Neuromodulators regulate large-scale brain network topology to support adaptive behaviour. Disease models offer a unique window into how neuromodulatory systems impact large-scale brain network organisation. Here, we take advantage of Parkinson’s disease—with its profound dopaminergic loss and pro-dopaminergic treatment strategies—to inform how dopamine may influence large-scale brain organisation. In 27 people with Parkinson’s disease, resting-state scans were obtained on their regular dopamine medication and following overnight withdrawal of medication. Nineteen matched controls provided normative data. Gradients of brain organisation were examined using dimensionality reduction techniques. For single gradients, when individuals were on their dopamine medication, we observed a shift in higher-order networks towards somatomotor anchors. When interrogated in the multi-dimensional gradient space, we found that dopamine medication enhanced separation between functionally discrete sensory and higher-order networks. This increase in dispersion was dependent on an individual’s dopamine dose level, and increased dispersion was more apparent in regions enriched with dopamine receptor (DRD2) gene expression. Together, these findings substantiate a role for dopamine in modulating large-scale functional brain organisation. Our findings further confirm that medication targeting the dopamine system may achieve its benefit by restoring aspects of network topology, and suggest new hypotheses about how dopamine medication is influencing large-scale functional brain organisation in Parkinson’s disease.

The ability to adapt to changes in the environment is essential for skilled performance, especially in competitive sports and events, where experts consistently perform at the highest level, rapidly adapting to unpredictable conditions. Current studies have identified cortical-cortical interactions between the premotor and primary motor cortex during expert performance; however, while these interactions are important for planning and execution, our understanding of the mechanisms underlying learning, feedback, and adaptation remains unclear. Subcortical structures, such as the cerebellum, have dense connections with the cerebral cortex through which they provide precise topological constraints that could putatively play a crucial role in fast, accurate task execution. To test this hypothesis, we tracked cortical, subcortical, and cerebellar BOLD activity during a visuomotor rotation task in which participants executed a visual cue-driven, ballistic motor task across three conditions: at baseline; following a 45° clockwise motor rotational perturbation; and then within a follow-up (washout) condition. We observed increased recruitment of primary visual, basal ganglia, and cerebellar regions that robustly covaried with fast, accurate performance across all conditions (baseline, rotation, and washout). Tracking individualised performance across participants, we observed three distinct groups: experts (consistently fast and accurate), adapters (initially poor with improvement to expert-level), and non-adapters (initially good but ultimately poor performance). The experts and adapter groups demonstrated performances that were robust to changes in conditions and were more variable in their neural signatures between trials, whereas the performance of non-adapters decreased with changes in conditions and were characterised by less variable neural signatures. These results aligned with the tenets of the differential learning theory. To establish the validity of our interpretation of these whole-brain signatures and behavioural patterns, the neuroimaging results were reproduced by training recurrent neural networks representing each group and analysing their resultant activity patterns. Together, these results provide evidence for cerebellar and basal ganglia contributions to expertise in adaptation and suggest a possible connection between variable brain patterns and robust performance.