The first brain-inspired photonic integrated circuits have been designed, fabricated, tested, and validated to perform complex computational tasks. Memory is incorporated using the intrinsic nonlinearity of optical microring resonators and external optical feedback. Demonstrated neural networks range from simple optical perceptrons for telecom applications to arrays of nonlinear optical nodes for digit recognition and time series forecasting. A significant advancement is the creation of photonic integrated spiking neural networks with microring resonators, featuring short- and long-term memories, proposed for edge computing in sensing applications.
Using optogenetics and patterned light excitation in cultured neurons, we investigated synaptic strengthening and memory formation. We developed an optical platform for single-cell optogenetic experiments in vitro, utilizing multiple wavelengths to induce excitation or inhibition. This platform, coupled with labeling techniques or electrophysiological monitoring, allows selective excitation or inhibition of cells in a neuronal network, aiding molecular, physiological, and morphological characterization.
A photonic chip and neuronal culture have been designed, allowing optical signals to activate specific neurons, while neuronal activity influences the photonic neural network, establishing a bidirectional link.
Deep learning algorithms modeled biological network dynamics, initially in an artificial network and later in a hybrid artificial-biological network. Our Reservoir Computing Network (RCN) model accurately predicts network connectivity and simulates responses to stimuli.
Dissemination activities included over 50 presentations at conferences and workshops, 30 published articles, and organizing one winter school and two workshops. Six Master’s theses were completed, a patent was filed internationally, and an ERC-POC grant was approved. Numerous spin-off projects have been submitted for evaluation.
