Carnegie Mellon University

Neural Computation Minor

The Minor in Neural Computation

http://www.cnbc.cmu.edu/upnc/nc_minor/

The Minor in Neural Computation is an inter college minor jointly sponsored by the School of Computer Science, the Mellon College of Science, and the Dietrich College of Humanities and Social Sciences, and is coordinated by the Center for the Neural Basis of Cognition (CNBC).

The minor in Neural Computation will require a total of five courses: four courses drawn from the four core areas (A: Neural Computation, B: Neuroscience, C: Cognitive Psychology, D: Intelligent System Analysis), one from each area, and one additional depth elective chosen from one of the core areas that is outside the student's major. The depth elective can be replaced by a one-year research project in computational neuroscience. No more than two courses can be double counted toward the student's major or other minors.

A. Neural Computation

15-386    Neural Computation   
15-387    Computational Perception   
15-883    Computational Models of Neural Systems   
85-419    Introduction to Parallel Distributed Processing  
86-375    Computational Perception  
Pitt-Mathematics-1800 Introduction to Mathematical Neuroscience

B. Neuroscience

03-362    Cellular Neuroscience   
03-363    Systems Neuroscience   
03-761    Neural Plasticity   
85-765    Cognitive Neuroscience
Pitt-Neuroscience 1000 Introduction to Neuroscience
Pitt-Neuroscience 1012 Neurophysiology

C. Cognitive Psychology

85-211    Cognitive Psychology  
85-213    Human Information Processing and Artifical Intelligence  
85-412    Cognitive Modeling  
85-419    Introduction to Parallel Distributed Processing  
85-426    Learning in Humans and Machines  
85-765    Cognitive Neuroscience

D. Intelligent System Analysis

10-601    Machine Learning  
15-381    Artificial Intelligence: Representation and Problem Solving  
15-386    Neural Computation  
15-387    Computational Perception
15-486    Artificial Neural Networks
15-494    Special Topic: Cognitive Robotics
16-299    Introduction to Feedback Control Systems
16-311    Introduction to Robotics
16-385    Computer Vision
18-290    Signals and Systems
24-352    Dynamic Systems and Controls
36-225    Introduction to Probability Theory
36-247    Statistics for Lab Sciences
36-401    Modern Regression
36-410    Introduction to Probability Modeling
42-/86-631    Neural Data Analysis
42-632    Neural Signal Processing
86-375    Computational Perception

Prerequisites

The required courses in the above four core areas require a number of basic prerequisites: basic programming skills at the level of 15-110 Principles of Computing and basic mathematical skills at the level of 21-122 Integration, Differential Equations and Approximation or their equivalents. Some courses in Area D require additional prerequisites. Area B Biology courses require, at minimum, 03-121 Modern Biology. Students might skip the prerequisites if they have the permission of the instructor to take the required courses. Prerequisite courses are typically taken to satisfy the students' major or other requirements. In the event that these basic skill courses are not part of the prerequisite or required courses of a student's major, one of them can potentially count toward the five required courses (e.g. the depth elective), conditional on approval by the director of the minor program.