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Using Connectivity-Based Real-Time fMRI Neurofeedback to Modulate Attentional and Resting State Networks in People With High Trait Anxiety

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Using Connectivity-Based Real-Time fMRI Neurofeedback to Modulate Attentional and Resting State Networks in People With High Trait Anxiety

Elenor Morgenroth et al. Neuroimage Clin.

Abstract

High levels of trait anxiety are associated with impaired attentional control, changes in brain activity during attentional control tasks and altered network resting state functional connectivity (RSFC). Specifically, dorsolateral prefrontal cortex to anterior cingulate cortex (DLPFC - ACC) functional connectivity, thought to be crucial for effective and efficient attentional control, is reduced in high trait anxious individuals. The current study examined the potential of connectivity-based real-time functional magnetic imaging neurofeedback (rt-fMRI-nf) for enhancing DLPFC - ACC functional connectivity in trait anxious individuals. We specifically tested if changes in DLPFC - ACC connectivity were associated with reduced anxiety levels and improved attentional control. Thirty-two high trait anxious participants were assigned to either an experimental group (EG), undergoing veridical rt-fMRI-nf, or a control group (CG) that received sham (yoked) feedback. RSFC (using resting state fMRI), anxiety levels and Stroop task performance were assessed pre- and post-rt-fMRI-nf training. Post-rt-fMRI-nf training, relative to the CG, the EG showed reduced anxiety levels and increased DLPFC-ACC functional connectivity as well as increased RSFC in the posterior default mode network. Moreover, in the EG, changes in DLPFC - ACC functional connectivity during rt-fMRI-nf training were associated with reduced anxiety levels. However, there were no group differences in Stroop task performance. We conclude that rt-fMRI-nf targeting DLPFC - ACC functional connectivity can alter network connectivity and interactions and is a feasible method for reducing trait anxiety.

Figures

Fig. 1
Fig. 1
(A) Study design. (B) Example of visual gauge presented to participants during rt-fMRI-nf training. (C) Combined binary ROI across all subjects in the bilateral ACC and left DLPFC registered to standard MNI template.
Fig. 2
Fig. 2
(A) Mean DASS Anxiety scores by time-point and group, error bars show 95% confidence interval. (B) Time course of neurofeedback signal over training runs in percent change relative to functional localizer.
Fig. 3
Fig. 3
PPI analysis using left DLPFC seed region (purple) showing increased (red) and decreased (blue) functional connectivity in bilateral ACC ROI. Bar graphs show z-values from peak voxels separated by EG and CG. Results are Z-maps displayed at a threshold of p < .05 uncorrected for illustrative purposes. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 4
Fig. 4
Regression between PPI estimate of changes in functional connectivity between left DLPFC seed region and bilateral ACC ROI and changes in DASS Anxiety scores over rt-fMRI-nf training in the EG. Brain map shows positively (red) and negatively associated areas (blue). Results are Z-maps displayed at a threshold of p < .05 uncorrected for illustrative purposes. Scatter plot showing association between changes in DASS anxiety scores (Post – Pre training) and extracted PPI parameters from peak voxels in the ACC (based on 6 mm sphere). *A sphere of 4 mm was used to extract the parameters for this plot, as a 6 mm sphere had overlap with significant results in the opposite direction. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 5
Fig. 5
(A) Z-map for selected component based on group ICA analysis showing RSFC in CON, FPN and DMN regions (thresholded at ∣Z∣>2.5). (B) Increased RSFC in EG pre vs. post-rt-fMRI-nf training in the PCC (p-map, FWE corrected).

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