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An important issue in dealing with Deep Convolutional Neural Networks (DCNN) is the 'black box problem', which represents the unknowns about internal information representation and processing, especially in the middle and higher layers. In this study, we adopted a systems neuroscience methodology to measure the visual feature selectivity and visualize the spatial receptive field of the units in VGG16. Orientation and spatial frequency tunings of each unit were measured using sinusoidal gratingarXiv:2103.02587v1 fatcat:ryenloikh5fspkboqbu6p5kbqu