{"id":33013,"date":"2018-03-09T09:29:56","date_gmt":"2018-03-09T09:29:56","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/escalas-modelos-y-tecnicas-de-simulacion-en-neurociencia-computacional\/"},"modified":"2018-03-09T09:29:56","modified_gmt":"2018-03-09T09:29:56","slug":"escalas-modelos-y-tecnicas-de-simulacion-en-neurociencia-computacional","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/matematicas\/escalas-modelos-y-tecnicas-de-simulacion-en-neurociencia-computacional\/","title":{"rendered":"Escalas, modelos y t\u00e9cnicas de simulaci\u00f3n en neurociencia computacional"},"content":{"rendered":"<h2>Tesis doctoral de <strong> Pablo Varona Mart\u00ednez <\/strong><\/h2>\n<p>En la primera parte de esta tesis, se resume el estado del arte en neurociencia computacional, se especifican las escalas de modelado y se plantean los problemas que surgen en los distintos modelos.  la segunda parte presenta a xsim, un simulador de redes neuronales capaz de implementar modelos en una amplia escala de resoluci\u00f3n. Este simulador facilita la tarea de construcci\u00f3n, ajuste y an\u00e1lisis de neuronas y redes.  en la tercera parte, se presentan tres nuevos modelos con un grado de realismo creciente: un modelo de red estoc\u00e1stica con correlaciones emergentes de largo alcance, un paradigma de integraci\u00f3n y disparo con par\u00e1metros biol\u00f3gicos, y un modelo multicompartimental de neurona piramidal ca1 del hipocampo.  en la cuarta parte, se propone una t\u00e9cnica de an\u00e1lisis de densidad de fuentes de corriente que permite restringir el espacio de par\u00e1metros de los modelos multicompartimentales. Esta t\u00e9cnica contribuye tambi\u00e9n a una correcta interpretaci\u00f3n del an\u00e1lisis de los potenciales de campo y las densidades de corriente experimentales.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Escalas, modelos y t\u00e9cnicas de simulaci\u00f3n en neurociencia computacional<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Escalas, modelos y t\u00e9cnicas de simulaci\u00f3n en neurociencia computacional <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Pablo Varona Mart\u00ednez <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Aut\u00f3noma de Madrid<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 15\/07\/1997<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Juan  Alberto Siguenza Pizarro<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: joan Cabestany i moncus\u00ed <\/li>\n<li>federico Mor\u00e1n abad (vocal)<\/li>\n<li>vicente Lopez Martinez (vocal)<\/li>\n<li>Javier Yajeya p\u00e9rez (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Pablo Varona Mart\u00ednez En la primera parte de esta tesis, se resume el estado del arte en [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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