People who wish to analyze nature without using mathematics must settle for a reduced understanding.
Richard P. Feynman
We aim to understand how the brain works as an engineered system. How geometric and dynamic constraints in brain networks give rise to the mathematical rules responsible for emergent computational and cognitive functions. Our working hypothesis is that such emergent properties reflect a high level perspective of what is actually hierarchies of computed information that are passed across scales of organization. Ultimately, we want to contribute to the understanding of how the brain is able to achieve creativity, imagination, inference, and self awareness.
At the same time, we are taking what we learn to understand how the brain is different in neurodevelopmental disorders such as autism spectrum disorder. And how we can use such brain algorithms to develop a fundamentally new form of (non-gradient decent) machine learning capable of learning without the the need for any training.