Neuroscientists have long recognised that the visual cortex can be conceptualised as a hierarchical processing network. The power of this architecture has became apparent recently, when learning algorithms based on hierarchical networks ("deep learning") revolutionised artificial intelligence. The aim of the project is to understand how visual information is transformed across hierarchical levels in the brain, by combining high-throughput electrophysiology with new analytical tools, adopted from deep learning. By explaining the physiological properties of higher-level neurons in terms of hierarchical networks, the project will address long standing questions in neuroscience, and provide insights on biological hierarchical computation.
|Effective start/end date||1/04/17 → 31/03/20|
- Australian Research Council (ARC): AUD392,000.00
- Australian Research Council (ARC)
- Monash University: AUD123,827.00
- University of South Australia: AUD18,320.00
- University of California