Neural population control via deep image synthesis
Abstract
To what extent are predictive deep learning models of neural responses useful for generating experimental hypotheses? Bashivan et al. took an artificial neural network built to model the behavior of the target visual system and used it to construct images predicted to either broadly activate large populations of neurons or selectively activate one population while keeping the others unchanged. They then analyzed the effectiveness of these images in producing the desired effects in the macaque visual cortex. The manipulations showed very strong effects and achieved considerable and highly selective influence over the neuronal populations. Using novel and non-naturalistic images, the neural network was shown to reproduce the overall behavior of the animals' neural responses.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- May 03, 2019
- Source ID
- 10.1126/science.aav9436
Entities
People
- James J. DiCarlo
- Kohitij Kar
- Pouya Bashivan
Organizations
- Intelligence Advanced Research Projects Activity
- National Eye Institute
- Office of Naval Research