Input evoked nonlinearities in silicon dendritic circuits

Most VLSI spiking network implementations are constructed using point neurons. However, neurons with extended dendritic structures might offer additional computational advantages. Experimental evidence suggests that dendritic compartments could be considered as independent and parallel computational units. Depending on the synaptic input patterns, the dendritic integration could be either linear or nonlinear. We show the influence of spatio-temporal input patterns on the evoked dendritic integration in an a VLSI neuron chip with programmable dendritic compartments.