Whole-brain causal connectivity during decoded neurofeedback: a meta study

Abstract

Decoded Neurofeedback (DecNef) enables modulation of targeted brain activity patterns without subjective awareness through multivariate pattern analysis, reinforcement learning, and real-time fMRI feedback. Despite its proven effectiveness, the causal mechanisms underlying DecNef and the neural dynamics that distinguish successful learners from those who struggle remain poorly understood. We conducted a meta-study using fMRI data from five DecNef experiments and extracted causal network dynamics as well as their associations with performance differences. Across studies, we found that connectivity within a posterior control hub-consisting of posterior cingulate, precuneus, and lateral posterior parietal cortices-is stronger during DecNef and positively correlates with neurofeedback success. Comparisons across cognition- and perception-targeted DecNef revealed separation in connections to somatomotor network, where connections between somatomotor and control-default-attention networks are larger during cognitive neurofeedback while connections between somatomotor and subcortical-visual-limbic networks are larger during perceptive DecNef. Whole-brain causal connectivity during DecNef further exhibited distinct network reorganizations, with greater subject-to-subject variability, increased engagement of control, limbic and visual, and decreased engagement of ventral and dorsal attention networks. Our results distill the complex and distributed network mechanisms underlying DecNef into dissociable roles for well-known functional subnetworks, thus advancing the research and clinical applications of decoded neurofeedback.