750  9 36-202, 36-208, 36-309, 70-208, or equivalent
Neuroscience Requirements
Course Topic/Title Course Number Units Prerequisites
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.

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List of Approved Neuroscience Electives A: Methodology and Analysis
Course Topic/Title Course Number Units Prerequisites
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
Course Topic/Title Course Number Units Prerequisites
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