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Brain atrophy in Parkinson's disease occurs to varying degrees in different brain regions, even at the early stage of the disease. While cortical morphological features are often considered independently in structural brain imaging studies, research on the co-progression of different cortical morphological measurements could provide new insights regarding the progression of PD. This study's aim was to examine the interplay between cortical curvature and thickness as a function of PD diagnosis, motor symptoms, and cognitive performance.A total of 359 de novo PD patients and 159 healthy controls (HC) from the Parkinson's Progression Markers Initiative (PPMI) database were included in this study. Additionally, an independent cohort from four databases (182 PD, 132 HC) with longer disease durations was included to assess the effects of PD diagnosis in more advanced cases. Pearson correlation was used to determine subject-specific associations between cortical curvature and thickness estimated from T1-weighted MRI images. General linear modeling (GLM) was then used to assess the effect of PD diagnosis, motor symptoms, and cognitive performance on the curvature-thickness association. Next, longitudinal changes in the curvature-thickness correlation as well as the predictive effect of the cortical curvature-thickness association on changes in motor symptoms and cognitive performance across four years were investigated. Finally, Akaike information criterion (AIC) was used to build a GLM to model PD motor symptom severity cross-sectionally.A significant interaction effect between PD motor symptoms and age on the curvature-thickness correlation was found (βThe association between cortical curvature and thickness is related to PD motor symptoms and age. This research shows the potential of modeling the curvature-thickness interplay in PD.

Parkinson's disease (PD) is characterized by overlapping motor, neuropsychiatric, and cognitive symptoms. Worse performance in one domain is associated with worse performance in the other domains. Commonality analysis (CA) is a method of variance partitioning in multiple regression, used to separate the specific and common influence of collinear predictors. We apply, for the first time, CA to the functional connectome to investigate the unique and common neural connectivity underlying the interface of the symptom domains in 74 non‐demented PD subjects. Edges were modeled as a function of global motor, cognitive, and neuropsychiatric scores. CA was performed, yielding measures of the unique and common contribution of the symptom domains. Bootstrap confidence intervals were used to determine the precision of the estimates and to directly compare each commonality coefficient. The overall model identified a network with the caudate nucleus as a hub. Neuropsychiatric impairment accounted for connectivity in the caudate‐dorsal anterior cingulate and caudate‐right dorsolateral prefrontal‐right inferior parietal circuits, while caudate‐medial prefrontal connectivity reflected a unique effect of both neuropsychiatric and cognitive impairment. Caudate‐precuneus connectivity was explained by both unique and shared influence of neuropsychiatric and cognitive symptoms. Lastly, posterior cortical connectivity reflected an interplay of the unique and common effects of each symptom domain. We show that CA can determine the amount of variance in the connectome that is unique and shared amongst motor, neuropsychiatric, and cognitive symptoms in PD, thereby improving our ability to interpret the data while gaining novel insight into networks at the interface of these symptom domains.

Background The dual syndrome hypothesis of cognitive impairment in PD suggests that two cognitive profiles exist with distinct pathological mechanisms and a differential risk for further cognitive decline. How these profiles relate to network dysfunction has never been explicitly characterized. Objective First, to assess intranetwork functional connectivity while considering global connectivity, and second, to relate network connectivity with measures of the dysexecutive and posterior cortical profiles. Methods Eighty-two subjects with idiopathic PD and 37 age-matched controls underwent resting-state functional MRI and comprehensive neuropsychological assessment. Intranetwork and global connectivity was compared between groups. Measures of the dysexecutive and posterior cortical profiles were related to network connectivity while considering demographic and disease-related covariates. Results PD subjects show decreased connectivity within several cortical networks. However, only the sensorimotor network displayed a loss of connectivity independent of the observed decreased global connectivity. The dysexecutive factor was independently related to increased motor severity, less education, and decreased connectivity in the sensorimotor network. The posterior cortical factor was related to increased age, less education, decreased connectivity in the central executive network, as well as increased connectivity in the temporal network. Conclusions Our results provide evidence supporting a network-specific process of degeneration in the sensorimotor network which contributes to the dysexecutive cognitive profile. In contrast, connectivity of the temporal and central executive network is related to the posterior cortical profile, representing a distinct network signature of this syndrome. © 2019 International Parkinson and Movement Disorder Society.

Cognitive impairments are prevalent in Parkinson’s disease (PD), but the underlying mechanisms of their development are unknown. In this study, we aimed to predict global cognition (GC) in PD with machine learning (ML) using structural neuroimaging, genetics and clinical and demographic characteristics. As a post-hoc analysis, we aimed to explore the connection between novel selected features and GC more precisely and to investigate whether this relationship is specific to GC or is driven by specific cognitive domains. 101 idiopathic PD patients had a cognitive assessment, structural MRI and blood draw. ML was performed on 102 input features including demographics, cortical thickness and subcortical measures, and several genetic variants (APOE, MAPT, SNCA, etc.). Using the combination of RRELIEFF and Support Vector Regression, 11 features were found to be predictive of GC including sex, rs894280, Edinburgh Handedness Inventory, UPDRS-III, education, five cortical thickness measures (R-parahippocampal, L-entorhinal, R-rostral anterior cingulate, L-middle temporal, and R-transverse temporal), and R-caudate volume. The rs894280 of SNCA gene was selected as the most novel finding of ML. Post-hoc analysis revealed a robust association between rs894280 and GC, attention, and visuospatial abilities. This variant indicates a potential role for the SNCA gene in cognitive impairments of idiopathic PD.

Highlights • PD with mild behavioral impairment revealed deficits in cognitive flexibility. • Brain activities during a set-shifting task linked with MBI in PD was evaluated. • PD-MBI revealed reduced activity in the prefrontal and posterior parietal cortices. • The prefrontal activity was associated with cognitive impairment in PD-MBI. • High MBI-C score was associated with reduced deactivation in the hippocampus., Mild behavioral impairment (MBI) is a neurobehavioral syndrome characterized by later life emergence of sustained neuropsychiatric symptoms, as an at-risk state for incident cognitive decline and dementia. Prior studies have reported that neuropsychiatric symptoms are associated with cognitive abilities in Parkinson’s disease (PD) patients, and we have recently found a strong correlation between MBI and cognitive performance. However, the underlying neural activity patterns of cognitive performance linked to MBI in PD are unknown. Fifty-nine non-demented PD patients and 26 healthy controls were scanned using fMRI during performance of a modified version of the Wisconsin card sorting task. MBI was evaluated using the MBI-checklist, and PD patients were divided into two groups, PD-MBI and PD-noMBI. Compared to the PD-noMBI group and healthy controls, the PD-MBI group revealed less activation in the prefrontal and posterior parietal cortices, and reduced deactivation in the medial temporal region. These results suggest that in PD, MBI reflects deficits in the frontoparietal control network and the hippocampal memory system.

Patients with Parkinson’s disease (PD) have difficulties processing action words, which could be related to early cognitive decline. The action fluency test can be used to quickly and easily assess the processing of action words in PD. The goal of this study was to characterize how the action fluency test relates to personal characteristics, disease factors, cognition, and neural activity in PD. Forty-eight participants with PD (34 male, 14 female) and 35 control participants (16 male, 19 female) completed functional neuroimaging using a set-shifting task and a neuropsychological assessment including the action fluency test. PD participants with a score one standard deviation below the norm or lower on the action fluency test were identified. All PD participants with poor performance (PD-P, n = 15) were male. They were compared to male PD participants with scores within the normal range (PD-N, n = 19) and male healthy controls (HC, n = 16). PD-P were older, had lower global cognition scores, lower executive functions scores, and decreased activity in fronto-temporal regions compared with PD-N. There was no difference between the two PD groups in terms of the duration of the disease, dose of dopaminergic medication, and severity of motor symptoms. PD-N were younger than HC, but there was no other significant difference between these groups. The action fluency test identified a subgroup of PD patients with distinct sex, age, global cognition, executive functions, and brain activity characteristics. Implications for the evaluation of cognition are discussed.

The objective was to determine whether a history of traumatic brain injury (TBI) was associated with Parkinson's Disease (PD) and specific cognitive, motor, and neuropsychiatric symptoms. A cross-sectional cohort study of 120 participants aged 60-85 years old (48 females) were recruited (69 PD and 51 healthy controls). Assessments included demographic information, neuropsychological tests, a motor evaluation, neuropsychiatric questionnaires, and the Brain Injury Screening Questionnaire. A history of TBI or number of TBIs was not significantly related to an increased risk of developing PD or poorer motor scores on the United Parkinson Disease Rating Scale part 3. There was a significant negative correlation between number of TBI's and mean

ObjectiveTo evaluate the associations of mild behavioral impairment (MBI) with cognitive deficits and patterns of gray matter changes in Parkinson disease (PD).MethodsSixty patients with PD without dementia and 29 healthy controls underwent a cognitive neuropsychological evaluation and structural MRI scan. MBI was evaluated with the MBI Checklist (MBI-C), a rating scale designed to elicit emergent neuropsychiatric symptoms in accordance with MBI criteria. We divided the patients with PD into 2 groups: 1 group with high MBI-C scores (PD-MBI) and the other with low MBI-C scores (PD-noMBI).ResultsAmong 60 patients with PD, 20 were categorized as having PD-MBI (33.33%). In healthy controls, no participants met the MBI cut-point threshold. The PD-MBI group had significantly lower Montreal Cognitive Assessment and z scores in all 5 domains and the global score compared to healthy controls and those with PD-noMBI. In addition, all cognitive domains except language and global cognition negatively correlated with the MBI-C total score in all patients with PD. For cortical structures, the PD-MBI group revealed middle temporal cortex thinning and decreased volume compared with the PD-noMBI group, and decreased volume in this area negatively correlated with the MBI-C total score.ConclusionsThe impaired cognitive function over all domains and atrophy in the temporal area in the PD-MBI group are in line with posterior cortical circuit deficits in PD, which have been associated with a faster rate of progression to dementia. These initial results suggest that MBI might be an early and important marker for incident cognitive decline and dementia in patients with PD.

Highlights • Mild behavioral impairment in PD is linked to altered corticostriatal connectivity. • PD-MBI have less connectivity between the striatum and the DMN. • PD-MBI have increased atrophy of the SAN. • Caudate head and dorsal putamen connectivity is related to MBI-C scores in PD. • Caudate head-precuneus connectivity is linked to both MBI and MoCA scores., Background Mild behavioral impairment (MBI) is a syndrome characterized by later life onset, sustained neuropsychiatric symptoms as a marker of dementia risk. In Parkinson's disease (PD), MBI has been associated with worse cognitive abilities and increased cortical atrophy. However, the circuit level correlates of MBI have not been investigated in this population. Our objective was to investigate the relationship between MBI and corticostriatal connectivity in PD patients. This emphasis on corticostriatal connectivity was due to the significant role of these circuits in neuropsychiatric and cognitive symptoms across disease conditions. Methods Seventy-four non-demented patients with PD were administered the MBI-checklist, and classified as having high MBI (PD-MBI; n = 21) or low MBI scores (PD-noMBI; n = 53). Corticostriatal connectivity was assessed with both an atlas and seed-based analysis. The atlas analysis consisted of calculating the average connectivity between the striatal network and the default mode (DMN), central executive (CEN), and saliency networks (SAN). Structural measurements of cortical thickness and volume were also assessed. PD-MBI and PD-noMBI patients were compared, along with a group of age matched healthy control subjects (HC; n = 28). Subsequently, a seed analysis assessed the relationship of MBI scores with the connectivity of twelve seeds within the striatum while controlling for cognitive ability. A complementary analysis assessed the relationship between striatal connectivity and cognition, while controlling for MBI-C. Results PD-MBI demonstrated decreased connectivity between the striatum and both the DMN and SAN compared to PD-noMBI and HC. The decreased connectivity between the striatum and the SAN was explained partly by increased atrophy within the SAN in PD-MBI. The seed analysis revealed a relationship between higher MBI scores and lower connectivity of the left caudate head to the dorsal anterior cingulate cortex and left middle frontal gyrus. Higher MBI-C scores were also related to decreased connectivity of the right caudate head with the anterior cingulate cortex, precuneus, and left supramarginal gyrus, as well as increased connectivity to the left hippocampus and right cerebellar hemisphere. Caudate-precuneus connectivity was independently associated with both global behavioural and cognitive scores. Conclusion These results suggest PD-MBI is associated with altered corticostriatal connectivity, particularly between the head of the caudate and cortical regions associated with the DMN and SAN. In particular, caudate-precuneus connectivity is associated with both global behavioral and cognitive symptoms in PD.

Highlights • Screening tests can diagnose PD-MCI but do not give detailed cognitive profiles. • Criteria based on a complete neuropsychological battery identify more PD patients with MCI. • The overall cognitive profile is similar in PD-MCI and MCI. • Neuropsychological batteries and definition of impairment cut-offs should be refined.

Are self-report measures of prospective memory (ProM) reliable and valid? To examine this question, 240 undergraduate student volunteers completed several widely used self-report measures of ProM including the Prospective Memory Questionnaire (PMQ), the Prospective and Retrospective Memory Questionnaire (PRMQ), the Comprehensive Assessment of Prospective Memory (CAPM) questionnaire, self-reports of retrospective memory (RetM), objective measures of ProM and RetM, and measures of involvement in activities and events, memory strategies and aids use, personality and verbal intelligence. The results showed that both convergent and divergent validity of ProM self-reports are poor, even though we assessed ProM using a newly developed, reliable continuous measure. Further analyses showed that a substantial proportion of variability in ProM self-report scores was due to verbal intelligence, personality (conscientiousness, neuroticism), activities and event involvement (busyness), and use of memory strategies and aids. ProM self-reports have adequate reliability, but poor validity and should not be interpreted as reflecting ProM ability.