Maidana Capitán, Melisa (2013) Codificación en sistemas neuronales estocásticos. / Neural code in stochastic systems. Maestría en Ciencias Físicas, Universidad Nacional de Cuyo, Instituto Balseiro.
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Resumen en español
Una neurona es una célula excitable eléctricamente. Las excitaciones se producen en forma de disparos del potencial de membrana los cuáles pueden dar lugar a ráfagas. Las ráfagas pueden sucederse por dos motivos, el primero es que la dinámica neuronal incluya variables aleatorias y el segundo que el mecanismo intrínseco tenga una variable cuya constante temporal sea más lenta a las demás (corriente lenta). Cuando a un sistema con ráfagas intrínsecas se le agregan variables externas aleatorias la dinámica pierde periodicidad, y la longitud de las ráfagas se vuelve variable. Estas variaciones en la longitud de las ráfagas son las que codifican información del estímulo que llega a la neurona. En el presente trabajo se estudiaron las características de los estímulos que generan ráfagas con un determinado número de disparos en el caso de neuronas con ráfagas intrínsecas y se compararon los resultados con aquellos que surgen netamente de estímulos estocásticos. Para tal fin, se simuló un modelo neuronal basado en conductancias y se realizaron análisis por correlación inversa para el sistema con y sin corriente lenta. Se observaron diferencias cualitativas en los estímulos que generan ráfagas para los casos con y sin corriente lenta, principalmente en el estímulo que precede la finalizaci ón de la ráfaga. Además se observaron diferencias significativas en las direcciones de mayores variación del estímulo externo en ambos casos.
Resumen en inglés
Neurons are excitable cells. Excitations are mediated by rapid fluctuations of the membrane potential, which can be sustained in time (tonic firing), or interrupted by silent periods (burst firing). Two different mechanisms can generate bursting. The first mechanism requires a slow internal variable, periodically modulating the excitability of the cell. The bursting behavior thus generated is perfectly regular, all bursts containing the same number of spikes. The second mechanism relies on the presence of a stochastic external input inducing transitions between two stable attractors of the underlying dynamical system. In this case, the length of each burst fluctuates in time, and fluctuations encode the time course of the stochastic component of the input. In this work we compared the dynamic and computational properties of both mechanisms. We constructed conductance-based model neurons where slow internal currents could be switched on and off, and stimulated them with stochastic currents. The resulting spiking activity was analyzed through reverse correlation. We observed qualitative differences between the stimulus features that regulate bursting in neurons with and without the slow internal current. The most prominent difference involved the stimulus features inducing burst termination, although significant differences were also detected in the temporal course of the stimulus inducing burst generation.
| Tipo de objeto: | Tesis (Maestría en Ciencias Físicas) |
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| Palabras Clave: | Bioelectricity; Bioelectricidad; Nerve cells; Celulas nerviosas; Neuron; Neurona; Spike; Burst; Ráfaga |
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| Materias: | Biología > Biología celular Medicina > Neurociencias |
| Divisiones: | Gcia. de área de Investigación y aplicaciones no nucleares > Gcia. de Física > Sistemas complejos y altas energías > Física estadística interdisciplinaria |
| Código ID: | 429 |
| Depositado Por: | Marisa G. Velazco Aldao |
| Depositado En: | 19 Mar 2014 15:02 |
| Última Modificación: | 19 Mar 2014 15:02 |
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