No abstract

Parkinson's disease is a chronic progressive neurodegenerative disorder characterized by resting tremor, slowness of movements, rigidity, gait disturbance and postural instability. Most investigations on Parkinson's disease focused on the basal ganglia, whereas the cerebellum has often been overlooked. However, increasing evidence suggests that the cerebellum may have certain roles in the pathophysiology of Parkinson's disease. Anatomical studies identified reciprocal connections between the basal ganglia and cerebellum. There are Parkinson's disease-related pathological changes in the cerebellum. Functional or morphological modulations in the cerebellum were detected related to akinesia/rigidity, tremor, gait disturbance, dyskinesia and some non-motor symptoms. It is likely that the major roles of the cerebellum in Parkinson's disease include pathological and compensatory effects. Pathological changes in the cerebellum might be induced by dopaminergic degeneration, abnormal drives from the basal ganglia and dopaminergic treatment, and may account for some clinical symptoms in Parkinson's disease. The compensatory effect may help maintain better motor and non-motor functions. The cerebellum is also a potential target for some parkinsonian symptoms. Our knowledge about the roles of the cerebellum in Parkinson's disease remains limited, and further attention to the cerebellum is warranted.

Despite considerable advances toward understanding the molecular pathophysiology of the neurodegenerative dementias, the mechanisms linking molecular changes to neuropathology and the latter to clinical symptoms remain largely obscure. Connectivity is a distinctive feature of the brain and the integrity of functional network dynamics is critical for normal functioning. A better understanding of network disruption in the neurodegenerative dementias may help bridge the gap between molecular changes, pathology and symptoms. Recent findings on functional network disruption as assessed with “resting-state” or intrinsic connectivity fMRI and EEG/MEG have shown distinct patterns of network disruption across the major neurodegenerative diseases. These network abnormalities are relatively specific to the clinical syndromes, and in Alzheimer's disease and frontotemporal dementia network disruption tracks the pattern of pathological changes. These findings may have a practical impact on diagnostic accuracy, allowing earlier detection of neurodegenerative diseases even at the pre-symptomatic stage, and tracking of disease progression.

Patients with Parkinson's disease have great difficulty performing learned movements automatically. The neural contribution to the problem has not been identified. In the current study, we used functional magnetic resonance imaging (fMRI) to investigate the underlying neural mechanisms of movement automaticity in Parkinson's disease patients. Fifteen patients with Parkinson's disease were recruited. Three patients were finally excluded because they could not achieve automaticity. The remaining 12 patients were aged from 52 to 67 years, with a mean age of 61.2 years. Controls included 14 age-matched normal subjects. The subjects were asked to practise four tasks, including two self-initiated, self-paced sequences of finger movements with different complexity until they could perform the tasks automatically. Two dual tasks were used to evaluate automaticity. For dual tasks, subjects performed a visual letter-counting task simultaneously with the sequential movements. Twelve normal subjects performed all sequences automatically. All patients performed sequences correctly; 12 patients could perform the simpler sequence automatically; and only 3 patients could perform the more complex sequence automatically. fMRI results showed that for both groups, sequential movements activated similar brain regions before and after automaticity was achieved. No additional activity was observed in the automatic condition. In normal subjects, many areas had reduced activity at the automatic stage, whereas in patients, only the bilateral superior parietal lobes and left insular cortex were less activated. Patients had greater activity in the cerebellum, premotor area, parietal cortex, precuneus and prefrontal cortex compared with normal subjects while performing automatic movements. We conclude that Parkinson's disease patients can achieve automaticity after proper training, but with more difficulty. Our study is the first to demonstrate that patients with Parkinson's disease require more brain activity to compensate for basal ganglia dysfunction in order to perform automatic movements.

Resting state brain activity in Parkinson's disease (PD) can give clues to the pathophysiology of the disorder, and might be helpful in diagnosis, but it has never been explored using functional MRI (fMRI). In the current study, we used a regional homogeneity (ReHo) method to investigate PD-related modulations of neural activity in the resting state. FMRIs were acquired in 22 patients with PD at both before and after levodopa administration, as well as in 22 age- and sex-matched normal controls. In the PD group compared with the healthy controls, we found ReHo decreased in extensive brain regions, including the putamen, thalamus, and supplementary motor area; and increased in some other areas, including the cerebellum, primary sensorimotor cortex, and premotor area. The ReHo off medication was negatively correlated with the Unified Parkinson's Disease Rating Scale (UPDRS) in the putamen and some other regions, and was positively correlated with the UPDRS in the cerebellum. Administration of levodopa relatively normalized ReHo. Our findings demonstrate that neural activity in the resting state is changed in patients with PD. This change is secondary to dopamine deficiency, and related to the severity of the disease. The different neuronal activity at the baseline state should be considered in explaining fMRI findings obtained during tasks.

No abstract

Bradykinesia is the most important feature contributing to motor difficulties in Parkinson’s disease (PD). However, the pathophysiology underlying bradykinesia is not fully understood. One important aspect is that PD patients have difficulty in performing learned motor skills automatically, but this problem has been generally overlooked. Here we review motor automaticity associated motor deficits in PD, such as reduced arm swing, decreased stride length, freezing of gait, micrographia and reduced facial expression. Recent neuroimaging studies have revealed some neural mechanisms underlying impaired motor automaticity in PD, including less efficient neural coding of movement, failure to shift automated motor skills to the sensorimotor striatum, instability of the automatic mode within the striatum, and use of attentional control and/or compensatory efforts to execute movements usually performed automatically in healthy people. PD patients lose previously acquired automatic skills due to their impaired sensorimotor striatum, and have difficulty in acquiring new automatic skills or restoring lost motor skills. More investigations on the pathophysiology of motor automaticity, the effect of L-dopa or surgical treatments on automaticity, and the potential role of using measures of automaticity in early diagnosis of PD would be valuable.

We used functional magnetic resonance imaging (fMRI) and dual tasks to investigate the physiology of how movements become automatic. Normal subjects were asked to practice some self-initiated, self-paced, memorized sequential finger movements with different complexity until they could perform the tasks automatically. Automaticity was evaluated by having subjects perform a secondary task simultaneously with the sequential movements. Our secondary task was a letter-counting task where subjects were asked to identify the number of times a target letter from the letter sequences was seen. Only the performances that achieved high accuracy in both single and dual tasks were considered automatic. The fMRI results before and after automaticity was achieved were compared. Our data showed that for both conditions, sequential movements activated similar brain regions. No additional activity was observed in the automatic condition. There was less activity in bilateral cerebellum, presupplementary motor area, cingulate cortex, left caudate nucleus, premotor cortex, parietal cortex, and prefrontal cortex during the automatic stage. These findings suggest that most of the motor network participates in executing automatic movements and that it becomes more efficient as movements become more automatic. Our results do not provide evidence for any area to become more activated for automatic movements.