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It is one of the primary goals of medical care to secure good quality of life (QoL) while prolonging survival. This is a major challenge in severe medical conditions with a prognosis such as amyotrophic lateral sclerosis (ALS). Further, the definition of QoL and the question whether survival in this severe condition is compatible with a good QoL is a matter of subjective and culture-specific debate. Some people without neurodegenerative conditions believe that physical decline is incompatible with satisfactory QoL. Current data provide extensive evidence that psychosocial adaptation in ALS is possible, indicated by a satisfactory QoL. Thus, there is no fatalistic link of loss of QoL when physical health declines. There are intrinsic and extrinsic factors that have been shown to successfully facilitate and secure QoL in ALS which will be reviewed in the following article following the four ethical principles (1) Beneficence, (2) Non-maleficence, (3) Autonomy and (4) Justice, which are regarded as key elements of patient centered medical care according to Beauchamp and Childress. This is a JPND-funded work to summarize findings of the project NEEDSinALS (www.NEEDSinALS.com) which highlights subjective perspectives and preferences in medical decision making in ALS.
Tactile stimulation is less frequently used than visual for brain-computer interface (BCI) control, partly because of limitations in speed and accuracy. Non-visual BCI paradigms, however, may be required for patients who struggle with vision dependent BCIs because of a loss of gaze control. With the present study, we attempted to replicate earlier results by Herweg et al. (2016), with several minor adjustments and a focus on training effects and usability. We invited 16 healthy participants and trained them with a 4-class tactile P300-based BCI in five sessions. Their main task was to navigate a virtual wheelchair through a 3D apartment using the BCI. We found significant training effects on information transfer rate (ITR), which increased from a mean of 3.10–9.50 bits/min. Further, both online and offline accuracies significantly increased with training from 65% to 86% and 70% to 95%, respectively. We found only a descriptive increase of P300 amplitudes at Fz and Cz with training. Furthermore, we report subjective data from questionnaires, which indicated a relatively high workload and moderate to high satisfaction. Although our participants have not achieved the same high performance as in the Herweg et al. (2016) study, we provide evidence for training effects on performance with a tactile BCI and confirm the feasibility of the paradigm.
Chronic alcohol use leads to specific neurobiological alterations in the dopaminergic brain reward system, which probably are leading to a reward deficiency syndrome in alcohol dependence. The purpose of our study was to examine the effects of such hypothesized neurobiological alterations on the behavioral level, and more precisely on the implicit and explicit reward learning. Alcohol users were classified as dependent drinkers (using the DSM-IV criteria), binge drinkers (using criteria of the USA National Institute on Alcohol Abuse and Alcoholism) or low-risk drinkers (following recommendations of the Scientific board of trustees of the German Health Ministry). The final sample (n = 94) consisted of 36 low-risk alcohol users, 37 binge drinkers and 21 abstinent alcohol dependent patients. Participants were administered a probabilistic implicit reward learning task and an explicit reward- and punishment-based trial-and-error-learning task. Alcohol dependent patients showed a lower performance in implicit and explicit reward learning than low risk drinkers. Binge drinkers learned less than low-risk drinkers in the implicit learning task. The results support the assumption that binge drinking and alcohol dependence are related to a chronic reward deficit. Binge drinking accompanied by implicit reward learning deficits could increase the risk for the development of an alcohol dependence.
For the current study the Lazarian stress-coping theory and the appendant model of psychosocial adjustment to chronic illness and disabilities (Pakenham, 1999) has shaped the foundation for identifying determinants of adjustment to ALS. We aimed to investigate the evolution of psychosocial adjustment to ALS and to determine its long-term predictors. A longitudinal study design with four measurement time points was therefore, used to assess patients' quality of life, depression, and stress-coping model related aspects, such as illness characteristics, social support, cognitive appraisals, and coping strategies during a period of 2 years. Regression analyses revealed that 55% of the variance of severity of depressive symptoms and 47% of the variance in quality of life at T2 was accounted for by all the T1 predictor variables taken together. On the level of individual contributions, protective buffering, and appraisal of own coping potential accounted for a significant percentage in the variance in severity of depressive symptoms, whereas problem management coping strategies explained variance in quality of life scores. Illness characteristics at T2 did not explain any variance of both adjustment outcomes. Overall, the pattern of the longitudinal results indicated stable depressive symptoms and quality of life indices reflecting a successful adjustment to the disease across four measurement time points during a period of about two years. Empirical evidence is provided for the predictive value of social support, cognitive appraisals, and coping strategies, but not illness parameters such as severity and duration for adaptation to ALS. The current study contributes to a better conceptualization of adjustment, allowing us to provide evidence-based support beyond medical and physical intervention for people with ALS.
Task instructions modulate the attentional mode affecting the auditory MMN and the semantic N400
(2014)
Event-related potentials (ERPs) have been proven to be a useful tool to complement clinical assessment and to detect residual cognitive functions in patients with disorders of consciousness. These ERPs are of ten recorded using passive or unspecific instructions. Patient data obtained this way are then compared to data from healthy participants, which are usually recorded using active instructions. The present study investigates the effect of attentive modulations and particularly the effect of activevs. passive instruction on the ERP components mismatch negativity (MMN) and N400. A sample of 18 healthy participants listened to three auditory paradigms: anoddball, aword priming, and a sentence paradigm. Each paradigm was presented three times with different instructions: ignoring auditory stimuli, passive listening, and focused attention on the auditory stimuli. After each task, the participants indicated their subjective effort. The N400 decreased from the focused task to the passive task, and was extinct in the ignore task. The MMN exhibited higher amplitudes in the focused and passive task compared to the ignore task. The data indicate an effect of attention on the supratemporal component of the MMN. Subjective effort was equally high in the passive and focused tasks but reduced in the ignore task. We conclude that passive listening during EEG recording is stressful and attenuates ERPs, which renders the interpretation of the results obtained in such conditions difficult.
Modulation of sensorimotor rhythms (SMR) was suggested as a control signal for brain-computer interfaces (BCI). Yet, there is a population of users estimated between 10 to 50% not able to achieve reliable control and only about 20% of users achieve high (80–100%) performance. Predicting performance prior to BCI use would facilitate selection of the most feasible system for an individual, thus constitute a practical benefit for the user, and increase our knowledge about the correlates of BCI control. In a recent study, we predicted SMR-BCI performance from psychological variables that were assessed prior to the BCI sessions and BCI control was supported with machine-learning techniques. We described two significant psychological predictors, namely the visuo-motor coordination ability and the ability to concentrate on the task. The purpose of the current study was to replicate these results thereby validating these predictors within a neurofeedback based SMR-BCI that involved no machine learning.Thirty-three healthy BCI novices participated in a calibration session and three further neurofeedback training sessions. Two variables were related with mean SMR-BCI performance: (1) a measure for the accuracy of fine motor skills, i.e., a trade for a person’s visuo-motor control ability; and (2) subject’s “attentional impulsivity”. In a linear regression they accounted for almost 20% in variance of SMR-BCI performance, but predictor (1) failed significance. Nevertheless, on the basis of our prior regression model for sensorimotor control ability we could predict current SMR-BCI performance with an average prediction error of M = 12.07%. In more than 50% of the participants, the prediction error was smaller than 10%. Hence, psychological variables played a moderate role in predicting SMR-BCI performance in a neurofeedback approach that involved no machine learning. Future studies are needed to further consolidate (or reject) the present predictors.
Objective: The aim of this longitudinal study was to identify predictors of instantaneous well-being in patients with amyotrophic lateral sclerosis (ALS). Based on flow theory well-being was expected to be highest when perceived demands and perceived control were in balance, and that thinking about the past would be a risk factor for rumination which would in turn reduce well-being.
Methods: Using the experience sampling method, data on current activities, associated aspects of perceived demands, control, and well-being were collected from 10 patients with ALS three times a day for two weeks.
Results: Results show that perceived control was uniformly and positively associated with well-being, but that demands were only positively associated with well-being when they were perceived as controllable. Mediation analysis confirmed thinking about the past, but not thinking about the future, to be a risk factor for rumination and reduced well-being.
Discussion: Findings extend our knowledge of factors contributing to well-being in ALS as not only perceived control but also perceived demands can contribute to well-being. They further show that a focus on present experiences might contribute to increased well-being.
One of the most often used instruments for the assessment of food cravings is the Food Cravings Questionnaire (FCQ), which consists of a trait (FCQ-T; 39 items) and state (FCQ-S; 15 items) version. Scores on the FCQ-T have been found to be positively associated with eating pathology, body mass index (BMI), low dieting success and increases in state food craving during cognitive tasks involving appealing food stimuli. The current studies evaluated reliability and validity of a reduced version of the FCQ-T consisting of 15 items only (FCQ-T-r). Study 1 was a questionnaire study conducted online among students (N = 323). In study 2, female students (N = 70) performed a working memory task involving food and neutral pictures. Study 1 indicated a one-factorial structure and high internal consistency (α = 0.94) of the FCQ-T-r. Scores of the FCQ-T-r were positively correlated with BMI and negatively correlated with dieting success. In study 2, participants reported higher state food craving after the task compared to before. This increase was positively correlated with the FCQ-T-r. Hours since the last meal positively predicted food craving before the task when controlling for FCQ-T-r scores and the interaction of both variables. Contrarily, FCQ-T-r scores positively predicted food craving after the task when controlling for food deprivation and the interaction term. Thus, trait food craving was specifically associated with state food craving triggered by palatable food-cues, but not with state food craving related to plain hunger. Results indicate high reliability of the FCQ-T-r. Replicating studies that used the long version, small-to-medium correlations with BMI and dieting success could be found. Finally, scores on the FCQ-T-r predicted cue-elicited food craving, providing further support of its validity. The FCQ-T-r constitutes a succinct, valid and reliable self-report measure to efficiently assess experiences of food craving as a trait.
This study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT) as a method for the extraction and assessment of event-related brain potentials (ERP) in data from a single subject. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of the t-CWT were assessed and compared to a variety of competing procedures using simulated EEG data at six low signal-to-noise ratios. Results show that the t-CWT combines high sensitivity and specificity with favorable PPV and NPV. Applying the t-CWT to authentic EEG data obtained from 14 healthy participants confirmed its high sensitivity. The t-CWT may thus be well suited for the assessment of weak ERPs in single-subject settings.
Large-Scale Assessment of a Fully Automatic Co-Adaptive Motor Imagery-Based Brain Computer Interface
(2016)
In the last years Brain Computer Interface (BCI) technology has benefited from the development of sophisticated machine leaning methods that let the user operate the BCI after a few trials of calibration. One remarkable example is the recent development of co-adaptive techniques that proved to extend the use of BCIs also to people not able to achieve successful control with the standard BCI procedure. Especially for BCIs based on the modulation of the Sensorimotor Rhythm (SMR) these improvements are essential, since a not negligible percentage of users is unable to operate SMR-BCIs efficiently. In this study we evaluated for the first time a fully automatic co-adaptive BCI system on a large scale. A pool of 168 participants naive to BCIs operated the co-adaptive SMR-BCI in one single session. Different psychological interventions were performed prior the BCI session in order to investigate how motor coordination training and relaxation could influence BCI performance. A neurophysiological indicator based on the Power Spectral Density (PSD) was extracted by the recording of few minutes of resting state brain activity and tested as predictor of BCI performances. Results show that high accuracies in operating the BCI could be reached by the majority of the participants before the end of the session. BCI performances could be significantly predicted by the neurophysiological indicator, consolidating the validity of the model previously developed. Anyway, we still found about 22% of users with performance significantly lower than the threshold of efficient BCI control at the end of the session. Being the inter-subject variability still the major problem of BCI technology, we pointed out crucial issues for those who did not achieve sufficient control. Finally, we propose valid developments to move a step forward to the applicability of the promising co-adaptive methods.