Dynamics of Spatial Game Theory Networks with Novel Modifications

Introduction: Advances in biotechnology have shed light on many biological processes. In biological networks, nodes are used to represent the function of individual entities within a system and have historically been studied in isolation. Network structure adds edges that enable communication between nodes. An emerging fieldis to combine node function and network structure to yield network function. One of the most complex networks known in biology is the neural network within the brain. Modeling neural function will require an understanding of networks, dynamics, andneurophysiology. It is with this work that modeling techniques will be developed to work at this complex intersection. Methods: Spatial game theory was developed by Nowak in the context of modeling evolutionary dynamics, or the way in which species evolve over time. Spatial game theory offers a two dimensional view of analyzingthe state of neighbors and updating based on the surroundings. Our work builds upon this foundation by studying evolutionary game theory networks with respect to neural networks. This novel concept is that neurons may adopt a particular strategy that will allow propagation of information. The strategy may therefore act as the mechanism for gating. Furthermore, the strategy of a neuron, as in a real brain, isimpacted by the strategy of its neighbors. The techniques of spatial game theory already established by Nowak are repeated to explain two basic cases and validate the implementation of code. Two novel modifications are introduced in Chapters 3 and 4 that build on this network and may reflect neural networks. Results: The introduction of two novel modifications, mutation and rewiring, in large parametricstudies resulted in dynamics that had an intermediate amount of nodes firing at any given time. Further, even small mutation rates result in different dynamics more representative of the ideal state hypothesized. Conclusions: In both modificationsto Nowak's model, the results demonstrate the network does not become locked into a particular global state of passing all information or blocking all information. It is hypothesized that normal brain function occurs within this intermediate range and that a number of diseases are the result of moving outside of this range.

Doubly-charged ethane ions: Solution to the dilemma of stability predicted by theory and instability observed in experiment

Potential energy curves have been computed for [C2H6]2+ ions and the results used to interpret the conspicuous absence of these ions in 2E mass spectra and in charge-stripping experiments. The energies and structures of geometry-optimized ground-state singlet and excited-state triplet [C2H6]2+ ions have been determined along with energies for different decomposition barriers and dissociation asymptotes. Although singlet and triplet [C2H6]2+ ions can exist as stable entities, they possess low energy barriers to decomposition. Vertical Franck-Condon transitions, involving electron impact ionization of ethane as well as charge-stripping collisions of [C2H6]+ ions, produce [C2H6]2+ ions which promptly dissociate since they are formed with energies in excess of various decomposition barriers. Appearance energies computed for doubly-charged ethane fragment ions are in accordance with experimental values.

Comparison of density functional theory predictions of gas-phase deprotonation data

The SVWN, BVWN, BP86, BLYP, BPW91, B3P86, B3LYP, B3PW91, B1LYP, mPW1PW, and PBE1PBE density functionals, as implemented in Gaussian 98 and Gaussian 03, were used to calculate ΔG0 and ΔH0 values for 17 deprotonation reactions where the experimental values are accurately known. The PBE1PBE and B3P86 functionals are shown to compute results with accuracy comparable to more computationally intensive compound model chemistries. A rationale for the relative performance of various functionals is explored.

Comparison of Model Chemistry and Density Functional Theory Thermochemical Predictions with Experiment for Formation of Ionic Clusters of the Ammonium Cation Complexed with Water and Ammonia; Atmospheric Implications

The G2, G3, CBS-QB3, and CBS-APNO model chemistry methods and the B3LYP, B3P86, mPW1PW, and PBE1PBE density functional theory (DFT) methods have been used to calculate ΔH° and ΔG° values for ionic clusters of the ammonium ion complexed with water and ammonia. Results for the clusters NH4+(NH3)n and NH4+(H2O)n, where n = 1−4, are reported in this paper and compared against experimental values. Agreement with the experimental values for ΔH° and ΔG° for formation of NH4+(NH3)n clusters is excellent. Comparison between experiment and theory for formation of the NH4+(H2O)n clusters is quite good considering the uncertainty in the experimental values. The four DFT methods yield excellent agreement with experiment and the model chemistry methods when the aug-cc-pVTZ basis set is used for energetic calculations and the 6-31G* basis set is used for geometries and frequencies. On the basis of these results, we predict that all ions in the lower troposphere will be saturated with at least one complete first hydration shell of water molecules.