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Functional neuroimaging typically explores how a particular task activates a set of brain regions. Importantly though, the same neural system can be activated by inherently different tasks. We are developing an alternative framework, the Automatic Neuroscientist (Figure, top left). This turns the standard functional magnetic resonance imaging (FMRI) approach on its head. We are using using real-time fMRI (functional images collected and analysed in close to real time) in combination with machine-learning techniques to automatically design neuroimaging experiments (Figure, top right). Our work explores how this type of closed-loop realtime methodology can accurately and efficiently estimate the underlying relationship between experimental stimuli and neural responses (Figure, bottom). We are also investigating how this real-time approach can be applied in a range of circumstances: ranging from optimizing stimuli in neuroimaging pilot studies to tailoring clinical rehabilitation therapy to patients.

Principal investigator

Researchers involved

  • Romy Lorenz