Network Synaptic Connectivity Reconstruction by Spike-triggered Regression

How neurons are connected in the brain to perform computation is a key issue in neuroscience. We propose the spike-triggered regression (STR) method, which employs both the voltage trace (intracellular recording) and firing activity of the neuronal population (calcium imaging measurement) to reconstruct the underlying synaptic connectivity. Our method can yield an accurate reconstruction of a large neuronal network even in the case of dense connectivity and nearly synchronous dynamics, which many other network reconstruction methods cannot successfully handle.