TVA-based modeling of short-term memory capacity, speed of processing and perceptual threshold in chronic stroke patients undergoing cognitive training: case-control differences, reliability, and associations with cognitive performance

Rehabilitation of working memory after acquired brain injury and multiple sclerosis: A systematic review

The objective is to study the effectiveness of working memory (WM) rehabilitation after Acquired brain injury (ABI) and multiple sclerosis (MS). A systematic database search of published studies, following PRISMA recommendations, with assessment of methodological quality and risk of bias, was conducted. The results were analysed according to the rehabilitation method used. 31 studies (including 14 class I) were included, and 11 different training programs were identified. Despite great variability in training methodology and outcome measures, the results were positive overall. However, only three rehabilitation programs showed a transfer effect to WM (near) and daily life with long-term maintenance. The results were more variable for protocols limited to the use of computerized n-back training tasks. Overall, the current evidence supports multi-task WM training rather than single-task-limited program. It also supports early and long duration training, with some therapist support. However, it is not possible, to date, to make strong recommendations regarding the rehabilitation program to be used preferentially. Although results are encouraging, level of evidence remains modest, particularly regarding the maintenance of the therapeutic effect after the end of training, and the transfer to everyday life skills. The influence of rehabilitation parameters (training duration, therapist involvement … ) remains difficult to assess.

The effect of processing speed on verbal and visual memory of adults with a chronic acquired brain injury

OBJECTIVE

Memory problems are among the most frequently reported cognitive complaints by individuals with an acquired brain injury (ABI). Processing speed and working memory deficits are often the result of ABI. These cognitive deficits significantly impact the acquisition and retention of information necessary for memory formation. This study investigated the influence of processing speed and working memory on immediate and delayed recall for verbal and visual memory, as well as overall memory recall in adults living with a chronic ABI.

METHODS

Sixty-three participants living with a chronic ABI, who were at least one-year post-injury, were cognitively assessed with the CNS-Vital Signs (CNS-VS) computerized cognitive battery and Wechsler Test of Adult Reading.

RESULTS

The CNS-VS Processing Speed significantly predicted delayed recall for verbal memory and overall memory performance. The CNS-VS Working Memory was not a significant predictor of memory recall.

CONCLUSIONS

Processing speed deficits negatively impact memory in individuals with a chronic ABI. These findings suggest the memory recall of adults with a chronic ABI is associated with poor processing speed and poor acquisition of information. Therefore, cognitive rehabilitation that improves processing speed should be the focus for individuals with ABI to improve memory performance as well as impaired processing speed.

No add-on effect of tDCS on fatigue and depression in chronic stroke patients: A randomized sham-controlled trial combining tDCS with computerized cognitive training

BACKGROUND

Fatigue and emotional distress rank high among self-reported unmet needs in life after stroke. Transcranial direct current stimulation (tDCS) may have the potential to alleviate these symptoms for some patients, but the acceptability and effects for chronic stroke survivors need to be explored in randomized controlled trials.

METHODS

Using a randomized sham-controlled parallel design, we evaluated whether six sessions of 1 mA tDCS (anodal over F3, cathodal over O2) combined with computerized cognitive training reduced self-reported symptoms of fatigue and depression. Among the 74 chronic stroke patients enrolled at baseline, 54 patients completed the intervention. Measures of fatigue and depression were collected at five time points spanning a 2 months period.

RESULTS

While symptoms of fatigue and depression were reduced during the course of the intervention, Bayesian analyses provided evidence for no added beneficial effect of tDCS. Less severe baseline symptoms were associated with higher performance improvement in select cognitive tasks, and study withdrawal was higher in patients with more fatigue and younger age. Time-resolved symptom analyses by a network approach suggested higher centrality of fatigue items (except item 1 and 2) than depression items.

CONCLUSION

The results reveal no add-on effect of tDCS on fatigue or depression but support the notion of fatigue as a relevant clinical symptom with possible implications for treatment adherence and response.

Non-verbal intelligence outperforms selective attention in a visual short-term memory test

Short-term memory is a dynamic psychological process that operates within a network in which non-verbal intelligence and attentional domains are connected. However, no consensus has been reached about which process has the greatest effect on this memory ability, which was the main objective of the present study. A sample of 1448 Brazilian participants (mean age = 26.62 years, standard deviation = 9.97 years; 53.9% females) were collectively tested on pen-and-paper standardized and validated measures of selective (ROTAS-C), alternating (ROTAS-A), and divided (ROTAS-D) attention. They also performed the R1 Non-verbal Intelligence Test and a visual short-term memory test (Memória Visual de Curto Prazo [MEMORE] test). The statistical analyses consisted of a data mining procedure, in which exhaustive automatic selection screening was performed. The results were compared with Corrected Akaike Information Criteria. The linear model met the classic assumptions of ordinary least squares and only included main effects of selective attention (standardized β = 0.39) and non-verbal intelligence (standardized β = 0.37) as main predictors (F2,39 = 7.01, p < 0.01, adjusted R2 = 24%). The results are discussed within a cognitive psychology framework.