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Deep convolutional neural networks (CNNs) trained for object classificationhave a number of striking similarities with the primate ventral visual stream.In particular, activity in early, intermediate, and late layers is closelyrelated to activity in V1, V4, and the inferotemporal cortex (IT). This studyfurther compares activity in late layers of object-classification CNNs toactivity patterns reported in the IT electrophysiology literature. There are anumber of close similarities, including the distributions of populationresponse sparseness across stimuli, and the distribution of size tuningbandwidth. Statisics of scale invariance, responses to clutter and occlusion,and orientation tuning are less similar. Statistics of object selectivity arequite different. These results agree with recent studies that highlight strongparallels between object-categorization CNNs and the ventral stream, and alsohighlight differences that could perhaps be reduced in future CNNs.

Similarities and differences between stimulus tuning in the inferotemporal visual cortex and convolutional networks