Brain-Inspired Cognitive Architectures
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From advanced learning to neurorobotics and neuromorphic applications
The central ambition of this focus area is to better understand how brain networks enable visuo-motor and cognitive functions, such as dexterous manipulation, spatial navigation, and relational reasoning.
Our approach is to emulate the architecture and operation of the brain by designing functional cognitive architectures addressing challenging visuo-motor and cognitive problems. Numerical simulations and embodiment in virtual or real robots enable us to study closed-loop interactions between the brain, the body, and the physical environment. We target the development of a novel cognitive framework supporting the flexible integration of a range of heterogeneous modules, representing brain areas, into coherent embodied architectures. Furthermore, we develop new learning rules to train the modules in biologically-plausible ways and new neuromorphic computation methods for rapid, energy-efficient simulation of large-scale models. Our computational architectures can perform a variety of cognitive functions and lead to new experimentally-testable hypotheses about brain function.