Surveys the molecular and cellular mechanisms of neuronal communication. Covers ion channels in excitable membrane, synaptic transmission, and synaptic plasticity. Correlates the properties of ion channels and synaptic transmission with their physiological function such as learning and memory. Discusses the organizational principles for the formation of functional neural networks at synaptic and cellular levels.
A short introduction to writing Content MathML by hand. It covers tokens, prefix notation, and applying functions and operators. In addition it introduces writing derivatives, integrals, vectors, and matrices.
Subject:
Mathematics and Statistics, Science and Technology
This module serves as an introduction to the Continuous Random Variables chapter in the Elementary Statistics textbook. The original module by S. Dean and B. Illowsky has been revised; concepts removed from the original version of module are discussed in R. Bloom's module Continuous Random Variables: Properties of Continuous Probability Distributions
In this module the student will explore the properties of data with a uniform distribution. The original module of practice problems for the Uniform distribution in Collaborative Statistics by Dr. Barbara Illowsky and Susan Dean has been modified by removing the problems involving conditional probability.
This module examines the properties of the continuous Uniform probability distribution, which describes a set of continuous data for which all intervals of values having the same length are equally likely. This revision is based on the original module in the textbook collection Collaborative Statistics by S. Dean and Dr. B. Illowsky; the last example in the original module was replaced with a new example.
Motion is vital to life, and to science. This unit will help you to understand why classical motion is probably the most fundamental part of physics. You will examine motion along a line and the ways in which such motion can be represented, through the use of graphs, equations and differential calculus.
This book covers the following topics: Sequences, limits, and difference equations; functions and their properties; best affine approximations; integration; polynomial approximations and Taylor series; transcendental functions; the complex plane; differential equations.
This module describes the properties of a hypergeometric experiment and hypergeometric probability distribution. This module is included in the Collaborative Statistics textbook/collection as an optional lesson
Since the discovery of the structure of the DNA double helix in 1953 by Watson and Crick, the information on detailed molecular structures of DNA and RNA, namely, the foundation of genetic material, has expanded rapidly. This discovery is the beginning of the "Big Bang" of molecular biology and biotechnology. In this seminar, students discuss, from a historical perspective and current developments, the importance of pursuing the detailed structural basis of genetic materials.
This team taught, multidisciplinary course covers the fundamentals of magnetic resonance imaging relevant to the conduct and interpretation of human brain mapping studies. The challenges inherent in advancing our knowledge about brain function using fMRI are presented first to put the work in context. The course then provides in depth coverage of the physics of image formation, mechanisms of image contrast, and the physiological basis for image signals. Parenchymal and cerebrovascular neuroanatomy and application of sophisticated structural analysis algorithms for segmentation and registration of functional data are discussed. Additional topics include fMRI experimental design including block design, event related and exploratory data analysis methods, building and applying statistical models for fMRI data. Human subjects issues including informed consent, institutional review board requirements and safety in the high field environment are presented.
" This team-taught multidisciplinary course provides information relevant to the conduct and interpretation of human brain mapping studies. It begins with in-depth coverage of the physics of image formation, mechanisms of image contrast, and the physiological basis for image signals. Parenchymal and cerebrovascular neuroanatomy and application of sophisticated structural analysis algorithms for segmentation and registration of functional data are discussed. Additional topics include: fMRI experimental design including block design, event related and exploratory data analysis methods, and building and applying statistical models for fMRI data; and human subject issues including informed consent, institutional review board requirements and safety in the high field environment. Additional Faculty Div Bolar Dr. Bradford Dickerson Dr. John Gabrieli Dr. Doug Greve Dr. Karl Helmer Dr. Dara Manoach Dr. Jason Mitchell Dr. Christopher Moore Dr. Vitaly Napadow Dr. Jon Polimeni Dr. Sonia Pujol Dr. Bruce Rosen Dr. Mert Sabuncu Dr. David Salat Dr. Robert Savoy Dr. David Somers Dr. A. Gregory Sorensen Dr. Christina Triantafyllou Dr. Wim Vanduffel Dr. Mark Vangel Dr. Lawrence Wald Dr. Susan Whitfield-Gabrieli Dr. Anastasia Yendiki "
Fevers are a sign of infection, but they may also be part of the cure. This drawing illustrates Matthew Kluger's lizard study, which supports the notion that fever can be beneficial.
Subject assesses the relationships between sequence, structure, and function in complex biological networks as well as progress in realistic modeling of quantitative, comprehensive functional-genomics analyses. Topics include: algorithmic, statistical, database, and simulation approaches; and practical applications to biotechnology, drug discovery, and genetic engineering. Future opportunities and current limitations critically assessed. Problem sets and project emphasize creative, hands-on analyses using these concepts. From the course home page: In addition to the regular lecture sessions, supplementary sections are scheduled to address issues related to Perl, Mathematica and biology.
A rigorous introduction designed for mathematicians into perturbative quantum field theory, using the language of functional integrals. Basics of classical field theory. Free quantum theories. Feynman diagrams. Renormalization theory. Local operators. Operator product expansion. Renormalization group equation. The goal is to discuss, using mathematical language, a number of basic notions and results of QFT that are necessary to understand talks and papers in QFT and string theory.
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