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Background: People with Parkinson's disease (PD) who develop visuo‐perceptual deficits are at higher risk of dementia, but we lack tests that detect subtle visuo‐perceptual deficits and can be performed by untrained personnel. Hallucinations are associated with cognitive impairment and typically involve perception of complex objects. Changes in object perception may therefore be a sensitive marker of visuo‐perceptual deficits in PD. Objective: We developed an online platform to test visuo‐perceptual function. We hypothesised that (1) visuo‐perceptual deficits in PD could be detected using online tests, (2) object perception would be preferentially affected, and (3) these deficits would be caused by changes in perception rather than response bias. Methods: We assessed 91 people with PD and 275 controls. Performance was compared using classical frequentist statistics. We then fitted a hierarchical Bayesian signal detection theory model to a subset of tasks. Results: People with PD were worse than controls at object recognition, showing no deficits in other visuo‐perceptual tests. Specifically, they were worse at identifying skewed images (P < .0001); at detecting hidden objects (P = .0039); at identifying objects in peripheral vision (P < .0001); and at detecting biological motion (P = .0065). In contrast, people with PD were not worse at mental rotation or subjective size perception. Using signal detection modelling, we found this effect was driven by change in perceptual sensitivity rather than response bias. Conclusions: Online tests can detect visuo‐perceptual deficits in people with PD, with object recognition particularly affected. Ultimately, visuo‐perceptual tests may be developed to identify at‐risk patients for clinical trials to slow PD dementia. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Objective Examine the relationship between the National Institutes of Health Toolbox Emotion Battery (Emotion Toolbox) and traditional measures in Parkinson’s disease (PD). Method Persons with PD (n = 30) and cognitively healthy older adults (OA; n = 40) completed the Emotion Toolbox consisting of Well-Being, Negative Affect, and Social Satisfaction scores along with traditional measures of depression (Beck Depression Inventory-II [BDI-II]), anxiety (State–Trait Anxiety Inventory [STAI]), and apathy (Apathy Scale [AS]); total raw scores). Results Separate bootstrapped analyses of covariance indicated that the PD group scored higher on BDI-II and STAI-State compared to OA (ps &lt; .01); groups did not differ on Emotion Toolbox. In the PD group, bootstrapped partial correlations indicated that Negative Affect was positively related to BDI-II and STAI (ps ≤ .001). Social Satisfaction was negatively related to BDI-II and STAI-Trait (.05 &lt; ps &lt; .004). Psychological Well-Being was negatively related to BDI-II, AS, and STAI (p &lt; .004). No relationships emerged in OA. In the PD group, separate binary logistic regressions showed that traditional measures (BDI-II, AS, and STAI-Trait) correctly classified 79.6% those with formal psychiatric diagnoses (presence vs. absence; p &lt; .011), whereas Emotion Toolbox measures correctly classified 73.3% (p &lt; .019). Conclusions The Emotion Toolbox showed moderate-strong correlations with traditional measures in persons with PD. Even so, it did not capture the group differences between PD and OA and had a somewhat lower classification accuracy rate for persons with PD who had a formal psychiatric diagnosis than traditional measures. Together, findings question the utility of the Emotion Toolbox as a stand-alone emotion screener in PD.

Background Current conflict exists regarding the potential beneficial effects of dopamine medications on facial expressivity in Parkinson's disease. Via digital video analysis software, we previously found reduced facial movement (entropy) and slower time to reach peak entropy in individuals with Parkinson's disease compared to controls. Objectives We aimed to determine whether levodopa medications improved parameters of dynamic facial expressions (amplitude, speed). Methods A total of 34 individuals with idiopathic Parkinson's disease were videotaped making voluntary facial expressions (happy, fear, anger, disgust) when “on” and “off” levodopa. Participants were 52 to 80 years old, early to mid‐stage disease, non‐demented, and included more men (65%). Expressions were digitized and analyzed using software that extracted three variables: two indices of movement change (total entropy, percent entropy change) and time to reach peak expression. Results Indices of facial movement (total entropy, peak entropy) and timing were significantly improved when patients were “on” vs “off” medication (all F's ≥ 3.00, P < 0.05). For total movement and time to reach peak entropy, levodopa‐related improvements were emotion nonspecific. Levodopa‐related improvement for peak entropy was driven primarily by happy expressions. There was no relationship between quantitative indices and clinical measures of mood (depression, anxiety) and motor disease severity. Conclusion The effects of levodopa on Parkinson's disease voluntary facial movement and on timing were robust and consistent with those of levodopa on other intentional movements in Parkinson's disease. This improvement possibly occurred because of levodopa enhanced activation of face representation areas in fronto‐cortical regions or because of less movement‐based suppression.