Task-Evoked Whole-Brain Functional Connectivity Predicts Post-Training Go-Choice Bias After Food Go/No-Go Training

Individual responses to food go/no-go training vary substantially, but the task-evoked network correlates of this variability remain unclear. This study tested whether large-scale functional connectivity during food choice predicts individual differences in post-training Go-choice bias. A behavioral sample of 172 young women completed food go/no-go training in which Go and No-Go cues were paired with value-matched food items, followed by an in-scanner binary food-choice task; usable task-based fMRI data were available for 162 participants. Task-modulated connectivity among 268 brain regions was estimated using generalized psychophysiological interaction analysis, and connectome-based predictive modeling with repeated 10-fold cross-validation was used to predict post-training Go-choice bias. Participants selected Go items above chance after training (59.3%). Whole-brain Go-No-Go connectivity showed modest cross-validated concurrent prediction of post-training Go-choice bias (combined network: mean ρ = 0.408, RMSE = 0.169, p < 0.001; positive network: ρ = 0.325, RMSE = 0.174, p < 0.001; negative network: ρ = 0.394, RMSE = 0.169, p < 0.001). Positive predictive edges prominently linked medial frontal and frontoparietal systems with the motor network and connected regions within the default mode network; medial frontal-salience connections were prominent in the distributed negative network. These findings identify candidate predictive connectivity patterns associated with individual variability in post-training Go-choice bias that require independent validation.