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Circuits et systemes de modelisation analogique de neurones ...

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Résumé<strong>Circuits</strong> <strong>et</strong> systèmes <strong>de</strong> modélisation <strong>analogique</strong> <strong>de</strong> <strong>neurones</strong> biologiques.L'objectif <strong>de</strong> c<strong>et</strong>te thèse est la réalisation <strong>de</strong> calculateurs <strong>analogique</strong>s basés sur <strong>de</strong>s modèles neurophysiologiques <strong>de</strong> typeHodgkin <strong>et</strong> Huxley. Ces simulateurs sont bâtis autour d'ASICs (Application Specific Integrated <strong>Circuits</strong>) <strong>analogique</strong>sspécifiquement conçus pour résoudre ces équations. Construits avec une approche modulaire, ils perm<strong>et</strong>tent lasimulation réaliste en temps réel <strong>et</strong> continu <strong>de</strong> l'activité électrophysiologique <strong>de</strong> <strong>neurones</strong> biologiques. Afin <strong>de</strong> gar<strong>de</strong>rune souplesse d’utilisation maximale, les paramètres <strong>de</strong>s modèles <strong>et</strong> les interconnexions <strong>de</strong> ses différents éléments sontprogrammables. L’application première <strong>de</strong>s systèmes présentés est la réalisation <strong>de</strong> "réseaux hybri<strong>de</strong>s", où <strong>neurones</strong>biologiques <strong>et</strong> artificiels interagissent, <strong>de</strong>s exemples d’utilisation <strong>de</strong> c<strong>et</strong>te technique sont présentés.Mots-clés<strong>Circuits</strong> intégrés <strong>analogique</strong>s <strong>et</strong> mixtesMémoires <strong>analogique</strong>s intégréesModèles <strong>de</strong> <strong>neurones</strong>Neurones artificielsHodgkin-HuxleyRéseaux <strong>de</strong> <strong>neurones</strong>Réseaux hybri<strong>de</strong>sAbstract<strong>Circuits</strong> and systems for analog mo<strong>de</strong>ling of biological neurons.This thesis <strong>de</strong>als with the realization of analog calculators based on neurophysiological mo<strong>de</strong>ls of the Hodgkin andHuxley type. At the heart of the simulators are analog ASICs (Application Specific Integrated <strong>Circuits</strong>) specially<strong>de</strong>signed to solve those equations. They are built using a modular approach and allow for a realistic, real time andcontinuous time simulation of the neurophysiological activity of biological neurons. In or<strong>de</strong>r to achieve a maximumflexibility, param<strong>et</strong>ers of the mo<strong>de</strong>ls and connections b<strong>et</strong>ween its different elements are programmable within thesystem. The main application of the presented systems is the making of "hybrid n<strong>et</strong>works", where biological andartificial neurons interact. Some examples of the use of this technique are presented.Key wordsAnalog and mix mo<strong>de</strong> vlsiIntegrated analog memoriesMo<strong>de</strong>ls of neuronsArtificial neuronsHodgkin-HuxleyNeural n<strong>et</strong>worksHybrid N<strong>et</strong>works

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