  Neuromorphic chip refers to an unconventional computing architecture that is
modelled on biological brains. It is ideally suited for processing sensory data
for intelligence computing, decision-making or context cognition. Despite rapid
development, conventional artificial synapses exhibit poor connection
flexibility and require separate data acquisition circuitry, resulting in
limited functionalities and significant hardware redundancy. Here we report a
novel light-stimulated artificial synapse based on a graphene-nanotube hybrid
phototransistor that can directly convert optical stimuli into a "neural image"
for further neuronal analysis. Our optically-driven synapses involve multiple
steps of plasticity mechanisms and importantly exhibit flexible tuning of both
short- and long-term plasticity. Furthermore, our neuromorphic phototransistor
can take multiple pre-synaptic light stimuli via wavelength-division
multiplexing and allows advanced optical processing through
charge-trap-mediated optical coupling. The capability of complex neuromorphic
functionalities in a simple silicon-compatible device paves the way for novel
neuromorphic computing architectures involving photonics.
