Neuron circuitry from brain signals

A research team has developed a machine learning model that allows scientists to reconstruct neuronal circuitry by measuring signals from the neurons themselves. The team constructed an analytical method by applying a Generalized Linear Model to a Cross Correlogram, that records the firing correlation between neurons. The model has the potential to elucidate the difference in neuronal computation in different brain regions.
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