Dr. Hai and his PhD student, Adam Vareberg, have published “Interference of network connectivity from temporally binned spike trains” in the Journal of Neuroscience Methods, Vol 404.
Dr. Hai, Vareberg, and the Hai lab have pioneered a new method to infer synaptic weights by processing firing rates within variable time bins for heterogeneous feed-forward network of excitatory, inhibitory, and unconnected units. They have provided a framework for reverse engineering neural networks from data with limited temporal quality.
https://www.sciencedirect.com/science/article/pii/S0165027024000189