he Neurobiology Graduate Training Program provides a number required and elective courses for its students. The first-year curriculum emphasizes coursework, but also allows students to spend about half of their time in laboratory rotations. Students select their thesis advisors at the end of their first year.
Required first-year courses:
- Boot Camp
- Research in Neurobiology
- Concepts in Neurobiology I
- Concepts in Neurobiology II
- Neurobiology of Disease
- Journal Club
- Student Seminar
- Neurostatistics
Required second-year courses:
- Journal Club
- Student Seminar
- Scientific Writing
- Quantitative Approaches in Neurobiology – OR – Experimental Design and Biostatistics
Additional information:
NEUROBIO 751 (NEUROSCI 751): Neuroscience Bootcamp
A two-week immersive lecture, discussion and laboratory course for graduate students in the Neurobiology Graduate Program and the Cognitive Neuroscience Admitting Program, and graduate students in allied programs at the discretion of the instructors. The Duke Neuroscience Bootcamp is designed to (1) provide a common knowledge base of neuroscience fundamentals; (2) demystify the tools of the discipline - providing hands-on experience with techniques that are commonly used to explore cellular/molecular, circuits and cognitive neuroscience.
FALL 2021: Aug 26 - Sep 19, TWThF; 9:00am – 5:00pm; Glickfeld/Grandl/Samanez-Larkin; Bryan Research, room 301; 2 Units.
Laboratory Rotations: NEUROBIO 793 Research in Neurobiology (Independent Study)
This course acquaints students with research in neuroscience and allows them to become proficient in a variety of techniques. It is an independent study in one of the laboratories of the Neurobiology Training Faculty. Students are expected to do four rotations in three semesters. (Laboratory Rotations) (up to 12 Units)s.
NEUROBIO 719: Concepts in Neuroscience I
Cellular and Molecular Neurobiology - The goal of this course is for students to gain in depth knowledge of cellular and molecular neurobiology and to learn to critically evaluate the associated primary scientific literature. This is a required core course for Neurobiology program graduate students. The course is also frequently taken by other graduate students with research interests in neuroscience including (but not limited to) those in Cognitive Neuroscience, Cell Biology, Developmental Biology, Pharmacology, Genetics, Biology, Psychology, and Biomedical Engineering.
FALL 2021: Sep 6 – Dec 8; MWF 10:15am - 11:30am; Grandl/West; Bryan Research, room 301; 5 Units.
NEUROBIO 720: Concepts in Neuroscience II
The principles of organization of neurons into functional circuits is examined through a series of 5 distinct modules, listed below. All five modules required for first-year neurobiology students.
- 720A Neuroanatomy – Overview of the general plan for the vertebrate nervous system and survey of the functional anatomy of the human brain. Hands-on examination of human brain specimens with guided explorations of external and internal brain structures and their vascular anatomy. Dissections of human brains to facilitate discovery, with use of interactive digital media to explore the gross anatomy of the central nervous system and the organization of the major neural systems underlying sensory, motor and cognitive function.
- 720B Sensory Processing: Representations and Computations – A major function of the nervous system is to generate perceptions based on input from sensory organs. This module explores how populations of neurons represent sensory information and perform computations on those signals. This question is considered at a variety of levels of the visual and auditory pathways and spans domains of inquiry from circuits to cognition.
- 720C Sensory-Motor Integration – Much of our motor activity is directed by sensory inputs. In this module, we cover the basic principles of how the brain processes and transforms sensory inputs in the service of the planning and coordination of movements. We will consider the function of both cortical and subcortical areas in motor control. Topics include the roles of the parietal and frontal cortices, movement coordination by the cerebellum, and the principles of motor skill learning. Examples are heavily drawn from eye movements while drawing parallels to other motor effector systems. Course sessions include some lecture material, but also include class discussion of strategically-chosen historical and current papers.
- 720D Learning and Memory – Our capacity to form memories and learn new behaviors is critical to survival, in part because these processes permit rapid adaptation and behavioral flexibility in the face of environmental change. In this module, we examine memory and learning by considering processes ranging from classical conditioning to spatial navigation to the cultural transmission of behaviors such as speech. These complex phenomena are viewed from cellular, circuit and systems perspectives.
- 720E Circuits and Computation – Computational neuroscience seeks to describe brains and nervous systems as information processing units that have evolved to perform the complex computations needed to solve the difficult problem humans and animals face on a daily basis. In 1976, David Marr and Tomaso Poggio summarized the computational approach to neuroscience as consisting of three complimentary levels of analysis: the computational level, the algorithmic level, and the physical level. The computational level is concerned with identifying a specific problem that an animal is trying to solve. The algorithmic level is concerned with generating an understanding of how the animal represents the problem and how the solution to that problem is generated. The physical level is concerned with the precise means by which neurons and neural circuits implement the solution in order to generate behavior. In this module, we explore computational approach to neuroscience and introduce the information theoretic tools upon which it is based. Emphasis is placed on models of neural encoding and decoding, signal detection theory, decision theory, and model neural circuits that perform evidence integration, object tracking, and binary choice.
NEUROBIO 730: Neurostatistics
Introduction to applied probability theory and statistical methods in commonly used neuroscience.
FALL 2021: Oct 5 – Nov 23; T Th 10:00am - 11:30am; Beck; Bryan Research, room 301; 1 Unit.
NEUROBIO 762: Neurobiology of Disease
Discuss given disease of the nervous system. One or two students working with a designated faculty member are responsible for an introduction (20-25 minutes) followed by a discussion of key primary papers on the subject. Two or three articles provided at least a week in advance provide a framework for discussion. Diseases covered currently include: ALS, Alzheimer's, CNS neoplasms, Epilepsy, multiple sclerosis, Parkinson's disease, retinitis pigmentosa, and stroke. We discuss key features of the disease, etiology and pathogenetic mechanisms of the disease, models available and the evidence establishing the validity of the models & therapies.
NEUROBIO 726: Neurobiology Journal Club (Seminar)
First and second year Neurobiology graduate students attend the weekly Neurobiology Invited Seminar Series. Once a month, students will meet to hold a student-run journal club to discuss the work of a speaker from an outside institution.
FALL 2021: Weekly Tu 12:00 pm – 1:15 pm; Monthly Fri 3:30pm-4:45pm; West; Bryan Research, rooms 101 and 301; 1 Unit.
NEUROBIO 790: Student Seminar
Preparation and presentation of seminars to students and faculty on topics of broad interest in neurobiology. Required of all first – and second-year Neurobiology graduate students.
FALL 2021: Aug 23 – Dec. 15; W 12:00pm – 2:30pm; Rebecca Yang/Jeremy Kay; Bryan Research, room 301; 1 Unit.
NEUROBIO 710 (CELLBIO 710): Scientific Writing: Papers and Grant Writing Workshop
Introduction to grant and fellowship writing; writing assignment of two proposal topics; evaluation and critique of proposal by fellow students.
NEUROBIO 735 Quantitative Approaches in Neurobiology
The three modules of this course provides 1) basic training in computer programming (using Matlab), 2) grounding in the principles of statistics needed for neurobiology, and 3) an introduction to computational neuroscience.
- The Programming module assumes students are familiar with basic principles of computer programming at the level of an introductory undergraduate course (variables, loops, functions). Students without this background should consult with the instructor, as materials covering these concepts are available online and should be completed prior to the start of class. Classwork focuses on real-world examples of neuroscience data analysis from loading data to producing figures.
- The Statistics module provides a firm grounding in the principles on which statistical analysis of neuroscience data is based.
- The Theory model gives the students experience in developing simple computational models of neurons or of the nervous system.
-OR-
NEUROBIO 733 Experimental Design and Biostatistics for Basic Biomedical Scientists
The use and importance of statistical methods in laboratory science, with an emphasis on the “nuts and bolts” of experimental design, hypothesis testing, and statistical inference. Central tendency and dispersion, Gaussian and Non-Gaussian distribution, parametric and non-parametric tests, uni- and multivariate, ANOVA and regression procedures are covered. Students present their own data and literature examples in addition to lectures.
Graduate Student Teaching
Students are required to teach for a minimum of one semester. This experience is an important part of training for a career in neurobiology. Student teaching will vary as courses in the department evolve, but can be expected to include the Boot Camp, graduate neurobiology courses, or undergraduate neurobiology courses.
Elective Courses
NEUROSCI 267 Neuroethics
NEUROSCI 360 Drugs, Brain, and Behavior
NEUROSCI 366S Behavioral Neuroendocrinology
NEUROSCI 373 Behavioral Neuroimmunology
NEUROSCI 470S Cognitive Neuroscience of Memory
NEUROSCI 518S Natural Neurotoxins
NEUROSCI 533 Essentials of Pharmac. and Toxicology
NEUROSCI 567 Theoretical Neuroscience
NEUROSCI 773S Reward and the Brain
NEURO 405C The Neurobiology of Aging
NEUROSUR 404C Neuro-Oncology
ECE 661 Machine Learning and Deep Neural Nets
BME 260L Modeling Cellular and Molecular Systems
BME 301L Bioelectricity
BME 515 Neural Prosthetic Systems
BME 518L Modern Neuroscience Tools
BME 601L Introduction to Neural Engineering
BME 804 Developments in Neural Engineering