The Automatic Neuroscientist: automated experimental design with real-time fMRI
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Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Jun 2015.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 2.
4 papers.
- 2021AdaptiFont: Increasing Individuals' Reading Speed with a Generative Font Model and Bayesian Optimizationcited by 5
- 2023Designing Optimal Behavioral Experiments Using Machine Learningcited by 3
- 2022MIDAS: Deep learning human action intention prediction from natural eye movement patternscited by 2
- 2023Towards AI-controlled FES-restoration of arm movements: Controlling for progressive muscular fatigue with Gaussian state-space modelscited by 1
- 2023Designing Optimal Behavioral Experiments Using Machine Learning12 May 2023
- 2023Towards AI-controlled FES-restoration of arm movements: Controlling for progressive muscular fatigue with Gaussian state-space models10 Jan 2023
- 2022MIDAS: Deep learning human action intention prediction from natural eye movement patterns22 Jan 2022
- 2021AdaptiFont: Increasing Individuals' Reading Speed with a Generative Font Model and Bayesian Optimization21 Apr 2021