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People with Parkinson’s disease (PD) and their care partners frequently report cognitive decline as one of their greatest concerns. Mild cognitive impairment affects approximately 20–50% of people with PD, and longitudinal studies reveal dementia in up to 80% of PD. Through the Parkinson’s Disease Foundation Community Choice Research Award Program, the PD community identified maintaining cognitive function as one of their major unmet needs. In response, a working group of experts across multiple disciplines was organized to evaluate the unmet needs, current challenges, and future opportunities related to cognitive impairment in PD. Specific conference goals included defining the current state in the field and gaps regarding cognitive issues in PD from patient, care partner, and healthcare professional viewpoints; discussing non-pharmacological interventions to help maintain cognitive function; forming recommendations for what people with PD can do at all disease stages to maintain cognitive health; and proposing ideas for how healthcare professionals can approach cognitive changes in PD. This paper summarizes the discussions of the conference, first by addressing what is currently known about cognitive dysfunction in PD and discussing several non-pharmacological interventions that are often suggested to people with PD. Second, based on the conference discussions, we provide considerations for people with PD for maintaining cognitive health and for healthcare professionals and care partners when working with people with PD experiencing cognitive impairment. Furthermore, we highlight key issues and knowledge gaps that need to be addressed in order to advance research in cognition in PD and improve clinical care.

Cognitive dysfunction is common in Parkinson’s disease (PD). We developed and evaluated an EEG-based biomarker to index cognitive functions in PD from a few minutes of resting-state EEG. We hypothesized that synchronous changes in EEG across the power spectrum can measure cognition. We optimized a data-driven algorithm to efficiently capture these changes and index cognitive function in 100 PD and 49 control participants. We compared our EEG-based cognitive index with the Montreal cognitive assessment (MoCA) and cognitive tests across different domains from National Institutes of Health (NIH) Toolbox using cross-validations, regression models, and randomization tests. Finally, we externally validated our approach on 32 PD participants. We observed cognition-related changes in EEG over multiple spectral rhythms. Utilizing only 8 best-performing electrodes, our proposed index strongly correlated with cognition (MoCA: rho = 0.68, p value < 0.001; NIH-Toolbox cognitive tests: rho ≥ 0.56, p value < 0.001) outperforming traditional spectral markers (rho = −0.30–0.37). The index showed a strong fit in regression models ( R 2  = 0.46) with MoCA, yielded 80% accuracy in detecting cognitive impairment, and was effective in both PD and control participants. Notably, our approach was equally effective (rho = 0.68, p value < 0.001; MoCA) in out-of-sample testing. In summary, we introduced a computationally efficient data-driven approach for cross-domain cognition indexing using fewer than 10 EEG electrodes, potentially compatible with dynamic therapies like closed-loop neurostimulation. These results will inform next-generation neurophysiological biomarkers for monitoring cognition in PD and other neurological diseases.

People with Parkinson’s disease (PwPD) often experience gait and balance problems that substantially impact their quality of life. Pharmacological, surgical, and rehabilitative treatments have limited effectiveness and many PwPD continue to experience gait and balance impairment. Transcranial direct current stimulation (tDCS) may represent a viable therapeutic adjunct. The effects of lower intensity tDCS (2 mA) over frontal brain areas, in unilateral and bilateral montages, has previously been explored; however, the effects of lower and higher intensity cerebellar tDCS (2 mA and 4 mA, respectively) on gait and balance has not been investigated. Seven PwPD underwent five cerebellar tDCS conditions (sham, unilateral 2 mA, bilateral 2 mA, unilateral 4 mA, and bilateral 4 mA) for 20 min. After a 10 min rest, gait and balance were tested. The results indicated that the bilateral 4 mA cerebellar tDCS condition had a significantly higher Berg Balance Scale score compared to sham. This study provides preliminary evidence that a single session of tDCS over the cerebellum, using a bilateral configuration at a higher intensity (4 mA), significantly improved balance performance. This intensity and cerebellar configuration warrants future investigation in larger samples and over repeated sessions.

Cognitive dysfunction is common in Parkinson's disease (PD) and predicts poor clinical outcomes. It is associated primarily with pathologic involvement of basal forebrain cholinergic and prefrontal dopaminergic systems. Impairments in executive functions, attention, and visuospatial abilities are its hallmark features with eventual involvement of memory and other domains. Subtle symptoms in the premotor and early phases of PD progress to mild cognitive impairment (MCI) which may be present at the time of diagnosis. Eventually, a large majority of PD patients develop dementia with advancing age and longer disease duration, which is usually accompanied by immobility, hallucinations/psychosis, and dysautonomia. Dopaminergic medications and deep brain stimulation help motor dysfunction, but may have potential cognitive side effects. Central acetylcholinesterase inhibitors, and possibly memantine, provide modest and temporary symptomatic relief for dementia, although there is no evidence-based treatment for MCI. There is no proven disease-modifying treatment for cognitive impairment in PD. The symptomatic and disease-modifying role of physical exercise, cognitive training, and neuromodulation on cognitive impairment in PD is under investigation. Multidisciplinary approaches to cognitive impairment with effective treatment of comorbidities, proper rehabilitation, and maintenance of good support systems in addition to pharmaceutical treatment may improve the quality of life of the patients and caregivers.

Hand gesture, a ubiquitous feature of human interaction, facilitates communication. Gesture also facilitates new learning, benefiting speakers and listeners alike. Thus, gestures must impact cognition beyond simply supporting the expression of already-formed ideas. However, the cognitive and neural mechanisms supporting the effects of gesture on learning and memory are largely unknown. We hypothesized that gesture's ability to drive new learning is supported by procedural memory and that procedural memory deficits will disrupt gesture production and comprehension. We tested this proposal in patients with intact declarative memory, but impaired procedural memory as a consequence of Parkinson's disease (PD), and healthy comparison participants with intact declarative and procedural memory. In separate experiments, we manipulated the gestures participants saw and produced in a Tower of Hanoi (TOH) paradigm. In the first experiment, participants solved the task either on a physical board, requiring high arching movements to manipulate the discs from peg to peg, or on a computer, requiring only flat, sideways movements of the mouse. When explaining the task, healthy participants with intact procedural memory displayed evidence of their previous experience in their gestures, producing higher, more arching hand gestures after solving on a physical board, and smaller, flatter gestures after solving on a computer. In the second experiment, healthy participants who saw high arching hand gestures in an explanation prior to solving the task subsequently moved the mouse with significantly higher curvature than those who saw smaller, flatter gestures prior to solving the task. These patterns were absent in both gesture production and comprehension experiments in patients with procedural memory impairment. These findings suggest that the procedural memory system supports the ability of gesture to drive new learning.

The proportion of elderly people in the general population is rising, resulting in greater numbers of drivers with neurodegenerative disorders such as Alzheimer’s disease and Parkinson’s disease. These neurodegenerative disorders impair cognition, visual perception, and motor function, leading to reduced driver fitness and greater crash risk. Yet neither medical diagnosis nor age alone is reliable enough to predict driver safety or crashes or to revoke the driving privileges of these individuals. Driving research utilizes tools such as questionnaires about driving habits and history, driving simulators, standardized road tests utilizing instrumented vehicles, and state driving records. Research challenges include outlining the evolution of driving safety, understanding the mechanisms of driving impairment, and developing a reliable and efficient standardized test battery for prediction of driver safety in neurodegenerative disorders. This information will enable healthcare providers to advise their patients with neurodegenerative disorders with more certainty, affect policy, and help develop rehabilitative measures for driving.

Parkinson’s disease (PD) is associated with procedural learning deficits. Nonetheless, studies have demonstrated that reward-related learning is comparable between patients with PD and controls (Bódi et al., Brain , 132 (9), 2385–2395, 2009 ; Frank, Seeberger, & O’Reilly, Science , 306 (5703), 1940–1943, 2004 ; Palminteri et al., Proceedings of the National Academy of Sciences of the United States of America , 106 (45), 19179–19184, 2009 ). However, because these studies do not separate the effect of reward from the effect of practice, it is difficult to determine whether the effect of reward on learning is distinct from the effect of corrective feedback on learning. Thus, it is unknown whether these group differences in learning are due to reward processing or learning in general. Here, we compared the performance of medicated PD patients to demographically matched healthy controls (HCs) on a task where the effect of reward can be examined separately from the effect of practice. We found that patients with PD showed significantly less reward-related learning improvements compared to HCs. In addition, stronger learning of rewarded associations over unrewarded associations was significantly correlated with smaller skin-conductance responses for HCs but not PD patients. These results demonstrate that when separating the effect of reward from the effect of corrective feedback, PD patients do not benefit from reward.

Introduction: This study evaluates driving ability in those with Charcot-Marie-Tooth Disease Type 1A, a hereditary peripheral neuropathy. Methods: Individuals with Charcot-Marie-Tooth Disease Type 1A (n = 18, age = 42 ± 7) and controls (n = 19; age = 35 ± 10) were evaluated in a driving simulator. The Charcot-Marie-Tooth Neuropathy Score version 2 was obtained for individuals. Rank Sum test and Spearman rank correlations were used for statistical analysis. Results: A 74% higher rate of lane departures and an 89% higher rate of lane deviations were seen in those with Charcot-Marie-Tooth Disease Type 1A than for controls (p = 0.005 and p < 0.001, respectively). Lane control variability was 10% higher for the individual group and correlated with the neuropathy score (rS = 0.518, p = 0.040), specifically sensory loss (rS = 0.710, p = 0.002) and pinprick sensation loss in the leg (rS = 0.490, p = 0.054). Discussion: Driving simulator assessment demonstrated more lane control errors in those with Charcot-Marie-Tooth Disease Type 1A, which correlated with lower extremity sensory loss. There was no significant difference in reported motor vehicle accidents.

Demographically adjusted norms generally enhance accuracy of inferences based on neuropsychological assessment. However, we hypothesized that demographic corrections diminish predictive accuracy for real-world activities with absolute cognitive demands. Driving ability was assessed with a 45-minute drive along a standardized on-road route in participants aged 65+ (24 healthy elderly, 26 probable Alzheimer’s disease, 33 Parkinson’s disease). Neuropsychological measures included: Trail-Making A and B, Complex Figure, Benton Visual Retention, and Block Design tests. A multiple regression model with raw neuropsychological scores was significantly predictive of driving errors (R2 = .199, p = .005); a model with demographically adjusted scores was not (R2 = .113, p = .107). Raw scores were more highly correlated with driving errors than were adjusted scores for each neuropsychological measure, and among healthy elderly and Parkinson’s patients. When predicting real-world activities that depend on absolute levels of cognitive abilities regardless of demographic considerations, predictive accuracy is diminished by demographic corrections. (JINS, 2010, 16, 679–686.)

Objective: To assess visual search and recognition of roadside targets and safety errors during a landmark and traffic sign identification task in drivers with Alzheimer’s disease. Methods: 33 drivers with probable Alzheimer’s disease of mild severity and 137 neurologically normal older adults underwent a battery of visual and cognitive tests and were asked to report detection of specific landmarks and traffic signs along a segment of an experimental drive. Results: The drivers with mild Alzheimer’s disease identified significantly fewer landmarks and traffic signs and made more at-fault safety errors during the task than control subjects. Roadside target identification performance and safety errors were predicted by scores on standardised tests of visual and cognitive function. Conclusions: Drivers with Alzheimer’s disease are impaired in a task of visual search and recognition of roadside targets; the demands of these targets on visual perception, attention, executive functions, and memory probably increase the cognitive load, worsening driving safety.