Because of difficulties involving the realization and coupling of many systems, the dynamics of large complex networks have mostly been studied theoretically. In simulations, it was shown that networks of neural-like and oscillatory systems display a wide range of astonishing and often counter-intuitive dynamics, for example cluster synchronization and coexistence of ordered and disordered phases. Recently two papers have been published [1,2] that study such dynamics also in the experiment, but they still require a computer for the coupling between the numerous experimental network nodes. In this talk, we propose to use a field-programmable gate array (FPGA) to build large experimental networks. On this re-programmable electronic chip, we can accommodate both the coupling and the dynamic nodes. We will present our results on neural-like networks to show the potential of our approach for building large networks. These networks display synchronization patterns that depend on the local node properties, which might have implications for cognition and learning.
 A. M. Hagerstrom et al., Nature Physics, 8, 658 (2012)
 M. R. Tinsley et al., Nature Physics, 8, 662 (2012)