RT Journal Article
SR Electronic
T1 Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream
JF The Journal of Neuroscience
JO J. Neurosci.
FD Society for Neuroscience
SP 10005
OP 10014
DO 10.1523/JNEUROSCI.5023-14.2015
VO 35
IS 27
A1 Güçlü, Umut
A1 van Gerven, Marcel A. J.
YR 2015
UL http://www.jneurosci.org/content/35/27/10005.abstract
AB Converging evidence suggests that the primate ventral visual pathway encodes increasingly complex stimulus features in downstream areas. We quantitatively show that there indeed exists an explicit gradient for feature complexity in the ventral pathway of the human brain. This was achieved by mapping thousands of stimulus features of increasing complexity across the cortical sheet using a deep neural network. Our approach also revealed a fine-grained functional specialization of downstream areas of the ventral stream. Furthermore, it allowed decoding of representations from human brain activity at an unsurpassed degree of accuracy, confirming the quality of the developed approach. Stimulus features that successfully explained neural responses indicate that population receptive fields were explicitly tuned for object categorization. This provides strong support for the hypothesis that object categorization is a guiding principle in the functional organization of the primate ventral stream.