This thesis applies the great advances of modern dynamical systems theory
(DST) to consciousness. Consciousness, or subjective experience, is faced
here in two different ways: from the global dynamics of the human brain and
from the integrated information theory (IIT), one of the currently most prestigious theories on consciousness. Before that, a study of a numerical simulation of a network of individual neurons justifies the use of the Lotka-Volterra
model for neurons assemblies in both applications. All these proposals are
developed following this scheme:
• First, summarizing the structure, methods and goal of the thesis.
• Second, introducing a general background in neuroscience and the global
dynamics of the human brain to better understand those applications.
• Third, conducting a study of a numerically simulated network of neurons. This network, which displays brain rhythms, can be employed,
among other objectives, to justify the use of the Lotka-Volterra model
for applications.
• Fourth, summarizing concepts from the mathematical DST such as
the global attractor and its informational structure, in addition to its
particularization to a Lotka-Volterra system.
• Fifth, introducing the new mathematical concepts of model transform
and instantaneous parameters that allow the application of simple mathematical models such as Lotka-Volterra to complex empirical systems
as the human brain.
• Sixth, using the model transform, and specifically the Lotka-Volterra
transform, to calculate global attractors and informational structures
in global dynamics of the human brain.
• Seventh, knowing the probably most prestigious theory on consciousness, the IIT developed by G. Tononi.
• Eighth, using informational structures to develop a continuous version of IIT.
And ninth, establishing some final conclusions and commenting on new
open questions from this work.
These nine points of this scheme correspond to the nine chapters of this thesis
