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Background: Working memory (WM) training (WMT) is a popular intervention approach against cognitive decline in patients with Parkinson’s disease (PD). However, heterogeneity in WM responsiveness suggests that WMT may not be equally efficient for all patients. Objective: The present study aims to evaluate a multivariate model to predict post-intervention verbal WM in patients with PD using a supervised machine learning approach. We test the predictive potential of novel learning parameters derived from the WMT and compare their predictiveness to other more commonly used domains including demographic, clinical, and cognitive data. Methods: 37 patients with PD (age: 64.09±8.56, 48.6% female, 94.7% Hoehn & Yahr stage 2) participated in a 5-week WMT. Four random forest regression models including 1) cognitive variables only, 2) learning parameters only, 3) both cognitive and learning variables, and 4) the entire set of variables (with additional demographic and clinical data, ‘all’ model), were built to predict immediate and 3-month-follow-up WM. Result: The ‘all’ model predicted verbal WM with the lowest root mean square error (RMSE) compared to the other models, at both immediate (RMSE = 0.184; 95% -CI=[0.184;0.185]) and 3-month follow-up (RMSE = 0.216; 95% -CI=[0.215;0.217]). Cognitive baseline parameters were among the most important predictors in the ‘all’ model. The model combining cognitive and learning parameters significantly outperformed the model solely based on cognitive variables. Conclusion: Commonly assessed demographic, clinical, and cognitive variables provide robust prediction of response to WMT. Nonetheless, inclusion of training-inherent learning parameters further boosts precision of prediction models which in turn may augment training benefits following cognitive interventions in patients with PD.

Background. Patients with Parkinson’s disease (PD) are highly vulnerable to develop cognitive dysfunctions, and the mitigating potential of early cognitive training (CT) is increasingly recognized. Predictors of CT responsiveness, which could help to tailor interventions individually, have rarely been studied in PD. This study aimed to examine individual characteristics of patients with PD associated with responsiveness to targeted working memory training (WMT). Methods. Data of 75 patients with PD (age: 63.99 ± 9.74 years, 93% Hoehn & Yahr stage 2) without cognitive dysfunctions from a randomized controlled trial were analyzed using structural equation modeling. Latent change score models with and without covariates were estimated and compared between the WMT group ( n = 37), who participated in a 5-week adaptive WMT, and a waiting list control group ( n = 38). Results. Latent change score models yielded adequate model fit (χ2-test p > .05, SRMR ≤ .08, CFI ≥ .95). For the near-transfer working memory composite, lower baseline performance, younger age, higher education, and higher fluid intelligence were found to significantly predict higher latent change scores in the WMT group, but not in the control group. For the far-transfer executive function composite, higher self-efficacy expectancy tended to significantly predict larger latent change scores. Conclusions. The identified associations between individual characteristics and WMT responsiveness indicate that there has to be room for improvement (e.g., lower baseline performance) and also sufficient “hardware” (e.g., younger age, higher intelligence) to benefit in training-related cognitive plasticity. Our findings are discussed within the compensation versus magnification account. They need to be replicated by methodological high-quality research applying advanced statistical methods with larger samples.

Objective To determine the feasibility and evaluate effects of a computerized working memory (WM) training (WMT) in patients with Parkinson's Disease (PD) on cognitive and clinical outcomes. Methods 76 patients with PD without cognitive impairment were randomized to either the WMT group (n = 37), who participated in a 5-week adaptive WMT, or a passive waiting-list control group (CG, n = 39). Patients underwent clinical and neuropsychological examination at baseline, after training, and at 3-months follow-up, with verbal WM and non-verbal WM as primary outcomes. Outcome assessors were blinded for group allocation. Results All WMT participants completed the training successfully and reported high levels of motivation for and satisfaction with the training. Repeated-measures, linear mixed-effects models revealed positive training effects for the WMT group compared to the CG in verbal working memory with a small relative effect size 0.39 [95%CI 0.05; 0.76] for the 3-months follow-up only. No other reliable training effects in cognitive and clinical variables were found for either point of time. Conclusions In this randomized controlled trial, WMT was feasible and yielded some evidence for 3-months follow-up training gains in patients with PD. WMT might be an effective intervention to prevent cognitive decline in this patient group, however, more longitudinal studies with longer follow-up periods and more sensitive assessment tools will have to proof this concept. Trial registration German Clinical Trials Register (DRKS00009379).

ObjectivesParkinson’s disease (PD) is the second most common neurodegenerative disorder and is further associated with progressive cognitive decline. In respect to motor phenotype, there is some evidence that akinetic-rigid PD is associated with a faster rate of cognitive decline in general and a greater risk of developing dementia.The objective of this study was to examine cognitive profiles among patients with PD by motor phenotypes and its relation to cognitive function.MethodsDemographic, clinical and neuropsychological cross-sectional baseline data of the DEMPARK/LANDSCAPE study, a multicentre longitudinal cohort study of 538 patients with PD were analysed, stratified by motor phenotype and cognitive syndrome. Analyses were performed for all patients and for each diagnostic group separately, controlling for age, gender, education and disease duration.ResultsCompared with the tremor-dominant phenotype, akinetic-rigid patients performed worse in executive functions such as working memory (Wechsler Memory Scale-Revised backward; p=0.012), formal-lexical word fluency (p=0.043), card sorting (p=0.006), attention (Trail Making Test version A; p=0.024) and visuospatial abilities (Leistungsprüfungssystem test 9; p=0.006). Akinetic-rigid neuropsychological test scores for the executive and attentive domain correlated negatively with non-tremor motor scores. Covariate-adjusted binary logistic regression analyses showed significant odds for PD-mild cognitive impairment for not-determined as compared with tremor-dominant (OR=3.198) and akinetic-rigid PD (OR=2.059). The odds for PD-dementia were significant for akinetic-rigid as compared with tremor-dominant phenotype (OR=8.314).ConclusionThe three motor phenotypes of PD differ in cognitive performance, showing that cognitive deficits seem to be less severe in tremor-dominant PD. While these data are cross-sectional, longitudinal data are needed to shed more light on these differential findings.

Objective Inconsistent results exist regarding the cognitive profile in patients with Parkinson9s disease with mild cognitive impairment (PD-MCI). We aimed at providing data on this topic from a large cohort of patients with PD-MCI. Methods Sociodemographic, clinical and neuropsychological baseline data from patients with PD-MCI recruited in the multicentre, prospective, observational DEMPARK/LANDSCAPE study were analysed. Results 269 patients with PD-MCI (age 67.8±7.4, Unified Parkinson9s Disease Rating Scale (UPDRS-III) scores 23.2±11.6) were included. PD-MCI subtypes were 39.4% non-amnestic single domain, 30.5% amnestic multiple domain, 23.4% non-amnestic multiple domain and 6.7% amnestic single domain. Executive functions were most frequently impaired. The most sensitive tests to detect cognitive dysfunctions were the Modified Card Sorting Test, digit span backwards and word list learning direct recall. Multiple stepwise regression analyses showed that global cognition, gender and age, but not education or disease-related parameters predicted PD-MCI subtypes. Conclusions This study with the so far largest number of prospectively recruited patients with PD-MCI indicates that non-amnestic PD-MCI is more frequent than amnestic PD-MCI; executive dysfunctions are the most typical cognitive symptom in PD-MCI; and age, gender and global cognition predict the PD-MCI subtype. Longitudinal data are needed to test the hypothesis that patients with PD-MCI with specific cognitive profiles have different risks to develop dementia.