Emergence of Macro Spatial Structures in Dissipative Cellular Automata

This paper describes the peculiar behavior observed in a class of cellular automata that we have defined as dissipative, i.e., cellular automata that are open and makes it possible for the environment to influence their evolution. Peculiar in the dynamic evolution of this class of cellular automata is that stable macro-level spatial structures emerge from local interactions among cells, a behavior that does not emerge when the cellular automaton is closed, i.e., when the state of a cell is not influenced by the external world. Moreover, we observed that Dissipative Cellular Automata (DCA) exhibit a behavior very similar to that of dissipative structures, as macro-level spatial structures emerge as soon as the external perturbation exceeds a threshold value and it stays below the "turbulence" limit. Finally, we discuss possible relations of the performed experiments with the area of open distributed computing, and in particular of agent-based distributed computing

Synchronization, Diversity, and Topology of Networks of Integrate and Fire Oscillators

We study synchronization dynamics of a population of pulse-coupled oscillators. In particular, we focus our attention in the interplay between networks topological disorder and its synchronization features. Firstly, we analyze synchronization time $T$ in random networks, and find a scaling law which relates $T$ to networks connectivity. Then, we carry on comparing synchronization time for several other topological configurations, characterized by a different degree of randomness. The analysis shows that regular lattices perform better than any other disordered network. The fact can be understood by considering the variability in the number of links between two adjacent neighbors. This phenomenon is equivalent to have a non-random topology with a distribution of interactions and it can be removed by an adequate local normalization of the couplings.Comment: 6 pages, 8 figures, LaTeX 209, uses RevTe

Fluctuations in Neuronal Synchronization in Brain Activity Correlate with the Subjective Experience of Visual Recognition

The scientific study of subjective experience is a current major research area in the neurosciences. Coordination patterns of brain activity are being studied to address the question of how brain function relates to behaviour, and particularly methods to estimate neuronal synchronization can unravel the spatio-temporal dynamics of the transient formation of neuronal assemblies. We report here a biophysical correlate of subjective experience. Subjects visualised figures with different levels of noise, while their brain activity was recorded using magnetoencephalography (MEG), and reported the moment in time (corresponding to a noise level) of figure recognition, which varied between individuals, as well as the moment when they saw the figure more clearly, which was mostly common among the participants (thus less subjective). This latter moment is considered to represent psychophysical stochastic resonance (PSR). Fluctuations in neuronal synchronization, quantified using a diffusion coefficient, were lower in occipital cortex when subjects recognised the figure, for a certain noise level, but did not correlate with the moment of PSR. A different pattern was observed in frontal cortex, where lower values of the diffusion coefficient in neuronal synchronization was maintained from the moment of recognition to the moment of PSR. No specific pattern was found analysing signals from temporal or parietal cortical areas. These observations provide support for distinct synchronization patterns in different cortical areas, and represent another demonstration that the subjective, first-person perspective is accessible to scientific methods