Neuroscience Minor
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
Majors
Minors
Graduate Programs
Requirements
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.
| Code | Title | Hours |
|---|---|---|
| Core Requirements | ||
| NSCI 175 | Introduction 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 | ||
| Neuropsychopharmacology | ||
| 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 | ||
| Autism | ||
| Emotion | ||
| Social Neuroscience | ||
| Neuropsychobiology of Stress | ||
| Psychopathology H | ||
| Clinical Psychopharmacology | ||
| Evolution and Development of Biobehavioral Systems | ||
| Addiction | ||
| The General Linear Model in Psychology H | ||
| Applied Machine Learning in Psychology | ||
| Evolutionary Psychology | ||
Biology: | ||
| Cellular and Developmental Biology H | ||
| Mathematical Methods for Quantitative Biology and Mathematical Methods for Quantitative Biology Laboratory | ||
| Human Genetics | ||
| Biological Physics | ||
| Neurobiology | ||
| 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 | ||
Biostatistics: | ||
| Introduction to Biostatistics | ||
Chemistry: | ||
| Introduction to Biological Chemistry H | ||
Computer Science: | ||
| Discrete Structures H | ||
| Foundation of Programming H | ||
| Data Structures | ||
| Computer Organization | ||
| Bioalgorithms | ||
| 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 | ||
Mathematics: | ||
| 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 | ||
Physics: | ||
| 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 Hours | 15 | |
| H | Honors version available. An honors course fulfills the same requirements as the nonhonors version of that course. Enrollment and GPA restrictions may apply. |
| 1 | Students may receive elective credit for BMME 445 or PSYC 220, but not both. |
See the program page here for special opportunities.
