Does cognitive flexibility training enhance subjective mental functioning in healthy older adults?

Declining cognitive abilities in older adults can contribute to significant changes in socioemotional health and substantially reduce their perception of well-being. Whereas much attention has been dedicated to creating cognitive training programs to improve cognitive health in old age, there is little emphasis on the consequences of such interventions for subjective mental functioning. We created a randomized controlled trial in which we evaluated the effects of an adaptive computerized cognitive flexibility training. Healthy older adults (60-80 years old) were assigned to one of three conditions (frequent or infrequent switching or active control group) and performed 58 half-hour sessions within a period of 12 weeks. We measured effects on subjective cognitive failures and executive dysfunctioning, everyday functioning, depressive symptoms, anxiety, and quality of life, before, and after training. Additionally, participants' proxies rated their cognitive failures and executive dysfunctioning. Subjective cognitive failures and executive dysfunctioning improved 4 weeks posttraining in all groups, although effect sizes were low (ɳp2 = .058 and .079, respectively) and there were no differences between groups (all p's > .38). No significant changes in subjective reports were seen directly after training, which was the case in all groups. Proxies did not report any functional changes over time, yet their evaluations were significantly more favorable than those of the participants, both pretraining (p < .0005) and posttraining (p = .004). Although we found no evidence of improvement on subjective mental functioning, we adduce several factors that encourage further research into the effects of computerized cognitive training on subjective performance.

Cognitive Flexibility Training: A Large-Scale Multimodal Adaptive Active-Control Intervention Study in Healthy Older Adults.

As aging is associated with cognitive decline, particularly in the executive functions, it is essential to effectively improve cognition in older adults. Online cognitive training is currently a popular, though controversial method. Although some changes seem possible in older adults through training, far transfer, and longitudinal maintenance are rarely seen. Based on previous literature we created a unique, state-of-the-art intervention study by incorporating frequent sessions and flexible, novel, adaptive training tasks, along with an active control group. We created a program called TAPASS (Training Project Amsterdam Seniors and Stroke), a randomized controlled trial. Healthy older adults (60-80 y.o.) were assigned to a frequent- (FS) or infrequent switching (IS) experimental condition or to the active control group and performed 58 half-hour sessions over the course of 12 weeks. Effects on executive functioning, processing- and psychomotor speed, planning, verbal long term memory, verbal fluency, and reasoning were measured on four time points before, during and after the training. Additionally, we examined the explorative question which individual aspects added to training benefit. Besides improvements on the training, we found significant time effects on multiple transfer tasks in all three groups that likely reflected retest effects. No training-specific improvements were detected, and we did not find evidence of additional benefits of individual characteristics. Judging from these results, the therapeutic value of using commercially available training games to train the aging brain is modest, though any apparent effects should be ascribed more to expectancy and motivation than to the elements in our training protocol. Our results emphasize the importance of using parallel tests as outcome measures for transfer and including both active and passive control conditions. Further investigation into different training methods is advised, including stimulating social interaction and the use of more variable, novel, group-based yet individual-adjusted exercises.

The influence of computer-based cognitive flexibility training on subjective cognitive well-being after stroke: A multi-center randomized controlled trial.

BACKGROUND: Stroke can result in cognitive complaints that can have a large impact on quality of life long after its occurrence. A number of computer-based training programs have been developed with the aim to improve cognitive functioning. Most studies investigating their efficacy used only objective outcome measures, whereas a reduction of subjective cognitive complaints may be equally important for improving quality of life. A few studies used subjective outcome measures but were inconclusive, partly due to methodological shortcomings such as lack of proper active and passive control groups. OBJECTIVE: The aim of the current study was to investigate whether computer-based cognitive flexibility training can improve subjective cognitive functioning and quality of life after stroke. METHODS: We performed a randomized controlled double blind trial (RCT). Adults (30-80 years old) who had a stroke 3 months to 5 years ago, were randomly assigned to either an intervention group (n = 38), an active control group (i.e., mock training; n = 35), or a waiting list control group (n = 24). The intervention and mock training consisted of 58 half-hour sessions within 12 weeks. The primary subjective outcome measures were cognitive functioning (Cognitive Failure Questionnaire), executive functioning (Dysexecutive Functioning Questionnaire), quality of life (Short Form Health Survey), instrumental activities of daily living (IADL; Lawton & Brody IADL scale), and participation in society (Utrecht Scale for Evaluation of Rehabilitation-Participation). Secondary subjective outcome measures were recovery after stroke, depressive symptoms (Hospital Anxiety Depression Scale-depression subscale), fatigue (Checklist Individual Strength-Fatigue subscale), and subjective cognitive improvement (exit list). Finally, a proxy of the participant rated the training effects in subjective cognitive functioning, subjective executive functioning, and IADL. RESULTS AND CONCLUSIONS: All groups improved on the two measures of subjective cognitive functioning and subjective executive functioning, but not on the other measures. These cognitive and executive improvements remained stable 4 weeks after training completion. However, the intervention group did not improve more than the two control groups. This suggests that improvement was due to training-unspecific effects. The proxies did not report any improvements. We, therefore, conclude that the computer-based cognitive flexibility training did not improve subjective cognitive functioning or quality of life after stroke.

Brain training improves recovery after stroke but waiting list improves equally: A multicenter randomized controlled trial of a computer-based cognitive flexibility training.

BACKGROUND: Brain training is currently widely used in an attempt to improve cognitive functioning. Computer-based training can be performed at home and could therefore be an effective add-on to available rehabilitation programs aimed at improving cognitive functioning. Several studies have reported cognitive improvements after computer training, but most lacked proper active and passive control conditions. OBJECTIVE: Our aim was to investigate whether computer-based cognitive flexibility training improves executive functioning after stroke. We also conducted within-group analyses similar to those used in previous studies, to assess inferences about transfer effects when comparisons to proper control groups are missing. METHODS: We conducted a randomized controlled, double blind trial. Adults (30-80 years old) who had suffered a stroke within the last 5 years were assigned to either an intervention group (n = 38), active control group (i.e., mock training; n = 35), or waiting list control group (n = 24). The intervention and mock training consisted of 58 half-hour sessions within a 12-week period. Cognitive functioning was assessed using several paper-and-pencil and computerized neuropsychological tasks before the training, immediately after training, and 4 weeks after training completion. RESULTS AND CONCLUSIONS: Both training groups improved on training tasks, and all groups improved on several transfer tasks (three executive functioning tasks, attention, reasoning, and psychomotor speed). Improvements remained 4 weeks after training completion. However, the amount of improvement in executive and general cognitive functioning in the intervention group was similar to that of both control groups (active control and waiting list). Therefore, this improvement was likely due to training-unspecific effects. Our results stress the importance to include both active and passive control conditions in the study design and analyses. Results from studies without proper control conditions should be interpreted with care.

Frontostriatal anatomical connections predict age- and difficulty-related differences in reinforcement learning.

Reinforcement learning (RL) is supported by a network of striatal and frontal cortical structures that are connected through white-matter fiber bundles. With age, the integrity of these white-matter connections declines. The role of structural frontostriatal connectivity in individual and age-related differences in RL is unclear, although local white-matter density and diffusivity have been linked to individual differences in RL. Here we show that frontostriatal tract counts in young human adults (aged 18-28), as assessed noninvasively with diffusion-weighted magnetic resonance imaging and probabilistic tractography, positively predicted individual differences in RL when learning was difficult (70% valid feedback). In older adults (aged 63-87), in contrast, learning under both easy (90% valid feedback) and difficult conditions was predicted by tract counts in the same frontostriatal network. Furthermore, network-level analyses showed a double dissociation between the task-relevant networks in young and older adults, suggesting that older adults relied on different frontostriatal networks than young adults to obtain the same task performance. These results highlight the importance of successful information integration across striatal and frontal regions during RL, especially with variable outcomes.

Brain training in progress: a review of trainability in healthy seniors.

The cognitive deterioration associated with aging is accompanied by structural alterations and loss of functionality of the frontostriatal dopamine system. The question arises how such deleterious cognitive effects could be countered. Brain training, currently highly popular among young and old alike, promises that users will improve on certain neurocognitive skills, and this has indeed been confirmed in a number of studies. Based on these results, it seems reasonable to expect beneficial effects of brain training in the elderly as well. A selective review of the existing literature suggests, however, that the results are neither robust nor consistent, and that transfer and sustained effects thus far appear limited. Based on this review, we argue for a series of elements that hold potential for progress in successful types of brain training: (1) including flexibility and novelty as features of the training, (2) focusing on a number of promising, yet largely unexplored domains, such as decision-making and memory strategy training, and (3) tailoring the training adaptively to the level and progress of the individual. We also emphasize the need for covariance-based MRI methods in linking structural and functional changes in the aging brain to individual differences in neurocognitive efficiency and trainability in order to further uncover the underlying mechanisms.

Remedial effects of motivational incentive on declining cognitive control in healthy aging and Parkinson's disease.

The prospect of reward may provide a motivational incentive for optimizing goal-directed behavior. Animal work demonstrates that reward-processing networks and oculomotor-control networks in the brain are connected through the dorsal striatum, and that reward anticipation can improve oculomotor control via this nexus. Due perhaps to deterioration in dopaminergic striatal circuitry, goal-directed oculomotor control is subject to decline in healthy seniors, and even more in individuals with Parkinson's disease (PD). Here we examine whether healthy seniors and PD patients are able to utilize reward prospects to improve their impaired antisaccade performance. Results confirmed that oculomotor control declined in PD patients compared to healthy seniors, and in healthy seniors compared to young adults. However, the motivational incentive of reward expectation resulted in benefits in antisaccade performance in all groups alike. These findings speak against structural and non-modifiable decline in cognitive control functions, and emphasize the remedial potential of motivational incentive mechanisms in healthy as well as pathological aging.