Towards semantic fMRI neurofeedback: navigating among mental states using real-time representational similarity analysis

Andrea Gerardo Russo, Michael Lührs, Francesco Di Salle, Fabrizio Esposito*, Rainer Goebel

*Corresponding author for this work

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Abstract

OBJECTIVE: Real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-NF) is a non-invasive MRI procedure allowing examined participants to learn to self-regulate brain activity by performing mental tasks. A novel two-step rt-fMRI-NF procedure is proposed whereby the feedback display is updated in real-time based on high-level representations of experimental stimuli (e.g. objects to imagine) via real-time representational similarity analysis of multi-voxel patterns of brain activity.

APPROACH: In a localizer session, the stimuli become associated with anchored points on a two-dimensional representational space where distances approximate between-pattern (dis)similarities. In the NF session, participants modulate their brain response, displayed as a movable point, to engage in a specific neural representation. The developed method pipeline is verified in a proof-of-concept rt-fMRI-NF study at 7 Tesla involving a single healthy participant imagining concrete objects. Based on this data and artificial data sets with similar (simulated) spatio-temporal structure and variable (injected) signal and noise, the dependence on noise is systematically assessed.

MAIN RESULTS: The participant in the proof-of-concept study exhibited robust activation patterns in the localizer session and managed to control the neural representation of a stimulus towards the selected target in the NF session. The offline analyses validated the rt-fMRI-NF results, showing that the rapid convergence to the target representation is noise-dependent.

SIGNIFICANCE: Our proof-of-concept study introduces a new NF method allowing the participant to navigate among different mental states. Compared to traditional NF designs (e.g. using a thermometer display to set the level of the neural signal), the proposed approach provides content-specific feedback to the participant and extra degrees of freedom to the experimenter enabling real-time control of the neural activity towards a target brain state without suggesting a specific mental strategy to the subject.

Original languageEnglish
Article number046015
Number of pages14
JournalJournal of neural engineering
Volume18
Issue number4
Early online date8 Mar 2021
DOIs
Publication statusPublished - Aug 2021

Keywords

  • neurofeedback
  • representational similarity
  • real-time fMRI
  • semantic representation

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