Neuroscience Minor
Neuroscience embodies the liberal arts experience because it draws on techniques and findings from several academic disciplines including biology, chemistry, computer science, exercise and sports science, mathematics, physics, and psychology. The neuroscience minor provides undergraduate students the opportunity to obtain fundamental knowledge and exposure needed to pursue careers and post-graduate studies in fields related to psychology, human development and aging, health and disease, rehabilitation, biomedical research, human-machine interactions, and other emerging disciplines.
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.
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 cumulative GPA of 2.000 in the minor core requirements. Some programs may require higher standards for minor or specific courses.
For more information, please consult the degree requirements section of the catalog.
Code | Title | Hours |
---|---|---|
Core Requirements | ||
NSCI 175 | 3 | |
Four courses distributed over at least three academic departments, selected from the following lists: | 12 | |
Psychology and Neuroscience: | ||
Neuropsychopharmacology | ||
Learning H | ||
Sensation and Perception H | ||
Any NSCI course numbered between 300-699 1 | ||
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 | ||
Applied Physical Sciences: | ||
Developing Your Sixth Sense: Designing Sensors and Electrical Circuits to Make Measurements | ||
Data Science for Applied Science and Engineering | ||
Optical Instrumentation for Scientists and Engineers | ||
Nanophotonics | ||
Biology: | ||
Cellular and Developmental Biology H | ||
The Mathematics of Life and The Mathematics of Life Laboratory | ||
Mathematical Methods for Quantitative Biology and Mathematical Methods for Quantitative Biology Laboratory | ||
Human Genetics | ||
Biological Physics | ||
Neurobiology | ||
Comparative Physiology | ||
Molecular Control of Metabolism and Metabolic Disease | ||
Behavioral Neuroscience | ||
Sensory Neurobiology and Behavior | ||
Sex Differences in Human Disease | ||
Exploring Brain, Gut, and Immunity H | ||
Synaptic Plasticity: Analysis of Primary Literature | ||
Behavioral Endocrinology | ||
Mathematical and Computational Models in Biology | ||
Introduction to Computational Neuroscience | ||
Biomedical Engineering: | ||
Biomedical Electronics | ||
Human Physiology: Electrical Analysis | ||
Systems Neuroscience | ||
Medical Imaging I: Ultrasonic, Optical, and Magnetic Resonance Systems | ||
Chemistry: | ||
Introduction to Biological Chemistry H | ||
Computer Science: | ||
or COMP 116 | Introduction to Scientific Programming | |
Data Structures and Analysis | ||
Systems Fundamentals | ||
Foundations of Programming | ||
Computer Organization | ||
Bioalgorithms | ||
Artificial Intelligence | ||
Introduction to Machine Learning H | ||
Mathematics for Image Computing | ||
Introduction to Robotics H | ||
Networked and Distributed Systems | ||
Parallel and Distributed Computing | ||
Computational Geometry | ||
Images, Graphics, and Vision | ||
Exercise and Sport Science: | ||
Human Anatomy and Physiology I | ||
Human Anatomy and Physiology II | ||
Human Physiology | ||
Neuromuscular Control and Learning | ||
Neuromechanics of Human Movement | ||
Mathematics: | ||
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: | ||
Introduction to Optimization | ||
Introduction to Probability | ||
Stochastic Modeling | ||
Methods of Data Analysis | ||
Probability for Data Science | ||
Mathematical Statistics | ||
Time Series 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. |
F | FY-Launch class sections may be available. A FY-Launch section fulfills the same requirements as a standard section of that course, but also fulfills the FY-SEMINAR/FY-LAUNCH First-Year Foundations requirement. Students can search for FY-Launch sections in ConnectCarolina using the FY-LAUNCH attribute. |
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