Performances of computers based on von Neumann architecture [1], with separated  data processing and memory units, are hindered by power dissipation, execution time and sustainability issues [2]. This makes it challenging to process in real time a substantial amount of data for complex tasks, that are carried out with great efficiency by the human brain. This is a network composed by basic computing units, neurons, which are densely connected in a self-assembled and redundant way through synapses. Their conductive strength depends on the signals previously received, which are spike trains whose frequency encodes information; computation and memory thus take place together.

            Computational models and engineering solutions emulating the biological nervous system are called neuromorphic; thin films made of metallic clusters, fabricated by Supersonic Cluster Beam Deposition [4], can be an experimental strategy used to implement in hardware such paradigm. These systems show non-linear electrical properties and resistive switching [5,6]: their resistance has a spiking activity and explores distinct levels when constant voltage is applied.

            Here, we report how gold nanostructured networks change their conductive state depending on the features of voltage trains as input signals, in a controllable and reproducible way.

            We proved that the device resistance is affected by varying the temporal features and voltage levels of pulsed signals, switching reversibly between levels, several orders of magnitude apart; this switching mechanism is controlled by varying time and polarity features of the signal. Furthermore, devices preserve their conductive state in time and can cycle dozens of times between different resistance levels.

This behaviour, observed at first in two terminal devices, can be found also in multielectrode ones. Not only reversibility and input dependence are preserved, but the more complex terminal geometry allows to study the non-local electrical response of such devices: by applying the proper signal between two terminals it modifies not only the resistance of the path connecting them, but also those of the paths that do not cross it, in a non-trivial and reproducible way.

This type of device emulates the heterosynaptic plasticy featured in the brain, that makes it possible to change its state instantaneously and globally depending on input signal features. We propose the use of multi-electrodes devices based on cluster-assembled thin films both as a neuromorphic multiplexer and reconfigurable threshold logic gate.

To further engineer these devices, we plan to fabricate cluster assembled films with tailored metallic materials, featuring different thermic and electrical properties, as also to study their real time response to analog inputs.