Recent advances at the interface of biological intelligence and deep neural networks
Recent advances at the interface of biological intelligence and deep neural networks
Theme: Computational and theoretical neuroscience
Wednesday 26th April, 09:30 – 11:10
Biological neural networks adapt and learn in diverse behavioural contexts. Artificial neural networks (ANNs) have exploited biological properties to solve complex problems. However, despite their effectiveness for specific tasks, ANNs are yet to realize the flexibility and adaptability of biological cognition. This symposium will bring together recent advances from computational and experimental research to advance our understanding of biological and artificial intelligence.
- Srikanth Ramaswamy, Newcastle University, UK: Multi-scale principles of neuromodulatory systems in neural networks: now and beyond
- Maija Filipovica, University of Bristol, UK: AI-driven Cholinergic theory of learning and cognitive robustness
- Randy Bruno, University of Oxford, UK: Cortical Layers in Context and Learning
- Sylvia Schroeder, University of Sussex, UK: How adaptable are the first stages of visual processing?