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| Presentation | 2012-07-31 13:15 Stability Analysis of Stochastic Neural Network with Depression and Facilitation Synapses Yuichi Katori (JST, Univ. Tokyuo), Yasuhiko Igarashi (Univ. Tokyo), Masato Okada (Univ. Tokyo/RIKEN), Kazuyuki Aihara (Univ. Tokyo)  NC2012-29 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | We investigate dynamical properties of a stochastic neural network model in which neurons are connected by dynamic synapses that undergo short-term depression and facilitation. In this model, the state of the neuron is described by a binary variable that represents the active or resting state of the neuron and changes stochastically. Synaptic transmission efficacy is described by variables that represent the releasable neurotransmitters and the calcium concentration of the synaptic terminal. Here, we focus on a neural network with uniform connections, and we elucidate its neural dynamics, which is influenced by dynamic synapses. We derive a macroscopic mean field model that approximates the overall behavior of the stochastic neural network. We apply stability and bifurcation analyses to the macroscopic mean field model, and we find that the network exhibits a variety of dynamical structures, including ferromagnetic and paramagnetic states, as well as an oscillatory uniform state according to the parameters that specify the noise intensity and the properties of the dynamic synapses. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Short term plasticity / Mean field model / Neural network / Bifurcation analysis / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 112, no. 168, NC2012-29, pp. 83-88, July 2012. | |
| Paper # | NC2012-29 | |
| Date of Issue | 2012-07-23 (NC) | |
| ISSN | Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | NC2012-29 |
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| Conference Information | |
| Committee | NC |
| Conference Date | 2012-07-30 - 2012-07-31 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Ritsumeikan Univ. College of Information Science and Engineering |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | General |
| Paper Information | |
| Registration To | NC |
| Conference Code | 2012-07-NC |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Stability Analysis of Stochastic Neural Network with Depression and Facilitation Synapses |
| Sub Title (in English) | |
| Keyword(1) | Short term plasticity |
| Keyword(2) | Mean field model |
| Keyword(3) | Neural network |
| Keyword(4) | Bifurcation analysis |
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| 1st Author's Name | Yuichi Katori |
| 1st Author's Affiliation | FIRST Aihara Innovative Mathematical Modelling Project, JST/Institute of Industrial Science, The University of Tokyo (JST, Univ. Tokyuo) |
| 2nd Author's Name | Yasuhiko Igarashi |
| 2nd Author's Affiliation | The University of Tokyo (Univ. Tokyo) |
| 3rd Author's Name | Masato Okada |
| 3rd Author's Affiliation | The University of Tokyo, RIKEN Brain Science Institute (Univ. Tokyo/RIKEN) |
| 4th Author's Name | Kazuyuki Aihara |
| 4th Author's Affiliation | Institute of Industrial Science, The University of Tokyo (Univ. Tokyo) |
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| Speaker | Author-1 |
| Date Time | 2012-07-31 13:15:00 |
| Presentation Time | 25 minutes |
| Registration for | NC |
| Paper # | NC2012-29 |
| Volume (vol) | vol.112 |
| Number (no) | no.168 |
| Page | pp.83-88 |
| #Pages | 6 |
| Date of Issue | 2012-07-23 (NC) |
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