Advanced search
Start date
Betweenand


Determinism and stochasticity in models of biological neurons

Full text
Author(s):
Boris Marin
Total Authors: 1
Document type: Doctoral Thesis
Press: São Paulo.
Institution: Universidade de São Paulo (USP). Instituto de Física (IF/SBI)
Defense date:
Examining board members:
Reynaldo Daniel Pinto; Ibere Luiz Caldas; Pablo Varona Martínez; Marcelo Bussotti Reyes; Alberto Vazquez Saa
Advisor: Reynaldo Daniel Pinto
Abstract

We investigated the origin of irregularities in the dynamics of central pattern generator neurons, through analyzing electrophysiologically realistic models. A number of parallel approaches were adopted for that purpose. Initially, we studied information coding processes in these cells and proposed a technique to determine the underlying biophysical mechanisms. We also developed a novel hybrid method (based on numerical continuation and brute force sweeps) to analyze neuronal model databases, extending them and unveiling instances of multistability between oscillatory and resting regimes. Furthermore, in order to determine the origin of irregular dynamics in simplified neuronal models, we employed geometrical methods from the theory of dynamical systems. The analysis of stochastically perturbed maps allowed us to discuss possible scenarios for the generation of chaotic behaviour in random dynamical systems. Finally we showed that, by taking noise into account, a class of conductance based models gives rise to firing patterns akin to the ones observed \\emph{in vivo}. These perturbations unveil the richness of the transient dynamics, inducing the system to populate a preexistent complex deterministic scaffolding -- without resorting to parameter fine-tuning or ad hoc constructions to induce chaotic activity. (AU)