Using goal-driven deep learning models to understand sensory cortex.
|Title||Using goal-driven deep learning models to understand sensory cortex.|
|Publication Type||Journal Article|
|Year of Publication||2016|
|Authors||Yamins DLK, DiCarlo JJ|
|Date Published||2016 Feb 23|
Fueled by innovation in the computer vision and artificial intelligence communities, recent developments in computational neuroscience have used goal-driven hierarchical convolutional neural networks (HCNNs) to make strides in modeling neural single-unit and population responses in higher visual cortical areas. In this Perspective, we review the recent progress in a broader modeling context and describe some of the key technical innovations that have supported it. We then outline how the goal-driven HCNN approach can be used to delve even more deeply into understanding the development and organization of sensory cortical processing.
|Alternate Journal||Nat. Neurosci.|