Search

Alzheimer's disease is characterized by a decline in episodic memory and executive functioning, hampering learning ability. Insight into outcome‐based learning capacity may be relevant for optimizing the learning potential of these patients. To date, mixed results have been found in studies in which cognitively impaired participants have to learn based on positive and negative outcomes. In this study, we investigated the role of negative and positive feedback on memory performance and participants' ability to adjust their behaviour accordingly in a sample of 23 early‐stage AD patients and 23 matched healthy controls. We administered a novel computerized object‐location memory task, in which participants were instructed to learn and memorize the locations of different everyday objects following errorless learning (EL) and trial‐and‐error learning (TEL). A separate probabilistic TEL task was employed in which participants had to learn how to adjust their behaviour based on positive and negative feedback. EL had a beneficial general effect on memory performance for object locations. However, this effect was not larger in early‐stage AD patients compared to controls and error frequency during acquisition of object locations was unrelated to later recall performance. No group differences were found on the probabilistic learning task with respect to learning performance over time and based on positive and negative feedback. Although the error monitoring system seems intact in patients with early‐stage AD, errors during learning are likely acting as a source of interference causing difficulty in storage or retrieval of object locations. [ABSTRACT FROM AUTHOR]

BACKGROUND: Sleep disturbances are common after acquired brain injury (ABI) and have a negative impact on functioning. OBJECTIVE: This study examines whether a short add-on therapy for sleep disturbances in individuals with ABI is effective in addition to rehabilitation treatment as usual. METHODS: In the randomized-controlled study, 54 adults with ABI and self-reported sleep disturbances receiving outpatient rehabilitation services were randomized in two groups: one receiving a sleep intervention (based on cognitive behavioural therapy for insomnia (CBT-I)) in addition to their rehabilitation treatment (CBT-I + TAU group) and one receiving treatment as usual (TAU). The primary outcome was sleep quality, measured with the Pittsburgh Sleep Quality Index (PSQI). Secondary outcomes included measures of anxiety, depression, fatigue and dysfunctional beliefs and attitudes about sleep. RESULTS: The short add-on sleep therapy resulted in improvements in sleep quality in the CBT-I + TAU group as compared to the TAU group (ES = 0.924). Furthermore, the CBT-I + TAU group reported less dysfunctional beliefs and attitudes about sleep and were better able to cope with fatigue compared to the TAU group. CONCLUSIONS: The application of this short add-on sleep intervention could be implemented in neuropsychological rehabilitation settings. [ABSTRACT FROM AUTHOR]

Studies investigating the efficacy of errorless learning (EL), a rehabilitation method in which the occurrence of errors during learning are eliminated, have predominantly involved patients with memory impairment. However, the most recent perspective on the underlying mechanism of EL explicitly takes executive processes into account. The aim of this study was to investigate whether EL of object locations is beneficial for memory performance compared to trial-and-error learning (TEL) in patients with acquired brain injury (ABI) experiencing executive deficits (N = 15) and matched healthy controls (N = 15). Participants completed an EL and TEL condition of a computerized spatial learning task, in which the location of everyday objects had to be memorized. The number of errors made during learning was predetermined, varying from 0 (EL condition) to 1, 2, 3, 4 or 5 errors (TEL condition). Results showed a beneficial effect of EL on memory performance in both ABI patients and controls (p <.001), but this advantage was not larger in ABI patients compared to controls and was not moderated by the amount of errors made during learning. [ABSTRACT FROM AUTHOR]

Background: Cognitive decline remains difficult to predict as structural brain damage cannot fully explain the extensive heterogeneity found between MS patients. Objective: To investigate whether functional brain network organization measured with magnetoencephalography (MEG) predicts cognitive decline in MS patients after 5 years and to explore its value beyond structural pathology. Methods: Resting-state MEG recordings, structural MRI, and neuropsychological assessments were analyzed of 146 MS patients, and 100 patients had a 5-year follow-up neuropsychological assessment. Network properties of the minimum spanning tree (i.e. backbone of the functional brain network) indicating network integration and overload were related to baseline and longitudinal cognition, correcting for structural damage. Results: A more integrated beta band network (i.e. smaller diameter) and a less integrated delta band network (i.e. lower leaf fraction) predicted cognitive decline after 5 years ( R adj 2 = 15 %), independent of structural damage. Cross-sectional analyses showed that a less integrated network (e.g. lower tree hierarchy) related to worse cognition, independent of frequency band. Conclusions: The level of functional brain network integration was an independent predictive marker of cognitive decline, in addition to the severity of structural damage. This work thereby indicates the promise of MEG-derived network measures in predicting disease progression in MS. [ABSTRACT FROM AUTHOR]

The Modified Six Elements Test (MSET) is used to examine executive deficits—more specifically, planning deficits. This study investigates the reliability of an adapted version of the MSET and proposes a novel scoring method. Two parallel versions of the adapted MSET were administered in 60 healthy participants in a counterbalanced order. Test–retest and parallel-form reliability were examined using intraclass correlation coefficients, Bland-Altman analyses, standard errors of measurement, and smallest real differences, representing clinically relevant changes over time. Moreover, the ecological validity of the adapted MSET was evaluated using the Executive Function Index, a self-rating questionnaire measuring everyday executive performance. No systematic differences between the test occasions were present, and the adapted MSET including the proposed scoring method was capable of detecting real clinical changes. Intraclass correlations for the test–retest and parallel-form reliability were modest, and the variability between the test scores was high. The nonsignificant correlations with the Executive Function Index did not confirm the previously established ecological validity of the MSET. We show that both parallel versions of the test are clinically equivalent and can be used to measure executive function over the course of time without task-specific learning effects. [ABSTRACT FROM PUBLISHER]

Background: Cognitive decline remains difficult to predict as structural brain damage cannot fully explain the extensive heterogeneity found between MS patients., Objective: To investigate whether functional brain network organization measured with magnetoencephalography (MEG) predicts cognitive decline in MS patients after 5 years and to explore its value beyond structural pathology., Methods: Resting-state MEG recordings, structural MRI, and neuropsychological assessments were analyzed of 146 MS patients, and 100 patients had a 5-year follow-up neuropsychological assessment. Network properties of the minimum spanning tree (i.e. backbone of the functional brain network) indicating network integration and overload were related to baseline and longitudinal cognition, correcting for structural damage., Results: A more integrated beta band network (i.e. smaller diameter) and a less integrated delta band network (i.e. lower leaf fraction) predicted cognitive decline after 5 years ( R adj 2 = 15 % ), independent of structural damage. Cross-sectional analyses showed that a less integrated network (e.g. lower tree hierarchy) related to worse cognition, independent of frequency band., Conclusions: The level of functional brain network integration was an independent predictive marker of cognitive decline, in addition to the severity of structural damage. This work thereby indicates the promise of MEG-derived network measures in predicting disease progression in MS.