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.

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 orHuman 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 | 27 | |

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 |