Fundamentals Of Computational Neuroscience 2e
Fundamentals of ComputationalNeuroscience 2eDecember 13, 2009Chapter 1: Introduction
What is Computational Neuroscience?
What is Computational Neuroscience?Computational Neuroscience is the theoretical studyof the brain to uncover the principles and mechanismsthat guide the development, organization, informationprocessing and mental abilities of the nervous system.
Computational/theoretical tools in linear dynamicsInformation obiologyApplicationsNewquestions
Levels of organizations in the nervous systemLevels of OrganizationExamplesScaleExamples10 mPeople1mCNSComplementarymemorysystemPFCPMC10 cmSelf-organizingmapSystemHCMPCompartmentalmodel1 cmMaps1 mmNetworks100 mmNeuronsEdgedetector 1 μmAmino acidH2 NHOCCROH1A SynapsesMolecules Vesiclesand ionchannels
What is a model?
What is a model?yx
What is a model?yxModels are abstractions of real world systems orimplementations of hypothesis to investigate particularquestions about, or to demonstrate particular featuresof, a system or hypothesis.
Is there a brain theory?
Marr’s approach1. Computational theory: What is the goal of the computation,why is it appropriate, and what is the logic of the strategy bywhich it can be carried out?2. Representation and algorithm: How can this computationaltheory be implemented? In particular, what is therepresentation for the input and output, and what is thealgorithm for the transformation?3. Hardware implementation: How can the representation andalgorithm be realized physically?Marr puts great importance to the first level:”To phrase the matter in another way, an algorithm islikely to be understood more readily by understanding thenature of the problem being solved than by examining themechanism (and hardware) in which it is embodied.”
A computational theory of the brain: The anticipating brainThe brain is an anticipating memory system. It learnsto represent the world, or more specifically,expectations of the world, which can be used togenerate goal directed nEnvironmentConcepts
Overview of chaptersBasic neuronsChapter 2: Membrane potentials and spikesChapter 3: Simplified neurons andpopulation nodesChapter 4: Synaptic plasticityBasic networksChapter 5:Chapter 6:Chapter 7:Chapter 8:Random networksFeedforward networkCompetitive networksPoint attractor networksSystem-level modelsChapter 9: Modular modelsChapter 10: Hierarchical models
Further ReadingsPatricia S. Churchland and Terrence J. Sejnowski, 1992, Thecomputational Brain, MIT PressPeter Dayan and Laurence F. Abbott 2001, Theoretical Neuroscience, MITPressJeff Hawkins with Sandra Blakeslee 2004, On Intelligence, Henry Holt andCompanyNorman Doidge 2007, The Brain That Changes Itself: Stories ofPersonal Triumph from the Frontiers of Brain Science, James H.Silberman BooksPaul W. Glimcher 2003, Decisions, Uncertainty, and the Brain: TheScience of Neuroeconomics, Bradford Books
QuestionsWhat is a model?What are Marr’s three levels of analysis?What is a generative model?
Fundamentals of Computational Neuroscience 2e December 13, 2009 Chapter 1: Introduction. What is Computational Neuroscience? Computational Neuroscience is the theoretical study of the brain to uncover the principles and mechani
computational neuroscience, machine learning, and neural network theory (i.e., connectionism). The ideal CCN model should not make any assumptions that are known to contradict the current neuroscience literature and at the same time provide good accounts of behavior and at least some neuroscience
Introduction to Applied Neuroscience Objective: Fundamentals of Neuroscience Agenda: 1. Logistics 2. Computational Neuroscience 3. Neurobiology Name Grade Location What is something you would like to learn in
Neuroscience in Autobiography, is the first major publishing venture by the Society for Neuroscience after The Journal of Neuroscience. The book proj-ect was prepared with the active cooperation of the Committee on the His-tory of Neuroscience, which serves as an editorial board for the project. The
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Fundamentals of Neural Network Modeling: Neuropsychology and Cognitive Neuroscience, edited by Randolph W. Parks, Daniel S. Levine, and Debra . Computational neuroscience is an approach to understanding the infor-mation content
Course/Research Handbook. 2016-2017 . Majoring in Neuroscience at Lafayette . Neuroscience is an interdisciplinary field exploring the development, structure, and behavioral consequences of nervous systems. The B.S. Program in Neuroscience at Lafayette educates students about the nervous system from a variety of scientific
based beverages with added sugar, such as; non-diet soft drinks, energy drinks, fruit drinks, sports drinks, flavoured water and cordial. This does not include 100% fruit juice, flavoured milk, or sugared tea/coffee. 3.1 Consumption Over three-quarters (76%) of respondents reported having consumed a sugar-sweetened beverage in the three months prior to the survey, most commonly on a weekly .
