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.
Click here for original story, Neuron circuitry from brain signals
Source: ScienceDaily