A Model for the Origin and Properties of Flicker-Induced Geometric Phosphenes

We present a model for flicker phosphenes, the spontaneous appearance of geometric patterns in the visual field when a subject is exposed to diffuse flickering light. We suggest that the phenomenon results from interaction of cortical lateral inhibition with resonant periodic stimuli. We find that the best temporal frequency for eliciting phosphenes is a multiple of intrinsic (damped) oscillatory rhythms in the cortex. We show how both the quantitative and qualitative aspects of the patterns change with frequency of stimulation and provide an explanation for these differences. We use Floquet theory combined with the theory of pattern formation to derive the parameter regimes where the phosphenes occur. We use symmetric bifurcation theory to show why low frequency flicker should produce hexagonal patterns while high frequency produces pinwheels, targets, and spirals

Modeling, Analysis and Numerical Simulations in Mathematical Biology of Traveling Waves, Turing Instability and Tumor Dynamics

The dissertation includes three topics in mathematical biology. They are traveling wave solutions in a chain of periodically forced coupled nonlinear oscillators, Turing instability in a HCV model and tumor dynamics. Motivated by earlier studies of artificial perceptions of light called phosphenes, we analyze traveling wave solutions in a chain of periodically forced coupled nonlinear oscillators modeling this phenomenon. We examine the discrete model problem in its co-traveling frame and systematically obtain the corresponding traveling waves in one spatial dimension. Direct numerical simulations as well as linear stability analysis are employed to reveal the parameter regions where the traveling waves are stable, and these waves are, in turn, connected to the standing waves analyzed in earlier work. We also consider a two-dimensional extension of the model and demonstrate the robust evolution and stability of planar fronts and annihilation of radial ones. Finally, we show that solutions that initially feature two symmetric fronts with bulged centers evolve in qualitative agreement with experimental observations of phosphenes. For hepatitis C virus (HCV) model, using the Routh-Hurwitz conditions, we prove in most parameter regimes that there can be no Turing instability. The simulations support this in all parameter regions of the model. We introduce a modified model where Turing instability is observed. For tumor dynamics model, we present the Fisher Kolomogorov equation (PDE) and the effective particle methods (ODE) for single front solution and localized solution with and without radiation. The predicted lifetimes of the patients from the PDE and ODE are compared and show good quantitative agreement

The Interplay of Intrinsic Dynamics and Coupling in Spatially Distributed Neuronal Networks

We explore three coupled networks. Each is an example of a network whose spatially coupled behavior is dratically different than the behavior of the uncoupled system. 1. An evolution equation such that the intrinsic dynamics of the system are those near a degenerate Hopf bifurcation is explored. The coupled system is bistable and solutions such as waves and persistent localized activity are found. 2. A trapping mechanism that causes long interspike intervals in a network of Hodgkin Huxley neurons coupled with excitatory synaptic coupling is unveiled. This trapping mechanism is formed through the interaction of the time scales present intrinsically and the time scale of the synaptic decay. 3. We construct a model to create the spatial patterns reported by subjects in an experiment when their eyes were stimulated electrically. Phase locked oscillators are used to create boundaries representing phosphenes. Asymmetric coupling causes the lines to move, as in the experiment. Stable stationary solutions and waves are found in a reduced model of evolution/ convolution type