Cognitive Behavioral Therapy for Anxiety in Parkinson's Disease: A Randomized Controlled Trial.

BACKGROUND: Anxiety disorders are among the most prevalent and disabling neuropsychiatric syndromes in patients with Parkinson's disease (PD), but no randomized controlled treatment trials of anxiety have been published to date. OBJECTIVE: The aim of this study was to assess the effectiveness of cognitive behavioral therapy (CBT) in the treatment of anxiety in patients with PD. METHODS: Forty-eight patients with PD with anxiety were randomized 1:1 between CBT and clinical monitoring only (CMO). The CBT program was developed to specifically address anxiety symptoms in PD and consisted of 10 weekly sessions. Assessments were conducted by blinded assessors at baseline, at the end of the intervention, after 3 months, and after 6 months (CBT group only). Main outcome measures were the Hamilton Anxiety Rating Scale (HARS) and the Parkinson Anxiety Scale (PAS). RESULTS: Both the CBT and CMO groups showed clinically relevant improvement. Although there was no between-group difference in outcome on the Hamilton Anxiety Rating Scale (6.7-point reduction in the CBT group versus 3.9-point reduction in the CMO group; P = 0.15), there was both a statistically significant and a clinically relevant between-group difference on the total PAS in favor of CBT (9.9-point reduction in the CBT group versus 5.2-point reduction in the CMO group; P = 0.012), which was due to improvement on the PAS subscales for episodic (situational) anxiety and avoidance behavior. This greater improvement was maintained at 3- and 6-month follow-ups. CONCLUSION: CBT is an effective treatment for anxiety in patients with PD and reduces situational and social anxiety, as well as avoidance behavior. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Electroencephalography-based machine learning for cognitive profiling in Parkinson's disease: Preliminary results.

BACKGROUND: Cognitive symptoms are common in patients with Parkinson's disease. Characterization of a patient's cognitive profile is an essential step toward the identification of predictors of cognitive worsening. OBJECTIVE: The aim of this study was to investigate the use of the combination of resting-state EEG and data-mining techniques to build characterization models. METHODS: Dense EEG data from 118 patients with Parkinson's disease, classified into 5 different groups according to the severity of their cognitive impairments, were considered. Spectral power analysis within 7 frequency bands was performed on the EEG signals. The obtained quantitative EEG features of 100 patients were mined using 2 machine-learning algorithms to build and train characterization models, namely, support vector machines and k-nearest neighbors models. The models were then blindly tested on data from 18 patients. RESULTS: The overall classification accuracies were 84% and 88% for the support vector machines and k-nearest algorithms, respectively. The worst classifications were observed for patients from groups with small sample sizes, corresponding to patients with the severe cognitive deficits. Whereas for the remaining groups for whom an accurate diagnosis was required to plan the future healthcare, the classification was very accurate. CONCLUSION: These results suggest that EEG features computed from a daily clinical practice exploration modality in-that it is nonexpensive, available anywhere, and requires minimal cooperation from the patient-can be used as a screening method to identify the severity of cognitive impairment in patients with Parkinson's disease. © 2018 International Parkinson and Movement Disorder Society.

Cognitive phenotypes in parkinson's disease differ in terms of brain-network organization and connectivity.

Cognitive deficits are common in Parkinson's disease and we suspect that dysfunctions of connected brain regions can be the source of these deficits. The aim of the present study was to investigate changes in whole-brain intrinsic functional connectivity according to differences in cognitive profiles in Parkinson's disease. 119 participants were enrolled and divided into four groups according to their cognitive phenotypes (determined by a cluster analysis): (i) 31 cognitively intact patients (G1), (ii) 31 patients with only slight mental slowing (G2), (iii) 43 patients with mild to moderate deficits mainly in executive functions (G3), (iv) 14 patients with severe deficits in all cognitive domains (G4-5). Rs-fMRI whole-brain connectivity was examined by two complementary approaches: graph theory for studying network functional organization and network-based statistics (NBS) for exploring functional connectivity amongst brain regions. After adjustment for age, duration of formal education and center of acquisition, there were significant group differences for all functional organization indexes: functional organization decreased (G1 > G2 > G3 > G4-5) as cognitive impairment worsened. Between-group differences in functional connectivity (NBS corrected, P < 0.01) mainly concerned the ventral prefrontal, parietal, temporal and occipital cortices as well as the basal ganglia. In Parkinson's disease, brain network organization is progressively disrupted as cognitive impairment worsens, with an increasing number of altered connections between brain regions. We observed reduced connectivity in highly associative areas, even in patients with only slight mental slowing. The association of slowed mental processing with loss of connectivity between highly associative areas could be an early marker of cognitive impairment in Parkinson's disease and may contribute to the detection of prodromal forms of Parkinson's disease dementia. Hum Brain Mapp 38:1604-1621, 2017. © 2016 Wiley Periodicals, Inc.

Modeling anxiety in Parkinson's disease.

BACKGROUND: The aim of this work was to construct a model for anxiety in PD and compare the relative contributions of PD-specific and -nonspecific general population risk factors for anxiety in this model. METHODS: Structural equation modeling of associations of risk factors with the anxiety outcome using a cross-sectional data set of 342 patients with PD were used. RESULTS: A model with acceptable to good fit was generated that explained 65% of the variance in anxiety scores. A previous history of depression and the severity of the depressive symptoms scored on the Hamilton Depression Rating Scale were the only nonspecific variables with a direct effect on anxiety. The presence of motor fluctuations and disease-related decline in activities of daily living were PD-specific markers of anxiety. Nonspecific risk factors had a greater influence in the model than PD-specific risk factors. Standardized regression coefficients suggested that the Hamilton Depression Rating Scale score was the most important contributor to the variation in anxiety. A post-hoc analysis showed that the effects of the following variables on anxiety levels were fully mediated by depression: sex; family history of depression; previous history of anxiety; cognitive status; difficulties in non-disease-specific activities of daily living; and severity of motor signs. CONCLUSION: In this cross-sectional study, we showed that nonspecific general population risk factors are more important markers for anxiety than PD-specific risk factors. Depression was the most prominent marker. PD-specific markers for anxiety appear to be more situational and related to off periods and disease-specific disturbances of activities of daily living.

The spectrum of cognitive disorders in Parkinson's disease: a data-driven approach.

The objective of this study was to identify different cognitive phenotypes in Parkinson's disease (PD) using a data-driven approach. A model-based cluster analysis was conducted on the neuropsychological test results of 558 PD patients from 2 European movement disorder centers (Lille, n = 403; Maastricht, n = 155). The number of clusters was determined according to their clinical relevance as well as on the basis of 3 statistical criteria: the cubic cluster criterion, the pseudo F statistic, and the total squared correlation ratio (R(2)). A factorial discriminant analysis was performed to assess the quality of the cluster's separation. Descriptive variables were used to further characterize the clusters. A 5-cluster model was considered the clinically most relevant. The 5 clusters comprised: (1) cognitively intact patients (19.39%); (2) patients without cognitive deficits but with slight mental slowing (41.29%); (3) patients with slightly impaired overall cognitive efficiency and deficits in all cognitive domains except recognition memory (12.93%); (4) patients with severe mental slowing, impaired overall cognitive efficiency, and severe cognitive impairment in all domains, including memory (23.88%); and (5) patients with very severe impairment in all cognitive domains (2.51%). Cognitively intact patients were significantly younger and had received more years of formal education. Patients in the last 3 clusters had more severe motor symptoms, longer disease duration, and more axial signs. In the last cluster, most patients were demented. Our results confirm the heterogeneity of cognitive presentations in PD, ranging from cognitively intact patients with rather high levels of performance in each cognitive domain to very severely impaired patients.

Cognitive Behavioral Therapy for Anxiety in Parkinson's Disease Induces Functional Brain Changes.

BACKGROUND: Cognitive behavioral therapy (CBT) reduces anxiety symptoms in patients with Parkinson's disease (PD). OBJECTIVE: The objective of this study was to identify changes in functional connectivity in the brain after CBT for anxiety in patients with PD. METHODS: Thirty-five patients with PD and clinically significant anxiety were randomized over two groups: CBT plus clinical monitoring (10 CBT sessions) or clinical monitoring only (CMO). Changes in severity of anxiety symptoms were assessed with the Parkinson Anxiety Scale (PAS). Resting-state functional brain MRI was performed at baseline and after the intervention. Functional networks were extracted by an Independent Component Analysis (ICA). Functional connectivity (FC) changes between structures involved in the PD-related anxiety circuits, such as the fear circuit (involving limbic, frontal, and cingulate structures) and the cortico-striato-thalamo-cortical limbic circuit, and both within and between functional networks were compared between groups and regressed with anxiety symptoms changes. RESULTS: Compared to CMO, CBT reduced the FC between the right thalamus and the bilateral orbitofrontal cortices and increased the striato-frontal FC. CBT also increased the fronto-parietal FC within the central executive network (CEN) and between the CEN and the salience network. After CBT, improvement of PAS-score was associated with an increased striato-cingulate and parieto-temporal FC, and a decreased FC within the default-mode network and between the dorsal attentional network and the language network. CONCLUSION: CBT in PD-patients improves anxiety symptoms and is associated with functional changes reversing the imbalance between PD-related anxiety circuits and reinforcing cognitive control on emotional processing.

Grey matter abnormalities are associated only with severe cognitive decline in early stages of Parkinson's disease.

Cognitive impairment is common in Parkinson's disease (PD), yet with large heterogeneity in the range and course of deficits. In a cross-sectional study, 124 PD patients underwent extensive clinical and neuropsychological assessment as well as a 3T MRI scan of the brain. Our aim was to identify differences in grey matter volume and thickness, as well as cortical folding, across different cognitive profiles as defined through a data-driven exploratory cluster analysis of neuropsychological data. The identified cognitive groups ranged from cognitively intact patients to patients with severe deficits in all cognitive domains, whilst showing comparable levels of motor disability and disease duration. Each group was compared to the cognitively intact PD group using voxel- and vertex-based morphometry. Results revealed widespread age-related grey matter abnormalities associated with progressive worsening of cognitive functions in mild PD. When adjusted for age, significant differences were only seen between cognitively intact and severely affected PD patients and these were restricted to the right posterior cingulate and the right precuneus. Reduced cortical thickness was seen in the right inferior temporal gyrus and reduced folding in the right temporal region. As these differences were not associated with age, we assume that they are associated with underlying pathology of the cognitive decline. Given the limited involvement of grey matter differences, and the absence of differences in vascular changes across the groups, we hypothesize a more important role for white matter tract changes in cognitive decline in PD.

Neurobiological correlates of emotional processing in Parkinson's disease: A systematic review of experimental studies.

Deficits in emotional processing in patients with Parkinson's disease (PD) have received increasing interest over the past decades. In this systematic review, we present the results of 18 behavioral studies that have examined the neurobiological base of emotional processing in PD. Multiple aspects of emotional processing have been studied, using a variety of research methods. Deficits in PD are mainly related to autonomic and perceptive processing of intense emotional stimuli, which is accompanied by structural and functional neurobiological abnormalities in predominantly ventral regions of affective neurocircuitry. These structures are more strongly dependent on dopaminergic neurotransmission than the dorsal structures of affective neurocircuitry, which are more related to the cognitive and regulatory aspects of emotion and appear to remain largely intact in PD patients. Considering the importance of active dopaminergic neurotransmission, PD can serve as a prolific model for studying the neurobiological correlates of normal human emotional behavior as well as psychiatric disorders such as anxiety, depression, and apathy. Moreover, the fact that PD patients are able to cognitively regulate or modulate their emotional responses despite reduced dopamine supplies, can have important implications for the treatment of affective disorders not only in PD patients but in the general population likewise.

An fMRI study into emotional processing in Parkinson's disease: Does increased medial prefrontal activation compensate for striatal dysfunction?

BACKGROUND: Apart from a progressive decline of motor functions, Parkinson's disease (PD) is also characterized by non-motor symptoms, including disturbed processing of emotions. This study aims at assessing emotional processing and its neurobiological correlates in PD with the focus on how medicated Parkinson patients may achieve normal emotional responsiveness despite basal ganglia dysfunction. METHODS: Nineteen medicated patients with mild to moderate PD (without dementia or depression) and 19 matched healthy controls passively viewed positive, negative, and neutral pictures in an event-related blood oxygen level-dependent functional magnetic resonance imaging study (BOLD-fMRI). Individual subjective ratings of valence and arousal levels for these pictures were obtained right after the scanning. RESULTS: Parkinson patients showed similar valence and arousal ratings as controls, denoting intact emotional processing at the behavioral level. Yet, Parkinson patients showed decreased bilateral putaminal activation and increased activation in the right dorsomedial prefrontal cortex (PFC), compared to controls, both most pronounced for highly arousing emotional stimuli. CONCLUSIONS: Our findings revealed for the first time a possible compensatory neural mechanism in Parkinson patients during emotional processing. The increased medial PFC activity may have modulated emotional responsiveness in patients via top-down cognitive control, therewith restoring emotional processing at the behavioral level, despite striatal dysfunction. These results may impact upon current treatment strategies of affective disorders in PD as patients may benefit from this intact or even compensatory influence of prefrontal areas when therapeutic strategies are applied that rely on cognitive control to modulate disturbed processing of emotions.

Cognitive disorders in Parkinson's disease: Confirmation of a spectrum of severity.

INTRODUCTION: Clinical presentation and progression of cognitive disorders in Parkinson's disease (PD) is heterogeneous. Our objective was to confirm prospectively a previous exploratory cluster analysis based on retrospective data that identified five cognitive phenotypes in PD. METHODS: A model-based confirmatory cluster analysis was conducted on the results of neuropsychological tests administered in 156 PD patients from two European movement disorder centers (Lille, n = 81; Maastricht, n = 75). The number of clusters was determined on the basis of statistical criteria as well as clinical plausibility. A factorial discriminant analysis assessed the quality of the clusters' separation. RESULTS: A five-cluster model was statistically superior and clinically the most relevant. These clusters can be described as follows: 1) cognitively intact patients with high level of performance in all cognitive domains (25.64%), 2) cognitively intact patients slightly slower than those in cluster 1 (26.92%), 3) patients with deficits in executive functions (37.18%), 4) patients with severe deficits in all cognitive domains, particularly executive functions (3.20%), 5) patients with severe deficits in all cognitive domains, particularly working memory and recall in verbal episodic memory (7.05%). The groups differed in terms of age, apathy and frequency of hallucinations that were all higher in the clusters with cognitive deficits, and the duration of formal education was lower in those groups. CONCLUSION: We confirm our previous exploratory analysis. Cognitive disorders in PD patients are heterogeneous and can be separated in five clusters ranging from patients with performance in the normal range to patients with severe disorders in all cognitive domains.

Modeling depression in Parkinson disease: disease-specific and nonspecific risk factors.

OBJECTIVE: To construct a model for depression in Parkinson disease (PD) and to study the relative contribution of PD-specific and nonspecific risk factors to this model. METHODS: Structural equation modeling of direct and indirect associations of risk factors with the latent depression outcome using a cross-sectional dataset of 342 patients with PD. RESULTS: A model with acceptable fit was generated that explained 41% of the variance in depression. In the final model, 3 PD-specific variables (increased disease duration, more severe motor symptoms, the use of levodopa) and 6 nonspecific variables (female sex, history of anxiety and/or depression, family history of depression, worse functioning on activities of daily living, and worse cognitive status) were maintained and significantly associated with depression. Nonspecific risk factors had a 3-times-higher influence in the model than PD-specific risk factors. CONCLUSION: In this cross-sectional study, we showed that nonspecific factors may be more prominent markers of depression than PD-specific factors. Accordingly, research on depression in PD should focus not only on factors associated with or specific for PD, but should also examine a wider scope of factors including general risk factors for depression, not specific for PD.