The effects of an 8-week computer-based brain training programme on cognitive functioning, QoL and self-efficacy after stroke.

Cognitive impairment after stroke has a direct impact on daily functioning and quality of life (QoL) of patients and is associated with higher mortality and healthcare costs. The aim of this study was to determine the effect of a computer-based brain training programme on cognitive functioning, QoL and self-efficacy compared to a control condition in stroke patients. Stroke patients with self-perceived cognitive impairment were randomly allocated to the intervention or control group. The intervention consisted of an 8-week brain training programme (Lumosity Inc.®). The control group received general information about the brain weekly. Assessments consisted of a set of neuropsychological tests and questionnaires. In addition, adherence with trained computer tasks was recorded. No effect of the training was found on cognitive functioning, QoL or self-efficacy when compared to the control condition, except for very limited effects on working memory and speed. This study found very limited effects on neuropsychological tests that were closely related to trained computer tasks, but no transfers to other tests or self-perceived cognitive failures, QoL or self-efficacy. These findings warrant the need for further research into the value of computer-based brain training to improve cognitive functioning in the chronic phase after stroke.

Adherence of stroke patients with an online brain training program: the role of health professionals' support.

Background Computer-based cognitive rehabilitation is used to improve cognitive functioning after stroke. However, knowledge on adherence rates of stroke patients is limited. Objective To describe stroke patients' adherence with a brain training program using two frequencies of health professionals' supervision. Methods This study is part of a randomized controlled trial comparing the effect of the brain training program (600 min playtime with weekly supervision) with a passive intervention in patients with self-perceived cognitive impairments after stroke. Patients randomized to the control condition were offered the brain training after the trial and received supervision twice (vs weekly in intervention group). Adherence was determined using data from the study website. Logistic regression analyses were used to examine the impact of supervision on adherence. Results 53 patients allocated to the intervention group (group S8; 64% male, mean age 59) and 52 patients who were offered the intervention after the trial (group S2; 59% male, mean age 59) started the brain training. The median playtime was 562 min (range 63-1264) in group S8 vs. 193 min (range 27-2162) in group S2 (p < 0.001, Mann Whitney U). Conclusions The overall adherence of stroke patients with a brain training was low and there are some implications that systematic, regular interaction with a supervisor can increase training adherence of stroke patients with a restitution-focused intervention performed at home.

Dose dependent dopaminergic modulation of reward-based learning in Parkinson's disease.

Learning to select optimal behavior in new and uncertain situations is a crucial aspect of living and requires the ability to quickly associate stimuli with actions that lead to rewarding outcomes. Mathematical models of reinforcement-based learning to select rewarding actions distinguish between (1) the formation of stimulus-action-reward associations, such that, at the instant a specific stimulus is presented, it activates a specific action, based on the expectation that that particular action will likely incur reward (or avoid punishment); and (2) the comparison of predicted and actual outcomes to determine whether the specific stimulus-action association yielded the intended outcome or needs revision. Animal electrophysiology and human fMRI studies converge on the notion that dissociable neural circuitries centered on the striatum are differentially involved in different components of this learning process. The modulatory role of dopamine (DA) in these respective circuits and component processes is of particular relevance to the study of reward-based learning in patients diagnosed with Parkinson's disease (PD). Here we show that the first component process, learning to predict which actions yield reward (supported by the anterior putamen and associated motor circuitry) is impaired when PD patients are taken off their DA medication, whereas DA medication has no systematic effects on the second processes, outcome evaluation (supported by caudate and ventral striatum and associated frontal circuitries). However, the effects of DA medication on these processes depend on dosage, with larger daily doses leading to a decrease in predictability of stimulus-action-reward relations and increase in reward-prediction errors.

Deep brain stimulation of the subthalamic nucleus improves reward-based decision-learning in Parkinson's disease.

Recently, the subthalamic nucleus (STN) has been shown to be critically involved in decision-making, action selection, and motor control. Here we investigate the effect of deep brain stimulation (DBS) of the STN on reward-based decision-learning in patients diagnosed with Parkinson's disease (PD). We determined computational measures of outcome evaluation and reward prediction from PD patients who performed a probabilistic reward-based decision-learning task. In previous work, these measures covaried with activation in the nucleus caudatus (outcome evaluation during the early phases of learning) and the putamen (reward prediction during later phases of learning). We observed that stimulation of the STN motor regions in PD patients served to improve reward-based decision-learning, probably through its effect on activity in frontostriatal motor loops (prominently involving the putamen and, hence, reward prediction). In a subset of relatively younger patients with relatively shorter disease duration, the effects of DBS appeared to spread to more cognitive regions of the STN, benefiting loops that connect the caudate to various prefrontal areas importantfor outcome evaluation. These results highlight positive effects of STN stimulation on cognitive functions that may benefit PD patients in daily-life association-learning situations.