Carnegie Mellon University

Computational Neuroscience Concentration

Students can begin with the first year sample schedule or Computational Neuroscience Concentration sample schedule, as well as by contacting the advisors.

NOTE: Computational Neuroscience concentration students must complete 21-122, 15-112, and 36-217 in their General Science Requirements (section A, above) and 15-386 in their Core Neuroscience Courses (section B, above). Students must complete a minimum of 60 units in this concentration. Students should select their required laboratory and elective courses to complete a minimum of 31 units (Four 9 unit courses or a lesser number of 9 and 12 unit courses could be combined to complete this requirement).

Complete Computational Neuroscience Concentration Requirements

General Science Requirements

21-120        Differential and Integral Calculus
21-122        Integration, Differential Equations and Approximation
03-121        Modern Biology
03-220        Genetics (formerly 03-330)
33-111        Physics I for Science Students
15-112        Fundamentals of Programming and Computer Science
09-105        Introduction to Modern Chemistry I
09-106        Modern Chemistry II
09-217        Organic Chemistry I
   or 33-122    Physics II for Biologists and Chemists
09-207         Techniques in Quantitative Analysis
   or 03-124     Modern Biology Laboratory
36-217    Probability Theory and Random Processes*
   or 36-225    Introduction to Probability Theory

*Note: 36-217 and 36-225 do not count toward Dietrich GenEd.  Dietrich students should talk with DC advisors and major advisors.

Core Neuroscience Courses

85-219        Biological Foundations of Behavior
   or 03-161    Molecules to Mind
85-211        Cognitive Psychology
   or 85-213    Human Information Processing and Artificial Intelligence
03-362        Cellular Neuroscience
03-363        Systems Neuroscience
15-386        Neural Computation

Computational Core

15-122         Principles of Imperative Computation
      or 15-150    Principles of Functional Programming                
21-127         Concepts in Mathematics
21-241         Matrices and Linear Transformations

Two of the following

42-631        Neural Data Analysis    
42-632        Neural Signal Processing
15-486        Artificial Neural Networks
15-494        Special Topic: Cognitive Robotics
15-883        Computational Models of Neural Systems

Computational Electives

Students must complete 1 of the following
02-/03-512    Computational Methods for Biological Modeling and Simulation 
10-601         Machine Learning
15-381         Artificial Intelligence: Representation and Problem Solving
15-387         Computational Perception
15-451         Algorithm Design and Analysis
15-453         Formal Languages, Automata, and Computability
15-486         Artificial Neural Networks
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
21-228         Discrete Mathematics
      or 15-251    Great Theoretical Ideas in Computer Science            
21-259         Calculus in 3D
21-341         Linear Algebra
21-272         Introduction to Partial Differential Equations
PM-1800       Mathematical Neuroscience (at University of Pittsburgh)
36-/70-208   Regression Analysis
36-226         Introduction to Statistical Inference
36-350         Statistical Computing
36-401         Modern Regression
36-462         Topics in Statistics: Data Mining
42-631        Neural Data Analysis    
42-632        Neural Signal Processing

General Neuroscience Electives

Students must complete 18 units of course work from this list, at least 9 units must be at the 300-level or above.
(Concentration advisors can approve additional electives to fill this requirement)

Additional Graduation Requirements

Students must also complete:

  • Free elective hours to come to a total of 360 total course hours

Double-counting restrictions and additional majors & minors

Students may not major in two concentrations.

Students using Neuroscience as an additional major or who have an additional major or minor to Neuroscience may only double-count at most 3 courses between this an their other major or minor (this restriction does not apply to prerequisites, General Education Requirements, or the General Science Requirements – section A).

Other majors and minors may have more stringent double-counting restrictions, please consult with your neuroscience advisors and with the advising staff for the relevant host department for the other majors/minors.