Depression in Parkinson's disease.

In contrast to depression, motor symptoms in PD have been extensively researched. The result is a detailed understanding of the pathophysiology of abnormal movements (162). Commitment to, and funding for, a well thought-out depression research plan, such as that presented by the working group at the National Institutes of Health (6), will bring similar theoretical understanding and patient relief for the most disabling of all PD symptoms (3-5)--depression.

Relationships among the metabolic patterns that correlate with mnemonic, visuospatial, and mood symptoms in Parkinson's disease.

OBJECTIVE: A multivariate analysis of baseline brain metabolism was used to investigate the relationships among pathophysiological mechanisms responsible for cognitive dysfunction and dysphoria in nondemented patients with Parkinson's disease. METHOD: Using [(18)F]fluorodeoxyglucose positron emission tomography and neuropsychological tests, the authors studied 15 nondemented patients who had Parkinson's disease without major depression (DSM-III-R). Their mean age was 59.2 years (SD=9.2), the mean rating of Parkinson's disease stage (Hoehn and Yahr scale) was 3.3 (SD=0.9), and all had Mini-Mental State Examination scores of 24 or higher. To identify specific regional patterns of brain metabolism associated with abnormal cognitive and mood functioning, the data were analyzed by using brain-behavior partial least squares. This multivariate voxel-based analysis allowed detection of significant topographic patterns of metabolic activity and quantification of the extent to which each topographic pattern correlated with scores on mnemonic, visuospatial, and dysphoric tests. RESULTS: Two significant, independent topographic patterns were identified. Pattern 1 included parieto-occipito-temporal and medial temporal brain regions, and pattern 2 included the lateral frontal and anterior limbic cortex. Patterns 1 and 2 exhibited a double dissociation in their behavioral correlates: pattern 1 correlated with both visuospatial and mnemonic functioning but not with dysphoria; pattern 2 correlated with dysphoria but not with the cognitive measures. CONCLUSIONS: The authors used the independence of topographic patterns and the size of correlations between topographic patterns and behavior to infer relationships among the pathophysiological processes responsible for the correlations. The finding that mildly abnormal mnemonic and visuospatial functioning correlated with the same topographic pattern suggests that a common pathophysiology underlies this marker of cognition in Parkinson's disease. By contrast, the independence of the two topographic patterns supports the notion that different mechanisms underlie cognitive and dysphoric symptoms in nondemented patients with Parkinson's disease.

Anticholinesterase effect on motor kinematic measures and brain activation in Parkinson's disease.

Anticholinesterase (AChE) drugs are being prescribed off label for nonmotor symptoms in Parkinson's disease (PD). Theoretically, these drugs can impair motor function. A small literature suggests AChE therapy has little effect on clinical motor evaluation; however, no study has made objective motor kinematic measures or evaluated brain function. We hypothesized that even if clinical examination was normal in PD patients on dopamine therapy, (1) sensitive kinematic measures would be abnormal during AChE therapy or (2) normal kinematic measures would be maintained by compensatory brain activation. We carried out a randomized, double-blind, placebo-controlled trial of 8 weeks donepezil (10 mg/day) in 17 PD subjects. Subjects carried out a computerized motor task during a positron emission tomography (PET) scan before starting the drug and again after 8 weeks of donepezil or placebo. Kinematic measures of motor function and PET scans were analyzed to compare the effects of donepezil and placebo. Neither placebo nor donepezil altered motor kinematic measures. Furthermore, movement integrity while on donepezil was maintained without compensatory brain activity. Donepezil 10 mg/day can be given for nonmotor symptoms in PD without adverse motor effects or compensatory brain activity.

Early stage Parkinson's disease patients and normal volunteers: comparative mechanisms of sequence learning.

Early-stage nondemented Parkinson's disease (PD(es)) patients can learn short but not long sequences as well as controls. We have previously shown that to achieve normal performance, PD(es) patients activated the same right-sided cortical regions as controls plus the homologous left sided cortex and bilateral cerebellum. In this study, we evaluated two related hypotheses to explain the behavioral abnormalities and the increased bilateral brain activation observed in the PD(es) group. Hypothesis 1 proposed that PD(es) patients recruit regions from a normal bilateral network specialized for sequence learning that healthy controls would activate if performing difficult tasks. Thus, PD(es) patients can learn short sequences as well as controls. Hypothesis 2 proposed that information processing within the network in the PD(es) group is impaired. Thus, PD(es) patients cannot learn as difficult a sequence as controls. To test hypothesis 1, we increased task difficulty and statistical power in the control group and showed that the control and the PD(es) groups activated the same regions. To test hypothesis 2, we analyzed the equal performance data using two partial least squares (PLS) multivariate analyses. The task-PLS analysis showed that to perform equally with controls, the PD(es) group expressed the normal bilateral network more than the control group. The behavior-PLS analysis showed that the correlation between learning performance and regional activation was significantly different between the groups. We conclude that PD(es) patients have near normal learning if task difficulty is moderate because they can recruit additional regions from a normal bilateral network specialized for sequence learning. However, when a difficult task would normally require bilateral activation, PD(es) patients fail to learn because information processing within the network is impaired. Hum. Brain Mapp. 20:246-258, 2003.

Executive processes in Parkinson's disease: FDG-PET and network analysis.

It is assumed widely that the clinical expression of Parkinson's Disease (PD), both motor and cognitive, is subtended by topographically distributed brain networks. However, little is known about the functional neuroanatomy of executive dysfunction in PD. Our objective was to validate further in a PD group the use of network analysis to assess the relationship between executive processes and pathological disorganization of frontostriatal networks. We studied 15 patients with idiopathic PD, and 7 age-matched normal controls, using resting [(18)F]fluorodeoxyglucose (FDG) and high-resolution positron emission tomography (PET). We carried out network analysis on regional metabolic data to identify specific covariation patterns associated with motor and executive dysfunction. We detected two independent patterns relating respectively to the two clinical abnormalities. The first pattern (principal component 1) was topographically similar to that described previously in other PD populations. Subject scores for this pattern discriminated patients from controls and correlated significantly with bradykinesia ratings (P = 0.013, r = 0.655) in PD patients. The second pattern (principal component 2) was characterized by relative ventromedial frontal, hippocampal, and striatal hypometabolism, associated with mediodorsal thalamic hypermetabolism. In the PD group, scores from this pattern correlated with scores on the conditional associative learning (CAL; P = 0.01, r = 0.690) and the Brown Peterson paradigm (BPP; P = 0.017, r = -0.651) tests, respectively assessing strategy and planning, and working memory. According to these findings, the networks subserving bradykinesia and executive dysfunction in PD seems to be topographically distinct and to involve different aspects of subcortico-cortical processing.

Pallidal stimulation for parkinsonism: improved brain activation during sequence learning.

We used (15)O-labeled water and positron emission tomography to assess the effect of deep brain stimulation of the internal globus pallidus on motor sequence learning in Parkinson's disease. Seven right-handed patients were scanned on and off stimulation while they were performing a motor sequence learning task and a kinematically matched motor execution reference task. The scans were performed after a 12-hour medication washout. Stimulation parameters were adjusted for maximal motor improvement; experimental task parameters were held constant across stimulation conditions. Internal globus pallidus stimulation improved motor ratings by 37% (p < 0.01). During the sequence learning task, stimulation improved performance as measured by several correct anticipatory movements (p < 0.01) and by verbal report (p < 0.001). Concurrent positron emission tomography imaging during learning demonstrated significant (p < 0.01) increases in brain activation with stimulation in the left dorsolateral prefrontal cortex, bilaterally in premotor cortex, and in posterior parietal and occipital association areas. Stimulation did not affect the activity of these regions during the performance of the motor execution reference task. These findings suggest that internal globus pallidus deep brain stimulation can enhance the activity of prefrontal cortico-striato-pallidothalamic loops and related transcortical pathways. Improved sequence learning with stimulation may be directly related to these functional changes.

Tc-99m ethylene cysteinate dimer SPECT in the differential diagnosis of parkinsonism.

Positron emission tomography (PET) and network analysis have been used to identify a reproducible pattern of regional metabolic covariation that is associated with idiopathic Parkinson's disease (PD). The activity of this PD-related pattern can be quantified in individual subjects and used to discriminate PD patients from atypical parkinsonians. Because PET is not commonly available, we sought to determine whether similar discrimination could be achieved using more routine single photon emission computed tomography (SPECT) perfusion methods. Twenty-three subjects with PD (age, 63 +/- 9 years), 22 subjects with multiple system atrophy (MSA; age, 64 +/- 7 years), and 20 age-matched healthy controls (age, 62 +/- 13 years) underwent SPECT imaging of regional cerebral perfusion with Tc-99m ethylene cysteinate dimer (ECD). Using network analysis, we determined whether a PD-related pattern existed in the SPECT data, and whether its expression discriminated PD from MSA patients. Additionally, we compared the accuracy of group discrimination achieved by this pattern with that of the PET-derived PD-related pattern applied to the SPECT data. Network analysis of the SPECT data identified a significant pattern characterized by relative increases in cerebellar, lentiform, and thalamic perfusion covarying with decrements in the frontal operculum and in the medial temporal cortex. Subject scores for this pattern discriminated PD patients from controls (P < 0.01) and from MSA patients (P < 0.03). Subject scores for the PET-derived PD-related pattern computed in the individual SPECT scans more accurately distinguished PD patients from controls (P < 0.005) and from MSA patients (P = 0.0002). A significant PD-related covariance pattern can be identified in SPECT perfusion data. Moreover, the disease related pattern identified previously with PET can be applied to individual SPECT perfusion scans to provide group discrimination between PD patients, healthy controls, and individuals with MSA. Because of significant individual subject overlap between groups, however, the clinical utility of this method in the differential diagnosis of Parkinsonism remains uncertain.

Primary dystonia: is abnormal functional brain architecture linked to genotype?

The DYT1 dystonia mutation is associated with an abnormal metabolic brain network characterized by hypermetabolism of the basal ganglia, supplementary motor area, and the cerebellum. In this study, we quantified the activity of this network in carriers of other dystonia mutations to determine whether this functional abnormality is linked to genotype. The findings suggest that the DYT1 metabolic topography is not genotype specific and may be present in carriers of other dystonia mutations.

Learning networks in health and Parkinson's disease: reproducibility and treatment effects.

In a previous H(2) (15)O/PET study of motor sequence learning, we used principal components analysis (PCA) of region of interest (ROI) data to identify performance-related activation patterns in normal subjects and patients with Parkinson's disease (PD). In the present study, we determined whether these patterns predicted learning performance in subsequent normal and untreated PD cohorts. Using a voxel-based PCA approach, we correlated the changes in network activity that occurred during antiparkinsonian treatment and their relationship to learning performance. We found that the previously identified ROI-based patterns correlated with learning performance in the prospective normal (P < 0.01) and untreated PD (P < 0.05) cohorts. Voxel analysis revealed that target retrieval was related to a network characterized by bilateral activation of the dorsolateral prefrontal, premotor and anterior cingulate cortex, the precuneus, and the occipital association areas as well as the right ventral prefrontal and inferior parietal regions. Target acquisition was associated with a different network involving activation of the caudate, putamen, and right dentate nucleus, as well as the left ventral prefrontal and inferior parietal areas. Antiparkinsonian therapy gave rise to changes in retrieval performance that correlated with network modulation (P < 0.01). Increases in network activation and learning performance occurred with internal pallidal deep brain stimulation (GPi DBS); decrements in these measures were present with levodopa. Our findings suggest that network analysis of activation data can provide stable descriptors of learning performance. Network quantification can provide an objective means of assessing the effects of therapy on cognitive functioning in neurodegenerative disorders.