Abstract
A FPGA hardware core has been designed for real-time network simulations with up to 400 physiologically realistic, conductance-based neurons of the Hodgkin-Huxley type. A PC-FPGA interface allows easy parameter adjustment and on-line display of basic synchronization measures like field potentials, spike times or color-coded voltages of the complete array. Simulations of 20 ·20 gap-junction coupled 4-dimensional neurons reveal remarkable alterations of the synchronization states and impulse patterns during linearly increasing coupling strengths.
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Beuler, M., Tchaptchet, A., Bonath, W., Postnova, S., Braun, H.A. (2012). Real-Time Simulations of Synchronization in a Conductance-Based Neuronal Network with a Digital FPGA Hardware-Core. In: Villa, A.E.P., Duch, W., Érdi, P., Masulli, F., Palm, G. (eds) Artificial Neural Networks and Machine Learning – ICANN 2012. ICANN 2012. Lecture Notes in Computer Science, vol 7552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33269-2_13
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DOI: https://doi.org/10.1007/978-3-642-33269-2_13
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