  A standard approach in functional neuroimaging explores how a particular
cognitive task activates a set of brain regions (one task-to-many regions
mapping). Importantly though, the same neural system can be activated by
inherently different tasks. To date, there is no approach available that
systematically explores whether and how distinct tasks probe the same neural
system (many tasks-to-region mapping). In our work, presented here we propose
an alternative framework, the Automatic Neuroscientist, which turns the typical
fMRI approach on its head. We use real-time fMRI in combination with
state-of-the-art optimisation techniques to automatically design the optimal
experiment to evoke a desired target brain state. Here, we present two
proof-of-principle studies involving visual and auditory stimuli. The data
demonstrate this closed-loop approach to be very powerful, hugely speeding up
fMRI and providing an accurate estimation of the underlying relationship
between stimuli and neural responses across an extensive experimental parameter
space. Finally, we detail four scenarios where our approach can be applied,
suggesting how it provides a novel description of how cognition and the brain
interrelate.
