Carlos Ponce, Professor of Neuroscience at Washington University School of Medicine, describes a recent study that explores how neurons in inferotemporal (IT) cortex of the monkey visual system encode complex patterns for recognition. The video begins with a reflection on the discovery of orientation selectivity in the cat visual cortex by David Hubel and Torsten Wiesel, who won the Nobel Prize for their work. Neurons in IT cortex of the monkey visual system play a role in the recognition of complex objects. Dr. Ponce and his colleagues developed a novel technique for discovering the complex visual patterns that yield the strongest responses of these cells. The method uses a generative adversarial network (GAN), which combines aspects of deep neural networks and genetic algorithms, to drive the evolution of rich synthetic images of objects with complex combinations of shapes, colors, and textures, that are preferred by these neurons. The images sometimes resemble familiar objects and provide insight into the vocabulary of features encoded in IT cortex to support visual recognition.
Video: The visual alphabet 2.0 (32:57)
Slides: Carlos Ponce's Slides (pdf)
- Carlos Ponce’s Lab website
- Ponce, C.R., Xiao, W., Hartmann, T.S., Kreiman, G. & Livingstone, M.S. (2019) Evolving images for visual neurons using a deep generative network reveals coding principles and neuronal preferences. Cell 177(4):999-1009.
- Evolving images for visual neurons using a deep generative network reveals coding principles and neuronal preferences, CBMM publication release video: May 2019.