Editorial: Cognitive and Motor Control Based on Brain-Computer Interfaces for Improving the Health and Well-Being in Older Age.
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SUBMITTER: Belkacem AN
PROVIDER: S-EPMC9019071 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
Publications
Editorial: Cognitive and Motor Control Based on Brain-Computer Interfaces for Improving the Health and Well-Being in Older Age.
Belkacem Abdelkader Nasreddine AN Falk Tiago H TH Yanagisawa Takufumi T Guger Christoph C
Frontiers in human neuroscience 20220406
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Project description:Maintaining emotional well-being in late life is crucial for achieving successful and healthy aging. While previous research from Western cultures has documented that emotional well-being improves as individuals get older, previous research provided mixed evidence on the effects of age on well-being in Eastern Asian cultures. However, previous studies in East Asia do not always take into account the effects of cognitive control-an ability which has been considered as a key to enable older adults to regulate their emotions. In the current study, we tested whether cognitive control abilities interact with age in determining individuals' well-being in 59 Japanese females (age range: 26-79; M age = 64.95). Participants' mental health and mental fatigue were tracked for 5 years together with their cognitive control abilities. We found that as individuals became older, they showed improved mental health and decreased mental fatigue. In addition, we found a quadratic effect of age on mental fatigue, which was further qualified by baseline cognitive control abilities. Specifically, in those who had a lower level of cognitive control abilities, mental fatigue declined until the mid-60s, at which point it started increasing (a U-shape effect). In contrast, in those who had a higher level of cognitive control ability, mental fatigue showed a steady decrease with age even after their mid-60s. These results suggest that whether advancing age is associated with positive vs. negative changes in well-being depends on cognitive control abilities, and that preserved cognitive control is a key to maintain well-being in late life.
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Project description:Motor Imagery BCI systems have a high rate of users that are not capable of modulating their brain activity accurately enough to communicate with the system. Several studies have identified psychological, cognitive, and neurophysiological measures that might explain this MI-BCI inefficiency. Traditional research had focused on mu suppression in the sensorimotor area in order to classify imagery, but this does not reflect the true dynamics that underlie motor imagery. Functional connectivity reflects the interaction between brain regions during the MI task and resting-state network and is a promising tool in improving MI-BCI classification. In this study, 54 novice MI-BCI users were split into two groups based on their accuracy and their functional connectivity was compared in three network scales (Global, Large and Local scale) during the resting-state, left vs. right-hand motor imagery task, and the transition between the two phases. Our comparison of High and Low BCI performers showed that in the alpha band, functional connectivity in the right hemisphere was increased in High compared to Low aptitude MI-BCI users during motor imagery. These findings contribute to the existing literature that indeed connectivity might be a valuable feature in MI-BCI classification and in solving the MI-BCI inefficiency problem.
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Project description:It has been demonstrated that, on their own, both exercise and stimulation from the environment can improve cognitive function and well-being in older adults. The combined effect of exercising in the outdoor environment on psychological function is less well studied. The aim of the current study was to investigate the effect of an outdoor cycling intervention on cognitive function and mental health and well-being in older adults. A total of 100 older adults took part in the study (aged 50-83), 26 of which were non-cycling controls, 36 were conventional pedal cyclists and 38 were participants using an e-bike (a bike fitted with an electric motor to provide assistance with pedaling), as part of a larger project (www.cycleboom.org). Participants took part in the study for an eight-week period, with cycling participants required to cycle at least three times a week for thirty minutes in duration for each cycle ride. Cognitive function and well-being were measured before and after the intervention period. For executive function, namely inhibition (the Stroop task) and updating (Letter Updating Task), both cycling groups improved in accuracy after the intervention compared to non-cycling control participants. E-bike participants also improved in processing speed (reaction times in go trials of the Stop-It task) after the intervention compared to non-cycling control participants. Finally, e-bike participants improved in their mental health score after the intervention compared to non-cycling controls as measured by the SF-36. This suggests that there may be an impact of exercising in the environment on executive function and mental health. Importantly, we showed a similar (sometimes larger) effect for the e-bike group compared to the pedal cyclists. This suggests that it is not just the physical activity component of cycling that is having an influence. Both pedal cycles and e-bikes can enable increased physical activity and engagement with the outdoor environment with e-bikes potentially providing greater benefits.
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Project description:A large number of older adults have physical and/or cognitive challenges and require help to manage everyday activities. Many older adults receive care from a spouse. Over the long term, this has adverse consequences for caregiver health and well-being. Less is known about the outcomes associated with the early transition to becoming a spousal caregiver. Nor is it clear how mild-cognitive decline worsens caregiver outcomes. The present study uses dyadic data from 588 couples in the National Social Life, Health, and Aging Project to compare mental and social well-being in marital partners who became a spousal caregiver versus those who remained noncaregivers or became caregivers for someone other than a spouse between 2010 and 2015. Cognitive ability was assessed using a validated version of the Montreal Cognitive Assessment. Moderated Actor-Partner Independence Models revealed that becoming a caregiver was associated with an increase in perceived stress in both men and women, and an increase in anxiety among men. Partners' cognitive limitations moderated, in a dose-dependent fashion, the association between becoming a caregiver and changes in well-being. Specifically, becoming a caregiver was associated with increased support from friends for wives at lower levels of husband's cognitive ability, and with increased anxiety for husbands at lower levels of wife's cognitive ability. Associations were independent of demographic characteristics and physical limitations. We discuss the value of using population-based samples to study the transition to caregiving and implications for interventions during the early transition to a caregiving role for even modestly cognitively impaired partners. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
| S-EPMC6989024 | biostudies-literature
Project description:Purpose of the studyPrevious research has overlooked the heterogeneity in older adults' personal conceptions of subjective well-being (SWB), by not taking into account intradomain differences in the conceptions of SWB for different groups of older adults. The aim of this article is therefore to explore (a) older adults' own views on which aspects, categorized under domains, are important to their SWB and (b) which domains and aspects are important to older adults in different contexts and with different characteristics: to men and women, of different ages, and in different housing arrangements.Design and methodsSixty-six older adults (aged 65 and older) participated in our study. We asked the participants to freely nominate aspects of SWB that are important to them, using participant-generated word clouds as our exploratory, qualitative data collection method. The data were analyzed using qualitative inductive content analysis.ResultsWe found 15 domains based on our participants' conceptions of SWB. The multidimensional domains of social life, activities, health, and space and place were most important to our participants. The domains and aspects were defined and prioritized differently by different groups of participants.ImplicationsSWB should be studied as a multidimensional, individualized, and contextualized process to generate meaningful empirical information for researchers and policymakers.
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Project description: Not available
| S-EPMC10505724 | biostudies-literature
Project description:In a brain-computer interface (BCI) system, the testing of decoding algorithms, tasks, and their parameters is critical for optimizing performance. However, conducting human experiments can be costly and time-consuming, especially when investigating broad sets of parameters. Attempts to utilize previously collected data in offline analysis lack a co-adaptive feedback loop between the system and the user present online, limiting the applicability of the conclusions obtained to real-world uses of BCI. As such, a number of studies have attempted to address this cost-wise middle ground between offline and live experimentation with real-time neural activity simulators. We present one such system which generates motor imagery electroencephalography (EEG) via forward modeling and novel motor intention encoding models for conducting sensorimotor rhythm (SMR)-based continuous cursor control experiments in a closed-loop setting. We use the proposed simulator with 10 healthy human subjects to test the effect of three decoder and task parameters across 10 different values. Our simulated approach produces similar statistical conclusions to those produced during parallel, paired, online experimentation, but in 55% of the time. Notably, both online and simulated experimentation expressed a positive effect of cursor velocity limit on performance regardless of subject average performance, supporting the idea of relaxing constraints on cursor gain in online continuous cursor control. We demonstrate the merits of our closed-loop motor imagery EEG simulation, and provide an open-source framework to the community for closed-loop SMR-based BCI studies in the future. All code including the simulator have been made available on GitHub.
| S-EPMC9428352 | biostudies-literature
Project description:BackgroundStroke 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.ObjectiveThe 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.MethodsWe 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 conclusionsAll 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.
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Project description:Brain-computer interfaces (BCIs) can provide sensory feedback of ongoing brain oscillations, enabling stroke survivors to modulate their sensorimotor rhythms purposefully. A number of recent clinical studies indicate that repeated use of such BCIs might trigger neurological recovery and hence improvement in motor function. Here, we provide a first meta-analysis evaluating the clinical effectiveness of BCI-based post-stroke motor rehabilitation. Trials were identified using MEDLINE, CENTRAL, PEDro and by inspection of references in several review articles. We selected randomized controlled trials that used BCIs for post-stroke motor rehabilitation and provided motor impairment scores before and after the intervention. A random-effects inverse variance method was used to calculate the summary effect size. We initially identified 524 articles and, after removing duplicates, we screened titles and abstracts of 473 articles. We found 26 articles corresponding to BCI clinical trials, of these, there were nine studies that involved a total of 235 post-stroke survivors that fulfilled the inclusion criterion (randomized controlled trials that examined motor performance as an outcome measure) for the meta-analysis. Motor improvements, mostly quantified by the upper limb Fugl-Meyer Assessment (FMA-UE), exceeded the minimal clinically important difference (MCID=5.25) in six BCI studies, while such improvement was reached only in three control groups. Overall, the BCI training was associated with a standardized mean difference of 0.79 (95% CI: 0.37 to 1.20) in FMA-UE compared to control conditions, which is in the range of medium to large summary effect size. In addition, several studies indicated BCI-induced functional and structural neuroplasticity at a subclinical level. This suggests that BCI technology could be an effective intervention for post-stroke upper limb rehabilitation. However, more studies with larger sample size are required to increase the reliability of these results.
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Project description:Recent advancements in brain computer interfaces (BCI) have demonstrated control of robotic systems by mental processes alone. Together with invasive BCI, electroencephalographic (EEG) BCI represent an important direction in the development of BCI systems. In the context of EEG BCI, the processing of EEG data is the key challenge. Unfortunately, advances in that direction have been complicated by a lack of large and uniform datasets that could be used to design and evaluate different data processing approaches. In this work, we release a large set of EEG BCI data collected during the development of a slow cortical potentials-based EEG BCI. The dataset contains 60 h of EEG recordings, 13 participants, 75 recording sessions, 201 individual EEG BCI interaction session-segments, and over 60 000 examples of motor imageries in 4 interaction paradigms. The current dataset presents one of the largest EEG BCI datasets publically available to date.
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