Most studies of neural and neural-like systems have focused on emergent collective properties of large numbers of microscopic units. When these details of microscopic mteractions are coarse-grained. the utility of directly studying the aggregated mesoscopic scale of interactions becomes apparent. as has been demonstrated by a series of papers by the author: Detailed properties of "eocortical phenomena. e g.. a derivation of the 7+2 rule of short-term memory. its stability and duration. and spatial-temporal properties of electroencephalographic (EEG) and magnetoencephalographic (MEG] phenomena can be explicitly calculated and shown to agree favorably with empirical evidence. This mesoscopic scale is important. not only to achieve pattern recognition or to test the analysis of the microscopic scale, but indeed it is to be respected as a potential source of command and control over the microscopic scale. in both the brain. e g as a pre-attentive filter and processor of patterned information. and in other large-scale systems. e g in Command, Control and Communications (C3) systems Keywords Nonlinear Nonequilibrium Statistical Mechanics, neocortex. Command. Control and Communications I. INTRODUCTION In many complex systems. structures exist at various scales to accommodate different functions As a result. theoretical and experimental understanding of these systems often is complementary. sometimes mutually exclusive. at these scales (National Research Council. 1984)