Courses
Any of the following courses may be used as an elective in the Neuroscience Major, provided that course is not being used to fill another requirement. Some major requirements specify that a portion of some electives course has to be 300-level or above.
Students may also wish to consult our recommended Neuroscience-relevant electives.
Several course substitutions are allowed, but are not always explicitly listed in the catalog. Individual departments can provide a full list.
Additional electives may be approved by the concentration advisors.
Comp Bio Bio Chem & Physics Comp Sci Math Statistics BME Philosophy & Language Psych NSI
Computational Biology
02-250 Introduction to Computational Biology02-251 Great Ideas in Computational Biology
02-252 Introduction to Computational Cell Biology
02-319/03-360 Genomics and Epigenetics of the Brain
02-512 Computational Methods for Biological Modeling and Simulation
Biological Sciences
03-121/151 Modern Biology / Honors Modern Biology03-124 Modern Biology Lab
03-133 Neurobiology of Disease
03-201 Undergraduate Colloquium
03-231/232 Biochemistry I
03-220 Genetics
03-320 Cell Biology
03-343 Experimental Techniques in Molecular Biology
03-345 Experimental Cell and Developmental Biology
03-346 Experimental Neurobiology
03-350 Developmental Biology
03-365 Neural Correlates of Learning and Memory
03-366 Neuropharmacology: Drugs, Brain, and Behavior
03-439 Biophysics
03-442 Molecular Biology
Chemistry & Physics
09-105 Introduction to Modern Chemistry I (see possible substitutions)09-106 Modern Chemistry II
09-207 Techniques in Quantitative Analysis 1 (see possible substitutions)
09-217 Organic Chemistry I (see possible substitutions)
09-218 Organic Chemistry II (see possible substitutions)
09-208 Techniques in Organic Synthesis and Analysis (see possible substitutions)
33-121 Physics I for Science Students (see possible substitutions)
33-122 Physics II for Biological Sciences and Chemistry Students (see possible substitutions)
Computer Science, Machine Learning, & Robotics
10-301 Introduction to Machine Learning (Undergraduate)10-601 Machine Learning
15-110 Principles of Computing
15-112 Fundamentals of Programming and Computer Science
15-122 Principles of Imperative Computation
15-150 Principles of Functional Programming
15-251 Great Theoretical Ideas in Computer Science
15-386 Neural Computation
15-/86-387 Computational Perception
15-451 Algorithm Design and Analysis
15-494 Special Topic: Cognitive Robotics
15-883 Computational Models of Neural Systems
16-299 Introduction to Feedback Control Systems
16-311 Introduction to Robotics
Mathematical Sciences
21-120 Differential and Integral Calculus (see possible substitutions)21-122 Integration and Approximation
or 21-124 Calculus II for Biologists and Chemists
21-228 Discrete Mathematics
21-241 Matrices and Linear Transformations
or 21-240 Matrix Algebra with Applications
21-259 Calculus in 3D
21-341 Linear Algebra
Statistics
36-200 Reasoning with Data36-218 Probability Theory for Computer Scientists
or 36-219 Probability Theory and Random Processes
or 36-225 Probability Theory
36-226 Introduction to Statistical Inference
36-309 Experimental Design for Behavioral and Social Sciences
36-350 Statistical Computing
36-401 Modern Regression
36-462 Topics in Statistics: Data Mining
Biomedical Engineering
42-202 Physiology42-203 Biomedical Engineering Laboratory [BME majors have strong priority]
42-/86-631 Neural Data Analysis
42-632 Neural Signal Processing
English & Philosophy
80-210 Logic and Proofs80-211 Logic and Mathematical Inquiry
80-220 Philosophy of Science
80-254 Analytic Philosophy
80-270 Philosophy of Mind
80-280 Linguistic Analysis
Psychology
85-102 Introduction to Psychology85-221 Principles of Child Development
85-241 Social Psychology
85-261 Psychopathology
85-310 Research Methods in Cognitive Psychology
85-314 Research Methods in Cognitive Neuroscience
85-356 Expertise: The cognitive (neuro)science of mastering almost any skill
85-370 Perception
85-406 Autism: Psychological and Neuroscience Perspectives
85-408 Visual Cognition
85-412 Cognitive Modeling
85-414 Cognitive Neuropsychology
85-419 Introduction to Parallel Distributed Processing
85-442 Health Psychology
85-501 Readings in Developmental Psychology
Neuroscience Institute
86-351 What is Attention?86-375 Computational Perception
Core Neuroscience Courses
The following courses are the core Neuroscience courses that are most directly about brain function and its relationship to behavior.
02-219/03-360 Genomics & Epigenetics of the Brain
03-133 Neurobiology of Disease
03-161 Molecules to Mind
03-346 Experimental Neuroscience
03-362 Cellular Neuroscience
03-363 Systems Neuroscience
03-365 Neural Correlates of Learning and Memory
03-366 Neuropharmacology: Drugs, Brain, and Behavior
03-762 Advanced Cellular Neuroscience
03-763 Advanced Systems Neuroscience
03-765 Advanced Neural Correlates of Learning and Memory
10-301 Introduction to Machine Learning (Undergraduate)
10-601 Introduction to Machine Learning (Masters)
15-386 Neural Computation
15-494 Special Topic: Cognitive Robotics
15-883 Computational Models of Neural Systems
16-299 Introduction to Feedback Control Systems
16-311 Introduction to Robotics
36-401 Modern Regression
36-759 Statistical Models of the Brain
42-631 Neural Data Analysis (cross-listed as 86-631)
42-632 Neural Signal Processing
85-211 Cognitive Psychology
85-213 Human Information Processing and Artifical Intelligence
85-219 Biological Foundations of Behavior
85-314 Cognitive Neuroscience Research Methods
85-356 Expertise: The cognitive (neuro)science of mastering almost any skill
85-370 Perception
85-406 Autism: Psychological and Neuroscience Perspectives
85-408 Visual Cognition
85-412 Cognitive Modeling
85-414 Cognitive Neuropsychology
85-419 Introduction to Parallel Distributed Processing
85-719 Introduction to Parallel Distributed Processing
85-765 Cognitive Neuroscience
86-375 Computational Perception
Recommended Neuroscience Electives
The following courses are recommended because they have the most direct relevance for many Neuroscience applications.
Bio & Comp Bio Physics & Chemistry Comp Sci & Math Statistics BME Philosophy Psych NSI
Biology and Computational Biology
03-133 Neurobiology of Disease03-220 Genetics
02-512 Computational Methods for Biological Modeling and Simulation
03-231/232 Biochemistry I
03-320 Cell Biology
03-346 Experimental Neurobiology
03-350 Developmental Biology
02-319/03-360 Genomics & Epigenetics of the Brain
03-365 Neural Correlates of Learning and Memory
03-366 Neuropharmacology: Drugs, Brain, and Behavior
03-439 Biophysics
03-442 Molecular Biology
Physics & Chemistry
09-217 Organic Chemistry I33-122 Physics II for Biologists and Chemists
Computer Science, Machine Learning, Robotics, & Mathematics
10-301 Introduction to Machine Learning (Undergraduates)10-601 Machine Learning
15-386 Neural Computation
15-/86-387 Computational Perception
15-494 Special Topic: Cognitive Robotics
15-883 Computational Models of Neural Systems
16-299 Introduction to Feedback Control Systems
16-311 Introduction to Robotics
Statistics
36-200 Reasoning with Data36-309 Experimental Design for Behavioral and Social Sciences
36-350 Statistical Computing
36-401 Modern Regression
36-462 Topics in Statistics: Data Mining
Biomedical Engineering
42-202 Physiology42-/86-631 Neural Data Analysis
42-632 Neural Signal Processing
Philosophy
80-220 Philosophy of Science80-270 Philosophy of Mind
80-280 Linguistic Analysis
Psychology
85-102 Introduction to Psychology85-310 Research Methods in Cognitive Psychology
85-314 Research Methods in Cognitive Neuroscience
85-356 Expertise: The cognitive (neuro)science of mastering almost any skill
85-370 Perception
85-406 Autism: Psychological and Neuroscience Perspectives
85-408 Visual Cognition
85-412 Cognitive Modeling
85-414 Cognitive Neuropsychology
85-419 Introduction to Parallel Distributed Processing
Neuroscience Institute
86-351 What is Attention?86-375 Computational Perception
Common Course Substitutions
The department offering a course or the college that houses the department may offer substitutions. For a current list, please consult the department administration. This is a list of common substitutions.
These substitutions are not listed in because it is generally not advisable for students to take them as they are more challenging and many are less directly applicable to neuroscience. However, these substitutions are always acceptable for Neuroscience Majors.
Important note: These are approved substitutions only for the Neuroscience Major. Other majors and departments may not accept these substitutions.
Instead of 03-121 (Modern Biology), a student may substitute 03-151 (Honors Modern Biology).
Instead of 09-105 (Introduction to Modern Chemistry I), a student may substitute 09-107 (Honors Chemistry: Fundamentals Concepts and Applications).
Instead of 09-217 (Organic Chemistry I), a student may substitute 09-219 (Modern Organic Chemistry).
Instead of 09-218 (Organic Chemistry II), a student may substitute 09-220 (Modern Organic Chemistry II).
Instead of 09-207 (Techniques in Quantitative Analysis), a student may substitute 09-221 (Laboratory I).
Instead of 09-208 (Techniques in Organic Synthesis & Analysis), a student may substitute 09-222 (Laboratory II).
Instead of 21-120 (Differential and Integral Calculus), a student may substitute BOTH 21-111 and 21-112.
21-259 (Calculus in 3D) may also be used to substitute for one of the 2 calculus requirements.
Instead of 33-121 (Physics I for Science Students), a student may substitute either 33-141 or 33-151.
Instead of 33-122 (Physics II for Biologists and Chemists), a student may substitute either 33-142 or 33-152.
Transfer Credit
In order for a course to count as a substitute for a specific, required course toward the degree, two criteria must both be met:
- The course must be approved by the department that offers the Ò»±¾µÀÎÞÂë course as equivalent to the corresponding Ò»±¾µÀÎÞÂë course, and
- The course must be introductory level (200-level or below; the reason for this is that earning a degree from Ò»±¾µÀÎÞÂë means taking required, advanced courses from Ò»±¾µÀÎÞÂë).
Electives that are taken abroad can be used to satisfy 100-level or 200-level elective requirements toward the major if they are approved by the student's home department advising staff.
Students who wish to study abroad should discuss their plans with their major advisor and the . A plan should be reached before the student leaves for which classes they will take and how those classes will count toward their degree. Academic advisors and home department advising staff can also help a student obtain permission to take general education and core requirements abroad, subject to approval from the student's home college: MCS, or .