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The impact of parallel simulation strategies on the almost chaotic nature of the behavior of brain microcircuit simulations is of increasing importance to neuroscience. The challenge here is to design parallel simulation strategies (implementations of biological neural models and simulation loops) that preserve the dynamic behavior of neural microcircuits. In this paper, we present an approach to dynamics analysis based on strong dimensionality reduction and on the Lyapunov exponent method. The parallel implementation of the Spike Response Model relies on OpenMP and scales well when the number of threads matches the number of physical cores. The analysis performed on reduced data sets confirms the dynamic behavior observed in the high dimensional simulation data. As such, this approach is potentially of interest to computational neuroscience research.