This paper presents configuration methods for an existing neuromorphic hardware and shows first experimental results. The utilized mixed-signal VLSI1 device implements a highly accelerated network of integrate-and-fire neurons. We present a software framework, which provides the possibility to interface the hardware and explore it from the point of view of neuroscience. It allows to directly compare both spike times and membrane potentials which are emulated by the hardware or are computed by the software simulator NEST, respectively, from within a single software scope. Membrane potential and spike timing dependent plasticity measurements are shown which illustrate the capabilities of the software framework and document the functionality of the chip. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Brüderle, D., Grübl, A., Meier, K., Mueller, E., & Schemmel, J. (2007). A software framework for tuning the dynamics of neuromorphic silicon towards biology. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4507 LNCS, pp. 479–486). Springer Verlag. https://doi.org/10.1007/978-3-540-73007-1_59
Mendeley helps you to discover research relevant for your work.