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1 - 10 of 13 results for: NBIO

NBIO 101: Social and Ethical Issues in the Neurosciences (NBIO 201)

Foundational scientific issues and philosophical perspectives related to advances in the study of brain and behavior. Implications of new insights from the neurosciences for medical therapy, social policy, and broader conceptions of human nature including consciousness, free will, personal identity, and moral responsibility. Topics include ethical issues related to genetic screening and editing, desire and addiction, criminal behavior, the biology of sexuality, fetal pain, aging and neurodegenerative disease, brain-computer interfaces, and neural enhancement and the human future. May be taken for 2 units without a research paper. Undergraduates must enroll in NBIO101. This course must be taken for a minimum of 3 units and a letter grade to be eligible for Ways credit. Application required: http://bit.ly/NBIOApplication
Terms: Spr | Units: 2-3 | UG Reqs: WAY-ER

NBIO 198: Directed Reading in Neurobiology

Prerequisite: consent of instructor. (Staff)
Terms: Aut, Win, Spr, Sum | Units: 1-18 | Repeatable for credit

NBIO 199: Undergraduate Research

Investigations sponsored by individual faculty members. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr, Sum | Units: 1-18 | Repeatable for credit

NBIO 201: Social and Ethical Issues in the Neurosciences (NBIO 101)

Terms: Spr | Units: 2-3

NBIO 206: The Nervous System

Structure and function of the nervous system, including neuroanatomy, neurophysiology, and systems neurobiology. Topics include the properties of neurons and the mechanisms and organization underlying higher functions. Framework for general work in neurology, neuropathology, clinical medicine, and for more advanced work in neurobiology. Lecture and lab components must be taken together.
Terms: Win | Units: 6

NBIO 215: Current Controversies and Emerging Technologies in Applied Neuroscience (ANES 215, NEPR 215)

In this survey course we invite speakers form neuroscience disciplines such as psychiatry, nerurology, neurosurgery, anesthesiology and more to discuss innovative work and recent controversies in the field. We center the discussion around critical reading of published work in clinical and preclinical studies. This survey course meets the requirement for the Neuroscience scholarly concentration for the medical scholars research program.
Terms: Win | Units: 1

NBIO 220: Machine Learning Methods for Neural Data Analysis (CS 339N, STATS 220, STATS 320)

With modern high-density electrodes and optical imaging techniques, neuroscientists routinely measure the activity of hundreds, if not thousands, of cells simultaneously. Coupled with high-resolution behavioral measurements, genetic sequencing, and connectomics, these datasets offer unprecedented opportunities to learn how neural circuits function. This course will study statistical machine learning methods for analysing such datasets, including: spike sorting, calcium deconvolution, and voltage smoothing techniques for extracting relevant signals from raw data; markerless tracking methods for estimating animal pose in behavioral videos; network models for connectomics and fMRI data; state space models for analysis of high-dimensional neural and behavioral time-series; point process models of neural spike trains; and deep learning methods for neural encoding and decoding. We will develop the theory behind these models and algorithms and then apply them to real datasets in the homeworks and final project.This course is similar to STATS215: Statistical Models in Biology and STATS366: Modern Statistics for Modern Biology, but it is specifically focused on statistical machine learning methods for neuroscience data. Prerequisites: Students should be comfortable with basic probability ( STATS 116) and statistics (at the level of STATS 200). This course will place a heavy emphasis on implementing models and algorithms, so coding proficiency is required.
Last offered: Winter 2023

NBIO 227: Understanding Techniques in Neuroscience

Students will learn to select and evaluate multidisciplinary techniques for approaching modern neuroscience questions. A combination of lectures and small group paper discussions will introduce techniques from molecular, genetic, behavioral, electrophysiological, imaging, and computational neuroscience. Students will be expected to complete homework assignments analyzing primary literature and attend optional laboratory demonstrations. Intended for graduate students, postdocs, and staff from any discipline; and for advanced undergraduates in the biosciences, engineering, or medicine.
Terms: Aut | Units: 2

NBIO 228: Mathematical Tools for Neuroscience

Student-instructed. This course aims to equip biosciences graduate students with the fundamental skills in quantitative modeling and data analysis necessary for neuroscience research. It covers techniques including linear algebra, Fourier transforms, probability and statistics, signal detection, statistical inference, and information theory. The course is required for first-year students in the Neuroscience PhD program, and is open to other graduate students in the biosciences. Other students, including undergraduates, may enroll by special request.
Terms: Spr | Units: 3

NBIO 254: Principles of Neurobiology (BIO 254)

For graduate students. Includes lectures with BIO 154 and additional paper discussion sections. Principles and mechanisms in the organization and functions of the nervous system. Topics: neuronal communication, sensory and motor systems, innate behaviors, learning and memory, brain disorders, and evolution of the nervous system.
Last offered: Winter 2023
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