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Computer simulations of catalytic networks. Andrade et al. (1993) have recently published the results of our first simulations, and have addressed the problem of the effect that catalytic error has in controlling system dynamics. Simulations of large networks are being designed in order examine spatio-temporal dynamics in reaction-diffusion systems. The aim is to develop visualization and analysis methods to apply large networks composed of biologically realistic neurons. Immunohistochemical studies have examined mammalian tissues that may be useful as model systems to examine distributed function in neurotransmission and neuromodulation (Soinila and Mpitsos, 1992; Soinila et al., 1992). It is necessary, as these and other publications (e.g., Mpitsos and Soinila, 1993) indicate, not only to understand neural organization in a simple animal, but also to examine the applicability of the findings to higher animals, and, if possible, to humans. Molecular biological studies of muscarinic receptors: In previous AFOSR-published work, Murray et al. (1985) and Murray and Mpitsos (1988) showed further that brief pharmacologic blocking of these receptors enhances 1-Trial associative learning. Over the past year, we have developed cloning vectors for generating fusing proteins to all of the five known muscarinic receptor subtypes in humans. Our next step is to obtaine immunofluorescent antisera to the fusion proteins in order to visually identify cells containing the different muscarinic receptors. The in-between step will be to determine the specificity of the antisera. The findings will be applicable not only to our experimental animal, but also to studies of learning and pathologies in humans.