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1 - 10 of 14 results for: NENS

NENS 67N: Intracellular Trafficking and Neurodegeneration

Preference to freshmen. Cell structures and functions, the intracellular trafficking system that maintains exchanges of materials and information inside cells, and clinical features and pathologies of neurodegenerative diseases. Techniques for examining cellular and subcellular structures, especially cytoskeletons; functional insights generated from structural explorations. Prerequisite: high school biology.
Terms: Win, Sum | Units: 3 | UG Reqs: WAY-SMA
Instructors: Yang, Y. (PI)

NENS 199: Undergraduate Research

Students undertake research sponsored by an individual faculty member. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr, Sum | Units: 1-18 | Repeatable for credit

NENS 202: Longevity (HUMBIO 149L, PSYCH 102)

Interdisciplinary. Challenges to and solutions for the young from increased human life expectancy: health care, financial markets, families, work, and politics. Guest lectures from engineers, economists, geneticists, and physiologists.
Last offered: Winter 2016

NENS 204: Stroke Seminar

Standing at the intersection of many fields of medicine, including neurology, internal medicine, cerebrovascualr surgery, diagnostic and interventional radiology, and emergency medicine, as the third leading cause of death and the leading cause of disability, stroke is a critical topic for all practitioners of medicine. This seminar draws upon Stanford's leaders in stroke research to present and discuss the causes, presentation, treatment, and imaging characteristics of the disease.
Terms: Win | Units: 1 | Repeatable for credit

NENS 205: Neurobiology of Disease Seminar

Case demonstrations of selected disorders, discussion of the pathophysiological basis of the disorder, presentation of the basic principles underlying modern diagnostic and therapeutic management, and a discussion of recent research advances for each disease entity. Prerequisite: Neurobiology 206 or consent of instructor.
Terms: Win | Units: 3

NENS 206: Introduction to Neurology Seminar

Exploration of aspects of neurology, including subspecialties. Current issues, clinical cases, and opportunities in the field.
Terms: Aut | Units: 1 | Repeatable for credit
Instructors: Nguyen, V. (PI)

NENS 207: Neuroscience Core Curriculum: Translational Neuroscience (NEPR 214)

Emphasis on basic and preclinical research in selected categories of neurological disease, and understanding how these discoveries are being translated into therapies. Readings include primary scientific literature in mechanisms of disease and translational approaches and selected current reviews. Enrollment limited to 20 students. For first year Neuroscience graduate students, open to other graduate students as space permits with preference given to Neurosciences students .
Terms: Spr | Units: 2

NENS 220: Computational Neuroscience

Computational approaches to neuroscience applied at levels ranging from neurons to networks. Addresses two central questions of neural computation: How do neurons compute; and how do networks of neurons encode/decode and store information? Focus is on biophysical (Hodgkin-Huxley) models of neurons and circuits, with emphasis on application of commonly available modeling tools (NEURON, MATLAB) to issues of neuronal and network excitability. Issues relevant to neural encoding and decoding, information theory, plasticity, and learning. Fundamental concepts of neuronal computation; discussion focus is on relevant literature examples of proper application of these techniques. Final project. Recommended for Neuroscience Program graduate students; open to graduate, medical, and advanced undergraduate students with consent of instructor. Prerequisite: NBIO 206. Recommended: facility with linear algebra and calculus.
Last offered: Spring 2016

NENS 222: Dance, Movement and Medicine: Immersion in Dance for PD (DANCE 100)

Combining actual dancing with medical research, this Cardinal Course investigates the dynamic complementary relationship between two practices, medicine and dance, through the lens of Parkinson's disease (PD), a progressive neurological disease that manifests a range of movement disorders. "Dance for PD" is an innovative approach to dancing --and to teaching dance --for those challenged by PD. Course format consists of: 1. Weekly Lecture/Seminar Presentation: Partial list of instructors include Ms. Frank, Dr. Bronte-Stewart and other Stanford medical experts & research scientists, David Leventhal (Director, "Dance for PD") and Bay Area "Dance for PD" certified master teachers, film-maker Dave Iverson, Damara Ganley, and acclaimed choreographers Joe Goode, Alex Ketley, Judith Smith (AXIS Dance). 2. Weekly Dance Class: Stanford students will fully participate as dancers, and creative partners, in the Stanford Neuroscience Health Center's ongoing "Dance for Parkinson's" community dance class for people with PD. This Community Engaged Learning component provides opportunity to engage meaningfully with people in the PD community. Dancing together weekly, students will experience firsthand the embodied signature values of "Dance for PD" classes: full inclusion, embodied presence, aesthetic and expressive opportunity for creative engagement, and community-building in action. A weekly debriefing session within Friday's class time will allow students to integrate seminar material with their movement experiences.nnNO PRE-REQUISITES: No prior dance experience required. Beginners are welcome.
Terms: Win | Units: 1-2 | Repeatable for credit

NENS 230: Analysis Techniques for the Biosciences Using MATLAB

Data analysis and visualization techniques commonly encountered in biosciences research. Fundamentals of the MATLAB computing environment, programming and debugging, data import/export, data structures, plotting, image analysis, introduction to statistical tools. Examples and assignments draw from a range of topics applicable to bioscience research: frequency analysis, genetic data mining, ion channel kinetics, neural spike rasters and spike-triggered averages, cell counting in fluorescence images, regression, PCA, and stochastic simulation. Assignments are practical in nature and demonstrate how to implement specific analyses that a biosciences student is likely to encounter. Assumes no previous programming experience.
Terms: Aut | Units: 2
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