BACKUP will address the fundamental question of which is the role of neuron activity and plasticity in information elaboration and storage in the brain. Within an interdisciplinary team, BACKUP will develop a hybrid neuromorphic computing platform. Integrated photonic circuits will be interfaced to both electronic circuits and neuronal circuits (in vitro experiments) to emulate brain functions and develop schemes able to supplement (backup) neuronal functions. The photonic network is based on massive reconfigurable matrices of nonlinear nodes formed by microring resonators, which enter in regime of self-pulsing and chaos by positive optical feedback. These networks resemble human brain. BACKUP will push this analogy further by interfacing the photonic network with neurons making hybrid network. By using optogenetics, we will control the synaptic strengthening and the neuron activity. Deep learning algorithms will model the biological network functionality, initially within a separate artificial network and, then, in an integrated hybrid artificial-biological network.

• Developing a photonic integrated reservoir-computing network (RCN);
• Developing dynamic memories in photonic integrated circuits using RCN;
• Developing hybrid interfaces between a neuronal network and a photonic integrated circuit;
• Developing a hybrid electronic, photonic and biological network that computes jointly;
• Addressing neuronal network activity by photonic RCN to simulate in vitro memory storage and retrieval;
• Elaborating the signal from RCN and neuronal circuits in order to cope with plastic changes in pathological brain conditions such as amnesia and epilepsy.

Long term vision: The long-term vision is that hybrid neuromorphic photonic networks will

1. clarify the way brain thinks
2. compute beyond von Neumann
3. control and supplement specific neuronal functions

This project has a strong interdisciplinary content. We primarily address computing, photonics, electronics and photonics integrated circuits, photonic applications to biology and networks. However, we do also address the issue of interfacing neurons with condensed matter by using light, which is a topic peculiar to biophysics. In this research, we will develop photonic circuits that provide the light signal to genetically modified neurons in order to control their activity. Moreover, our intention is to use light in order to both strengthen synapses along specific light circuits and to restore or induce specific neuron interconnections, to achieve specific neuronal functions. BACKUP results will be applied to predict and control the mechanisms behind complex neurological diseases as amnesia and epilepsy.