Neurofeedback (NF) is a technique that enables individuals to learn self-regulation of brain activity in real-time. Promising findings indicate that NF can help healthy and clinical populations, yet a substantial proportion of participants fail to achieve self-modulation (“non-learners”). This study investigates potential neural and behavioral biomarkers underlying NF learning success using a dataset from a fMRI-based NF protocol targeting interhemispheric balance in the visual cortex for visual attention improvement. Participants were classified as learners or non-learners based on learning slopes across neurofeedback sessions. We investigated neural and behavioral differences between learners and non-learners using baseline assessments to identify potential biomarkers. Our analysis included voxel-based morphometry (VBM) to examine grey matter (GM) volume differences and seed-based resting-state functional connectivity (FC) analyses. Behavioral measures of attention and motivation were obtained from self-report questionnaires (QCM, CFQ). Post-training FC changes were also assessed. Contrary to our hypotheses, attentional and motivational scores did not differ significantly between learners and non-learners. On the other hand, VBM revealed that learners exhibited greater GM volume in the left middle cingulate cortex compared to non-learners, a region implicated in cognitive control and error monitoring. Baseline FC analyses indicated that learners exhibited stronger connectivity than non-learners, particularly within the seeds involving the salience network (SN), visual areas, frontal-parietal areas, and the default mode network (DMN), with the posterior cingulate cortex (PCC) emerging as a key hub. At the same time, learners showed increased connectivity thanks to the neurofeedback training involving occipital/insular and PCC seeds, suggesting NF-induced plasticity. These findings provide preliminary evidence that structural and functional brain characteristics, particularly concerning the cingulate GM volume and DMN connectivity, may contribute to NF learning success. Furthermore, NF may induce plasticity effects, particularly in reorganizing FC.