The Automatic Neuroscientist: automated experimental design with real-time fMRI

TL;DR

This paper introduces the Automatic Neuroscientist, a real-time fMRI system that automatically designs experiments to evoke specific brain states, significantly speeding up neuroimaging studies and exploring complex stimulus-response relationships.

Contribution

It presents a novel closed-loop framework combining real-time fMRI with optimization techniques to automatically tailor experiments for targeted neural activation.

Findings

Demonstrated the approach's effectiveness with visual and auditory stimuli

Showed significant speed-up in fMRI data collection

Accurately estimated stimulus-brain response relationships

Abstract

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.