How closely should an artificial neural network (ANN) emulate a biological neuronal network (BNN), then it will begin to exhibit the same type of intelligence of BNN? To tackle this profound question, I initiated my exploration with the question: “Is it possible to substitute a portion of biological neurons with artificial ones without altering the pre-existing neuronal functionality?”

I have sought to answer this question by developing cyto-silicon hybrid neuronal networks, focusing on three interconnected sub-areas: (1) building the tools to communicate with neurons, developing CMOS-Nano electrode array (CNEA) system-on-chips that enable high-throughput, high-resolution electrophysiology recording and precise neural stimulation; (2) listening to and talking to neurons, conducting electrophysiology experiments with cultured cells, brain organoids, and brain slices via CNEAs, then extracting the synaptic connection map from the recorded big data; (3) mimicking and modulating the connection and behavior of neurons, exploring neuromorphic systems that can closely emulate and precisely modulate the dynamics of single neurons and their connectivity.