Bridging the Computational Sensory Gap

A long standing aim for computer science has been to build ‘intelligent machines’. Building computer models of the human brain has the potential to achieve this aim, either through developing an artificial brain, or by understanding how the brain computes to replicate intelligence. However, despite significant advances, we have yet to realise this potential.  There appears to be a clear gap between modelling the brain for neuroscience and applying what we have learnt about brain-like computation to real-world, practical problems. On the one hand, models based on high-level cognition have been developed which can process real-world inputs. These cognitive architectures may show us broadly how the brain achieves certain function, but are too simplistic for practical purposes. On the other hand, large-scale brain simulations have been developed which model brain dynamics, but are not designed to replicate intelligence.  In this seminar we will explore these issues and debate some of the possible long-term answers which involve bridging the gap between cognitive architectures and large-scale simulations, particularly for sensory processing.