Statistics – 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.
Statistics and Neuroscience Track
Theory Requirements |
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| 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 | 36-225, 36-218, 36-219, 21-325, or 15-359 | 9 | various |
| Statistical Inference | 36-226 or 36-326 | 9 | C or higher in 36-225, 36-218, 36-219, 21-325, or 15-359 |
Data-Analysis Requirements |
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| Course Topic/Title | Course Number | Units | Prerequisites |
| Beginning Data Analysis | 36-200 | 9 | |
| Intermediate Data Analysis | 36-202, 36-208, 36-290, or 36-309 | 9 | |
| Advanced Elective | 36-303, 36-311, 36-315, 36-318, 36-46x, or 36-490, 36-493 or 36-497 | 9 | 36-202, 36-208, 36-290, 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) and (21-256 or 21-259 or 21-268) |
| Advanced Methods for Data Analysis | 36-402 | 9 | C or higher in 36-401 |
| Computing Requirements | |||
| Course Topic/Title | Course Number | Units | Prerequisites |
| Statistical Computing | 36-350 or 36-650 | 9 | (36-202 or 36-208 or 36-309 or 70-208, or 36-290 or equivalent) and 36-225 |
Neuroscience Requirements |
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| Course Topic/Title | Course Number | Units | Prerequisites |
| Cognitive Psychology | 85-211 | 9 | |
| Biological Foundations of Behavior | 85-219 | 9 | 85-100 or instructor approval |
| Three Neuroscience Electives |
With at least one selected from each list |
27 | |
List of Approved Neuroscience Electives A: Methodology and Analysis |
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| Course Topic/Title | Course Number | Units | Prerequisites |
| Probability and Mathematical Statistics or Intermediate Statistics | 36-700 or 36-705 | 12 | |
| Machine Learning | 10-301 | 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 | 86-631 or 42-631 | 12 | |
List of Approved Neuroscience Electives B: Neuroscientific Background |
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| 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 |
| Cognitive Neuropsychology | 85-414 | 9 | 85-219 or 85-211 |
| Intro to Parallel Distributed Processing | 85-419 | 9 | 85-213 or 85-211 |