Neuroscience Minor

Department of Psychology and Neuroscience

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Davie Hall, CB# 3270

(919) 843-0174

Donald T. Lysle, Chair

Regina M. Carelli, Associate Chair

Karen Gil, Associate Chair

Jeannie Loeb, Director of Undergraduate Studies

Desiree Griffin, Director of Undergraduate Psychology Advising

Kelly Giovanello, Director of Neuroscience Curricula

Rachel Penton, Director of Undergraduate Neuroscience Advising

Peter Gordon, Director of Cognitive Science Minor

Kaitlin Blakemore, Student Services Manager

Christopher Coffey, Undergraduate Instructional Program Coordinator

The minor is open to all students, including psychology majors. However, students should note that they are limited to no more than 45 credit hours within a specific department. Students must earn a grade of C or better in at least four of the five courses.

Department Programs



Graduate Programs


In addition to the program requirements listed below, students must:

  • take at least nine hours of their minor "core" requirements at UNC–Chapel Hill
  • earn a minimum of 12 hours of C or better in the minor (some minors require more)

For more information, please consult the degree requirements section of the catalog.

Core Requirements
NSCI 175Introduction to Neuroscience (with a grade of C or better)3
Four courses distributed over at least two academic departments, selected from the following lists:12
Psychology and Neuroscience:
Learning H
Sensation and Perception H
Neuroscience of Psychiatric Disorders
Animal Behavior
Advanced Biopsychology Laboratory H
Advanced Molecular Neuropharmacology
History of Neuroscience
Functional Neuroanatomy
Principles of Brain Circuits
Genetics of Brain Diseases
Neurotechnology in Modern Neuroscience Research
Neural Connections: Hands on Neuroscience
Neurobiology of Aging
Neuroscience, Society, and the Media
Cognitive Neuroscience
Neurobiology of Learning and Memory
Social Neuroscience
Neuropsychobiology of Stress
Psychopathology H
Clinical Psychopharmacology
Evolution and Development of Biobehavioral Systems
The General Linear Model in Psychology H
Applied Machine Learning in Psychology
Evolutionary Psychology
Cellular and Developmental Biology H
Mathematical Methods for Quantitative Biology
and Mathematical Methods for Quantitative Biology Laboratory
Human Genetics
Biological Physics
Comparative Physiology
Behavioral Neuroscience
Sensory Neurobiology and Behavior
Synaptic Plasticity: Analysis of Primary Literature
Behavioral Endocrinology
Mathematical and Computational Models in Biology
Introduction to Computational Neuroscience
Light Microscopy for the Biological Sciences
Biomedical Engineering:
Biomedical Electronics
Human Physiology : Electrical Analysis
Systems Neuroscience 1
Medical Imaging I: Ultrasonic, Optical, and Magnetic Resonance Systems
Introduction to Biostatistics
Introduction to Biological Chemistry H
Computer Science:
Discrete Structures H
Foundation of Programming H
Data Structures
Computer Organization
Artificial Intelligence
Introduction to Machine Learning
Mathematics for Image Computing
Introduction to Robotics H
Computer Networks
Parallel and Distributed Computing
Computational Geometry
Images, Graphics, and Vision
Exercise and Sport Science:
Human Anatomy
Human Physiology
Neuromuscular Control and Learning
Calculus of Functions of Several Variables H
Linear Algebra for Applications
First Course in Differential Equations H
Functions of a Complex Variable with Applications
Mathematical Methods for the Physical Sciences I
Mathematical Methods for the Physical Sciences II
Introduction to Probability
Mathematical and Computational Models in Biology
Introduction to Dynamics
Mathematical Modeling in the Life Sciences
Introduction to Numerical Analysis
Linear Algebra
Scientific Computation I
Scientific Computation II
Methods of Applied Mathematics I
Methods of Applied Mathematics II
How Bio Works
Biological Physics
Statistics and Operations Research:
Foundations of Decision Sciences
Introduction to Optimization
Introduction to Probability
Stochastic Modeling
Methods of Data Analysis
Mathematical Statistics
Advanced Methods of Data Analysis
Machine Learning
Total Hours15

Honors version available. An honors course fulfills the same requirements as the nonhonors version of that course. Enrollment and GPA restrictions may apply.

See the program page here for special opportunities.