PPT-Neural Dynamics The FitzHugh-Nagumo

v Nullcline I ap 0 W0 v 1 0 1 v 0ltWlt1 V derivative is 0 at the hash markes Connect the hash marks for all w to form the v nullcline Morris Lecar Phase Plane Red . Daselaar 12 Heather J Rice Daniel L Greenberg 13 Roberto Cabeza Kevin S LaBar and David C Rubin Department of Psychology and Neuroscience Duke University Durham NC 27708 USA Current address Swammerdam Institute for Life Sciences University of Ams L 133 SOUTH FITZHUGH STREET / ROCHESTER, NEW YORK 14608 - 2204 / 585 - 546 - 7029/ FAX: 585 - 546 - 4788 www.landmarksociety.org mail@landmarksociety.org Contact: Cindy Boyer cboyer@landmarksociety. Week 8 – Noisy . output . models:. Escape rate and soft threshold. Wulfram. Gerstner. EPFL, Lausanne, Switzerland. 8. .1. . Variation of membrane . potential. - . white noise approximation. Kong Da, Xueyu Lei & Paul McKay. Digit Recognition. Convolutional Neural Network. Inspired by the visual cortex. Our example: Handwritten digit recognition. Reference: . LeCun. et al. . Back propagation Applied to Handwritten Zip Code Recognition. What are Artificial Neural Networks (ANN)?. ". Colored. neural network" by Glosser.ca - Own work, Derivative of File:Artificial neural . network.svg. . Licensed under CC BY-SA 3.0 via Commons - https://commons.wikimedia.org/wiki/File:Colored_neural_network.svg#/media/File:Colored_neural_network.svg. presenter : Kyung-. Wha. Park . Dong-Hyun . Kwak. Biointelligence. Laboratory. Seoul National University. Morphological Computation – . Connecting Brain, Body. , and Environment. Introduction - . John Kounios, Drexel University . Mark Jung-Beeman, Northwestern University . Insight is. . sudden,…. Experiential Level: . Sudden and disconnected from preceding thought.. Behavioral Level: . Sudden availability of information about the correct response (Smith & Kounios, 1996, . of Poker AI. Christopher Kramer. Outline of Information. The Challenge. Application, problem to be solved, motivation. Why create a poker machine with ANNE?. The Flop. The hypothesis. Can a Poker AI run using only an ANNE?. 2015/10/02. 陳柏任. Outline. Neural Networks. Convolutional Neural Networks. Some famous CNN structure. Applications. Toolkit. Conclusion. Reference. 2. Outline. Neural Networks. Convolutional Neural Networks. Week 7 – Variability and Noise:. The question of . . the neural code. Wulfram. Gerstner. EPFL, Lausanne, Switzerland. 7. .1. . Variability. of . spike. trains. - . experiments. 7. .2 Sources of . Basic reference: Keener and . Sneyd. , Mathematical Physiology. Cardiac Cell. Nattel. and . Carlsson. . Nature Reviews Drug Discovery. . 5. , 1034. –. 1049 (December 2006) . Neuromuscular . Junction. For years, researchers have used the theoretical tools of engineering to understand neural systems, but much of this work has been conducted in relative isolation. In this text, Chris Eliasmith and Charles Anderson provide a synthesis of the disparate approaches in computational neuroscience, incorporating ideas from neural coding, neural computation, physiology, communications theory, control theory, dynamics, and probability theory. This synthesis, they argue, enables novel theoretical and practical insights into the functioning of neural systems. Such insights are pertinent to experimental and computational neuroscientists and to engineers, physicists, and computer scientists interested in how their quantitative tools relate to the brain. Learn to build neural network from scratch.. Focus on multi-level feedforward neural networks (multi-level . perceptrons. ). Training large neural networks is one of the most important workload in large scale parallel and distributed systems. Mark Hasegawa-Johnson. April 6, 2020. License: CC-BY 4.0. You may remix or redistribute if you cite the source.. Outline. Why use more than one layer?. Biological inspiration. Representational power: the XOR function.