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Diffusion models and reinforcement learning: Novel pathways to modeling decoded fMRI neurofeedback

Azimi Asrari, Hojjat; Peters, Megan; (2024) Diffusion models and reinforcement learning: Novel pathways to modeling decoded fMRI neurofeedback. In: Proceedings of the 8th annual conference on Cognitive Computational Neuroscience. (pp. pp. 1-3). CCN Green open access

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Abstract

This study explores the application of diffusion models and reinforcement learning to model Decoded Neurofeedback (DecNef), as applied via functional magnetic resonance imaging (fMRI). Our methodology, Denoising Diffusion Policy Optimization (DDPO), integrates diffusion models trained via reinforcement learning to navigate the complex dynamics of brain activity changes. Using a preexisting DecNef dataset, we implemented policy gradient methods to iteratively refine the diffusion models, aiming to produce target patterns of neural (voxel) activity. Our results demonstrate the potential of this approach for accurately modeling policies that allow the achievement of target brain states, offering a foundation for investigating the mechanisms of neurofeedback and its implications for basic science research and conducting more effective neurofeedback experiments.

Type: Proceedings paper
Title: Diffusion models and reinforcement learning: Novel pathways to modeling decoded fMRI neurofeedback
Event: 8th annual conference on Cognitive Computational Neuroscience
Open access status: An open access version is available from UCL Discovery
Publisher version: https://2024.ccneuro.org/pdf/431_Paper_authored_au...
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher's terms and conditions.
Keywords: Decoded Neurofeedback (DecNef), fMRI, Diffusion Models, Explainable Reinforcement Learning
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology
URI: https://discovery.ucl.ac.uk/id/eprint/10216054
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