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

Abstract Decoded Neurofeedback (DecNef) enables the modulation of targeted brain activity patterns without subjective awareness through real-time fMRI feedback and reinforcement learning. Despite its proven effectiveness, the network mechanisms underlying DecNef 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 putative posterior control hub—consisting of posterior cingulate, precuneus, and lateral posterior parietal cortices—is stronger during DecNef compared to baseline (rank-biserial r = 0.20) and correlates positively with average neurofeedback score (Spearman ρ = 0.22). Comparisons across cognition- and perception-targeted DecNef further revealed meaningful differences in connections to and from the somatomotor network. Specifically, connections between somatomotor and control-default-attention networks are stronger during cognitive neurofeedback, whereas connections between somatomotor and subcortical-visual-limbic networks are stronger during perceptive DecNef. Whole-brain causal connectivity during DecNef also exhibited distinct network reorganizations, with 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.