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Semantic fMRI neurofeedback: a multi-subject study at 3 tesla.

Assunta Ciarlo1, Andrea G Russo1,2, Sara Ponticorvo1

  • 1Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Baronissi, SA, Italy.

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|May 13, 2022
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Summary

This study shows that real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-NF) allows individuals to control brain activity. Semantic rt-fMRI-NF successfully guided participants in modulating target mental states using visual feedback.

Keywords:
neurofeedbackreal-time fMRIrepresentational similarity analysissemantic representation

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Medical Imaging

Background:

  • Real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-NF) enables self-regulation of brain activity.
  • Semantic rt-fMRI-NF utilizes representational similarity analysis (rt-RSA) for multi-dimensional feedback based on mental states.

Purpose of the Study:

  • To assess the performance of semantic rt-fMRI-NF on a 3 T MRI scanner in a multi-subject, multi-session study.
  • To evaluate participants' ability to replicate and modulate neural activation patterns corresponding to specific mental states.

Main Methods:

  • Eighteen healthy volunteers participated in two rt-fMRI-NF sessions over two days.
  • Participants generated and modulated neural patterns of concrete object imagery, guided by rt-RSA visual feedback.
  • Performance indicators measured pattern replication and maintenance; simulations assessed feedback distortions.

Main Results:

  • Sixteen participants completed both sessions; significant improvements in modulation performance were observed within and between runs.
  • No significant improvements were found between separate sessions, indicating stable performance.
  • Simulations revealed potential metric distortions in visual feedback due to rt-RSA's dimensionality reduction.

Conclusions:

  • Semantic rt-fMRI-NF is feasible on a 3 T MRI scanner, enabling subjects to modulate and maintain target mental states.
  • rt-RSA derived feedback effectively guides self-regulation of brain activity.
  • Further research is needed to optimize the framework for clinical applications.