Previous research has noted that music can improve gait in several pathological conditions, including Parkinson's disease, Huntington's disease and stroke. Current research into auditory-motor interactions and the neural bases of musical rhythm perception has provided important insights for developing potential movement therapies. Specifically, neuroimaging studies show that rhythm perception activates structures within key motor networks, such as premotor and supplementary motor areas, basal ganglia and the cerebellum - many of which are compromised to varying degrees in Parkinson's disease. It thus seems likely that automatic engagement of motor areas during rhythm perception may be the connecting link between music and motor improvements in Parkinson's disease. This review seeks to describe the link, address core questions about its underlying mechanisms, and examine whether it can be utilized as a compensatory mechanism.

Communication between the prefrontal cortex and subcortical nuclei underpins the control and inhibition of behavior. However, the interactions in such pathways remain controversial. Using a stop-signal response inhibition task and functional imaging with analysis of effective connectivity, we show that the lateral prefrontal cortex influences the strength of communication between regions in the frontostriatal motor system. We compared 20 generative models that represented alternative interactions between the inferior frontal gyrus, presupplementary motor area (preSMA), subthalamic nucleus (STN), and primary motor cortex during response inhibition. Bayesian model selection revealed that during successful response inhibition, the inferior frontal gyrus modulates an excitatory influence of the preSMA on the STN, thereby amplifying the downstream polysynaptic inhibition from the STN to the motor cortex. Critically, the strength of the interaction between preSMA and STN, and the degree of modulation by the inferior frontal gyrus, predicted individual differences in participants' stopping performance (stop-signal reaction time). We then used diffusion-weighted imaging with tractography to assess white matter structure in the pathways connecting these three regions. The mean diffusivity in tracts between preSMA and the STN, and between the inferior frontal gyrus and STN, also predicted individual differences in stopping efficiency. Finally, we found that white matter structure in the tract between preSMA and STN correlated with effective connectivity of the same pathway, providing important cross-modal validation of the effective connectivity measures. Together, the results demonstrate the network dynamics and modulatory role of the prefrontal cortex that underpin individual differences in inhibitory control.

Cognitive deficits are very common in Parkinson's disease particularly for ‘executive functions’ associated with frontal cortico-striatal networks. Previous work has identified deficits in tasks that require attentional control like task-switching, and reward-based tasks like gambling or reversal learning. However, there is a complex relationship between the specific cognitive problems faced by an individual patient, their stage of disease and dopaminergic treatment. We used a bimodality continuous performance task during fMRI to examine how patients with Parkinson's disease represent the prospect of reward and switch between competing task rules accordingly. The task-switch was not separately cued but was based on the implicit reward relevance of spatial and verbal dimensions of successive compound stimuli. Nineteen patients were studied in relative ‘on’ and ‘off’ states, induced by dopaminergic medication withdrawal (Hoehn and Yahr stages 1–4). Patients were able to successfully complete the task and establish a bias to one or other dimension in order to gain reward. However the lateral prefrontal cortex and caudate nucleus showed a non-linear U-shape relationship between motor disease severity and regional brain activation. Dopaminergic treatment led to a shift in this U-shape function, supporting the hypothesis of differential neurodegeneration in separate motor and cognitive cortico–striato–thalamo–cortical circuits. In addition, anterior cingulate activation associated with reward expectation declined with more severe disease, whereas activation following actual rewards increased with more severe disease. This may facilitate a change in goal-directed behaviours from deferred predicted rewards to immediate actual rewards, particularly when on dopaminergic treatment. We discuss the implications for investigation and optimal treatment of this common condition at different stages of disease.

Dynamic causal modelling (DCM) of functional magnetic resonance imaging (fMRI) data offers new insights into the pathophysiology of neurological disease and mechanisms of effective therapies. Current applications can be used both to identify the most likely functional brain network underlying observed data and estimate the networks' connectivity parameters. We examined the reproducibility of DCM in healthy subjects (young 18–48 years, n = 27; old 50–80 years, n = 15) in the context of action selection. We then examined the effects of Parkinson's disease (50–78 years, Hoehn and Yahr stage 1–2.5, n = 16) and dopaminergic therapy. Forty-eight models were compared, for each of 90 sessions from 58 subjects. Model-evidences clustered according to sets of structurally similar models, with high correlations over two sessions in healthy older subjects. The same model was identified as most likely in healthy controls on both sessions and in medicated patients. In this most likely network model, the selection of action was associated with enhanced coupling between prefrontal cortex and the pre-supplementary motor area. However, the parameters for intrinsic connectivity and contextual modulation in this model were poorly correlated across sessions. A different model was identified in patients with Parkinson's disease after medication withdrawal. In “off” patients, action selection was associated with enhanced connectivity from prefrontal to lateral premotor cortex. This accords with independent evidence of a dopamine-dependent functional disconnection of the SMA in Parkinson's disease. Together, these results suggest that DCM model selection is robust and sensitive enough to study clinical populations and their pharmacological treatment. For critical inferences, model selection may be sufficient. However, caution is required when comparing groups or drug effects in terms of the connectivity parameter estimates, if there are significant posterior covariances among parameters.