How organisms acquire, process, and store information is one of the central questions in neurobiology. A large body of evidence suggests that plasticity is a key element of learning and memory, while complex interactions in neuronal networks with plasticity are believed to explain biological intelligence and higher cognitive functions. Thanks to theoretical and computational neuroscience, significant progress in understanding complex phenomena has been made through modeling and simulation. However, direct experimental demonstration of emergent phenomena from the first principles remains challenging. An intriguing question that is attracting increasing attention is whether biological neuronal networks with plasticity can be used as hardware for abstract computation. In this work, building on technological advances in all-optical interrogation of cellular circuits with optogenetics and genetically encoded fluorescent activity reporters, we consider a novel strategy for “programming” neuronal networks and ultimately evaluate how they can be deployed in neurobiological computing.