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Related Experiment Video

Updated: May 5, 2026

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AutoNeuro: An Open-Source fMRI Toolbox for Real-Time Neuroadaptive Task Design.

Oliver Sherwood1, David Haydock2, Raha Razin2

  • 1Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.

Biorxiv : the Preprint Server for Biology
|May 4, 2026
PubMed
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This summary is machine-generated.

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AutoNeuro is an open-source framework for adaptive real-time fMRI experiments. It enables dynamic control of experimental parameters based on ongoing brain activity, optimizing data acquisition for brain mapping.

Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Biomedical Engineering

Background:

  • Real-time functional magnetic resonance imaging (fMRI) allows adaptive study of brain function.
  • Current real-time fMRI systems face limitations in infrastructure, flexibility, and closed-loop control, often focusing narrowly on neurofeedback.

Purpose of the Study:

  • To introduce AutoNeuro, an open-source framework for real-time fMRI acquisition, analysis, and adaptive experimental control.
  • To provide a flexible platform for closed-loop neuroimaging, moving beyond traditional neurofeedback designs.

Main Methods:

  • AutoNeuro connects directly to MRI scanners for low-latency data streaming and processing.
  • A modular pipeline performs real-time preprocessing and feature extraction.
  • A Bayesian optimization agent adaptively selects task conditions within a defined 'experiment space' to maximize a user-defined objective function.
Keywords:
Bayesian optimisationClosed-loop neuroimagingGaussian Process modellingNeuroadaptive experimental designReal-time fMRI

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Main Results:

  • The framework successfully operated within real-time processing constraints.
  • Stable model estimates were maintained across iterations, demonstrating reliable performance.
  • The system converged on experimental conditions that were most relevant to the measured brain metric, effectively mapping brain responses.

Conclusions:

  • AutoNeuro offers a flexible and efficient platform for closed-loop neuroimaging.
  • It supports both hypothesis-driven optimization and exploratory mapping of brain metrics.
  • This framework advances the adaptive study of brain function using real-time fMRI.