The neural mechanism of scale-invariant creative search

The human brain efficiently searches enormous mental spaces of thought for solutions to a given question. How is this done?

The growing importance of creative search has sparked a surge of interest in mapping the relations between people’s creative search strategies and the structure, activity, and connectivity of their brain.

Yet to date there are no coherent computational principles to bind behavioral, computational, and neurobiological findings together into a mechanistic understanding of creative search. CreativeBrain uses two such computational principles: scale-invariant sensing and Pareto optimality.

Scale-invariant sensing is essential for a robust search in environments with signals that span many orders of magnitude like in creative search.

Pareto optimality asserts that individual differences stem from different balancing between competing tasks that need to be optimized and thus explains the utility of these individual differences.

CreativeBrain will employ state-of-the-art computational and analysis methods from systems biology to infer the neural mechanism of creative search on the levels of function, computations and neural implementation.

This will be the first comprehensive research effort that ties these findings to a mechanistic theory of creative search that also explains the utility of neural individual differences.

The project will result in a breakthrough in our understanding of how the human brain can efficiently search in vast spaces of thought.

On a broader scale, CreativeBrain will open a new front in the interdisciplinary studies of the mind and brain, offering a principled way to unite neurobiological, behavioral, and computational aspects into one holistic and mechanistic view.

By doing so it will contribute significantly to the promise of computational modeling for connecting different levels of inquiry of a higher cognitive function in the brain and can thus be extended to other cognitive processes and systems.