Neural and functional validation of fMRI-informed EEG model of right inferior frontal gyrus activity

Ayelet Or-Borichev, Guy Gurevitch, Ilana Klovatch, Ayam Greental, Yulia Lerner, Dino J. Levy, Talma Hendler*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The right inferior frontal gyrus (rIFG) is a region involved in the neural underpinning of cognitive control across several domains such as inhibitory control and attentional allocation process. Therefore, it constitutes a desirable neural target for brain-guided interventions such as neurofeedback (NF). To date, rIFG-NF has shown beneficial ability to rehabilitate or enhance cognitive functions using functional Magnetic Resonance Imaging (fMRI-NF). However, the utilization of fMRI-NF for clinical purposes is severely limited, due to its poor scalability. The present study aimed to overcome the limited applicability of fMRI-NF by developing and validating an EEG model of fMRI-defined rIFG activity (hereby termed "Electrical FingerPrint of rIFG"; rIFG-EFP). To validate the computational model, we employed two experiments in healthy individuals. The first study (n = 14) aimed to test the target engagement of the model by employing rIFG-EFP-NF training while simultaneously acquiring fMRI. The second study (n = 41) aimed to test the functional outcome of two sessions of rIFG-EFP-NF using a risk preference task (known to depict cognitive control processes), employed before and after the training. Results from the first study demonstrated neural target engagement as expected, showing associated rIFG-BOLD signal changing during simultaneous rIFG-EFP-NF training. Target anatomical specificity was verified by showing a more precise prediction of the rIFG-BOLD by the rIFG-EFP model compared to other EFP models. Results of the second study suggested that successful learning to up-regulate the rIFG-EFP signal through NF can reduce one's tendency for risk taking, indicating improved cognitive control after two sessions of rIFG-EFP-NF. Overall, our results confirm the validity of a scalable NF method for targeting rIFG activity by using an EEG probe.

Original languageEnglish
Article number119822
JournalNeuroImage
Volume266
DOIs
StatePublished - 1 Feb 2023

Funding

FundersFunder number
European Union's Flagship Framework Programme for Research and Innovation945539
Henry Crown Institute of Business Research in Israel
Innovation authority Israel ministry of commerce67951
Sagol Family Foundation for Brain Research

    Keywords

    • Cognitive-control
    • Healthy Population
    • Neurofeedback
    • Risk Taking
    • Self Neuromodulation

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