Performance-optimized hierarchical models predict neural responses in higher visual cortex.

ABSTRACT: The ventral visual stream underlies key human visual object recognition abilities. However, neural encoding in the higher areas of the ventral stream remains poorly understood. Here, we describe a modeling approach that yields a quantitatively accurate model of inferior temporal (IT) cortex, the highest ventral cortical area. Using high-throughput computational techniques, we discovered that, within a class of biologically plausible hierarchical neural network models, there is a strong correlation between a model's categorization performance and its ability to predict individual IT neural unit response data. To pursue this idea, we then identified a high-performing neural network that matches human performance on a range of recognition tasks. Critically, even though we did not constrain th

SUBMITTER: Yamins DL 

PROVIDER: S-EPMC4060707 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature