First day of classes: August 26, 2019
Note: students in the CNBC graduate training program automatically have instructor permission to attend any of these core courses, but cross-registration procedures may apply.
Students are expected to complete all of the core courses by the end of their third year. Students are encouraged to take advantage of elective courses when they are offered.
This course will cover fundamental findings and approaches in cognitive neuroscience, with the goal of providing an overview of the field at an advanced level. Topics will include high-level vision, spatial cognition, working memory, long-term memory, learning, language, executive control, and emotion. Each topic will be approached from a variety of methodological directions, i.e. computational modeling, cognitive assessment in brain-damaged humans, non-invasive brain monitoring in humans and single-neuron recording in animals. Lecture format will be used for most sessions, with a few sessions devoted to discussion.
Special permission is required: Graduate Students, instructors permission from Carl Olson at email@example.com and once you have instructor’s permission, please see Erin Donahoe, in BH 342E or firstname.lastname@example.org to register you.
This introductory course in computational neuroscience is intended for a broad range of CNBC students, with backgrounds that may be either technical (math, engineering, statistics, etc.) or non-technical (biology, neuroscience, etc.). The course is co-taught by Brent Doiron and Rob Kass. Pitt students should register in MATH 3375; CMU students may register in 36-759. The two instructors settled on “statistical models” as a unifying theme for the many kinds of models discussed, ranging from those that describe the physiology of neurons to those that describe human behavior. Statistical ideas have been part of neurophysiology since the first probabilistic descriptions of spike trains, and the quantal hypothesis of neurotransmitter release, more than 50 years ago; they have been part of experimental psychology even longer. In broad stroke, this course will examine a few of the most important methods and claims that have come from applying statistical thinking to the brain. However, some of the topics involve tools typically taught in statistics courses, while other topics involve tools taught in math courses. Even at an intuitive level, a single course can not provide a comprehensive view of computational neuroscience; the field is too broad. Instead, by studying a series of examples, many of them very influential, students will come away with a sense of the way that computational methods contribute to contemporary understanding of neuroscience.
This course is an introductory graduate course in cellular neuroscience. As such it will assume little or no background but will rapidly progress to discussions of papers from the primarily literature. The structure of the course will be about half lectures and half discussions of new and classic papers from the primary literature. These discussions will be substantially led by students in the course. Topics covered will include ion channels and excitability, synaptic transmission and plasticity, molecular understanding of brain disease and cell biology of neurons. Assessment will be based on class participation, including performance on in-class presentations and a writing assignment.
2100- This course is the first component of the introductory graduate sequence designed to provide an overview of cellular and molecular aspects of neuroscience. This course covers protein chemistry, regulation of gene expression, nerve cell biology, signal transduction, development, and neurogenesis in a lecture format.
2101- This course is the second component of the introductory graduate sequence designed to provide an overview of cellular and molecular aspects of neuroscience. This course covers the electrical properties of neurons, signal propagation in nerve cells, and synaptic transmission.
Prerequisites: A background in basic biology and permission of the instructor are required.
Note for CMU students: Section 2 ofthe PCHE Cross Registration Request Form provides a space for students to enroll in a primary choice (course), and a secondary choice in case the primary is not available. Please register for the NROSCI sections as your primary chioce and the MSNBIO sections as your secondary choice, so that when NROSCI fills up, the Registrar’s Office will automatically put you in the MSNBIO section without having to complete any additional paperwork.
Note for non-Neuroscience students:The 2100/2101 sequence assumes a substantial background in biology. Students who lack this background and cannot devote adequate time to background reading might prefer to take Advanced Cellular Neuroscience instead.