coherent activity. This temporal and phase coherence plays an important role in current theory of sensory-associative-motor integrative function, how distributed attributions come together in the brain representation of a single object or process, in the context of the so-called “binding problem” (Singer, 1993; Bressler, 1995; Nicolelis, 1995; Schiff et al, 1997). Diffusely distributed neurochemical variables have been invoked. For example, the role of metabotropic glutamate receptors in driving the synchronization of interneuronal networks has been suggested as a mechanistic model (Whittington et al, 1995). The objects of relevance to the discovery of Fermi-Pasta-Ulam are studied as the nonlinear physics of nondissapative wave processes and are called solitons (Zabusky and Kruskal, 1965). They have been invoked to model nerve conduction and information transport in brain (Scott, 1990). A third counter-intuitive set of accidental computational findings is in an area of research called symbolic dynamics which involves the universal parameter- dependent coding language and capacity of nonlinear systems. In the early 1960’s, a group around Stan Ulam at Los Alamos (Cooper, 1987) used one of the early “high powered” computers, MANIAC Il, to iterate (letting the output of the action of a discrete time function serve as its input the next time around) simple equations they called “maps.” These reduced dimensional objects shaped like tents, sine functions and parabolas can be extracted from and represent the behavior of higher dimensional, nonlinear differential equations (see Devaney, 1989; Schuster, 1989 or Moon, 1992 for intuitive descriptions). They varied a parameter, such as the height of the tent or parabola, to systematically change the period and/or phase (order) of the symbol sequence (Metropolis et al, 1973). Normalizing the range of values of the output to [0,1] and transforming the series of values into a binary code, L < 0.5 and R > 0.5, they found an invaria