@article{HalderHammerKleihetal.2013, author = {Halder, Sebastian and Hammer, Eva Maria and Kleih, Sonja Claudia and Bogdan, Martin and Rosenstiel, Wolfgang and Birbaumer, Niels and K{\"u}bler, Andrea}, title = {Prediction of Auditory and Visual P300 Brain-Computer Interface Aptitude}, series = {PLoS ONE}, volume = {8}, journal = {PLoS ONE}, number = {2}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-130327}, pages = {e53513}, year = {2013}, abstract = {Objective Brain-computer interfaces (BCIs) provide a non-muscular communication channel for patients with late-stage motoneuron disease (e.g., amyotrophic lateral sclerosis (ALS)) or otherwise motor impaired people and are also used for motor rehabilitation in chronic stroke. Differences in the ability to use a BCI vary from person to person and from session to session. A reliable predictor of aptitude would allow for the selection of suitable BCI paradigms. For this reason, we investigated whether P300 BCI aptitude could be predicted from a short experiment with a standard auditory oddball. Methods Forty healthy participants performed an electroencephalography (EEG) based visual and auditory P300-BCI spelling task in a single session. In addition, prior to each session an auditory oddball was presented. Features extracted from the auditory oddball were analyzed with respect to predictive power for BCI aptitude. Results Correlation between auditory oddball response and P300 BCI accuracy revealed a strong relationship between accuracy and N2 amplitude and the amplitude of a late ERP component between 400 and 600 ms. Interestingly, the P3 amplitude of the auditory oddball response was not correlated with accuracy. Conclusions Event-related potentials recorded during a standard auditory oddball session moderately predict aptitude in an audiory and highly in a visual P300 BCI. The predictor will allow for faster paradigm selection. Significance Our method will reduce strain on patients because unsuccessful training may be avoided, provided the results can be generalized to the patient population.}, language = {en} } @article{MartensBenschHalderetal.2014, author = {Martens, Suzanne and Bensch, Michael and Halder, Sebastian and Hill, Jeremy and Nijboer, Femke and Ramos-Murguialday, Ander and Schoelkopf, Bernhard and Birbaumer, Niels and Gharabaghi, Alireza}, title = {Epidural electrocorticography for monitoring of arousal in locked-in state}, series = {Frontiers in Human Neuroscience}, volume = {8}, journal = {Frontiers in Human Neuroscience}, doi = {10.3389/fnhum.2014.00861}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-114863}, pages = {861}, year = {2014}, abstract = {Electroencephalography (EEG) often fails to assess both the level (i.e., arousal) and the content (i.e., awareness) of pathologically altered consciousness in patients without motor responsiveness. This might be related to a decline of awareness, to episodes of low arousal and disturbed sleep patterns, and/or to distorting and attenuating effects of the skull and intermediate tissue on the recorded brain signals. Novel approaches are required to overcome these limitations. We introduced epidural electrocorticography (ECoG) for monitoring of cortical physiology in a late-stage amytrophic lateral sclerosis patient in completely locked-in state (CLIS) Despite long-term application for a period of six months, no implant related complications occurred. Recordings from the left frontal cortex were sufficient to identify three arousal states. Spectral analysis of the intrinsic oscillatory activity enabled us to extract state-dependent dominant frequencies at <4, similar to 7 and similar to 20 Hz, representing sleep-like periods, and phases of low and elevated arousal, respectively. In the absence of other biomarkers, ECoG proved to be a reliable tool for monitoring circadian rhythmicity, i.e., avoiding interference with the patient when he was sleeping and exploiting time windows of responsiveness. Moreover, the effects of interventions addressing the patient's arousal, e.g., amantadine medication, could be evaluated objectively on the basis of physiological markers, even in the absence of behavioral parameters. Epidural ECoG constitutes a feasible trade-off between surgical risk and quality of recorded brain signals to gain information on the patient's present level of arousal. This approach enables us to optimize the timing of interactions and medical interventions, all of which should take place when the patient is in a phase of high arousal. Furthermore, avoiding low responsiveness periods will facilitate measures to implement alternative communication pathways involving brain-computer interfaces (BCI).}, language = {en} } @article{HalderRufFurdeaetal.2013, author = {Halder, Sebastian and Ruf, Carolin Anne and Furdea, Adrian and Pasqualotto, Emanuele and De Massari, Daniele and van der Heiden, Linda and Bogdan, Martin and Rosenstiel, Wolfgang and Birbaumer, Niels and K{\"u}bler, Andrea and Matuz, Tamara}, title = {Prediction of P300 BCI Aptitude in Severe Motor Impairment}, series = {PLoS ONE}, journal = {PLoS ONE}, doi = {10.1371/journal.pone.0076148}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-97268}, year = {2013}, abstract = {Brain-computer interfaces (BCIs) provide a non-muscular communication channel for persons with severe motor impairments. Previous studies have shown that the aptitude with which a BCI can be controlled varies from person to person. A reliable predictor of performance could facilitate selection of a suitable BCI paradigm. Eleven severely motor impaired participants performed three sessions of a P300 BCI web browsing task. Before each session auditory oddball data were collected to predict the BCI aptitude of the participants exhibited in the current session. We found a strong relationship of early positive and negative potentials around 200 ms (elicited with the auditory oddball task) with performance. The amplitude of the P2 (r = -0.77) and of the N2 (r = -0.86) had the strongest correlations. Aptitude prediction using an auditory oddball was successful. The finding that the N2 amplitude is a stronger predictor of performance than P3 amplitude was reproduced after initially showing this effect with a healthy sample of BCI users. This will reduce strain on the end-users by minimizing the time needed to find suitable paradigms and inspire new approaches to improve performance.}, language = {en} } @article{HalderVarkutiBogdanetal.2013, author = {Halder, Sebastian and Varkuti, Balint and Bogdan, Martin and K{\"u}bler, Andrea and Rosenstiel, Wolfgang and Sitaram, Ranganatha and Birbaumer, Niels}, title = {Prediction of brain-computer interface aptitude from individual brain structure}, series = {Frontiers in Human Neuroscience}, journal = {Frontiers in Human Neuroscience}, doi = {10.3389/fnhum.2013.00105}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-96558}, year = {2013}, abstract = {Objective: Brain-computer interface (BCI) provide a non-muscular communication channel for patients with impairments of the motor system. A significant number of BCI users is unable to obtain voluntary control of a BCI-system in proper time. This makes methods that can be used to determine the aptitude of a user necessary. Methods: We hypothesized that integrity and connectivity of involved white matter connections may serve as a predictor of individual BCI-performance. Therefore, we analyzed structural data from anatomical scans and DTI of motor imagery BCI-users differentiated into high and low BCI-aptitude groups based on their overall performance. Results: Using a machine learning classification method we identified discriminating structural brain trait features and correlated the best features with a continuous measure of individual BCI-performance. Prediction of the aptitude group of each participant was possible with near perfect accuracy (one error). Conclusions: Tissue volumetric analysis yielded only poor classification results. In contrast, the structural integrity and myelination quality of deep white matter structures such as the Corpus Callosum, Cingulum, and Superior Fronto-Occipital Fascicle were positively correlated with individual BCI-performance. Significance: This confirms that structural brain traits contribute to individual performance in BCI use.}, language = {en} } @article{PauliSchwenzerBrodyetal.1993, author = {Pauli, Paul and Schwenzer, Michael and Brody, Stuart and Rau, Harald and Birbaumer, Niels}, title = {Hypochondriacal attitudes, pain sensitivity, and attentional bias}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-32617}, year = {1993}, abstract = {The relation between hypochondriacal attitudes, thermal pain threshold, and attentional bias toward pain was examined in a non-clinical population (N = 28). Attentional bias was operationalized with a concentration-performance test, which subjects performed while connected to a pain stimulator. Subjects were informed that they would receive a painful stimulus during the second part of the test, while the first part was introduced as pain-free. The pain stimulus was never applied during the test phase. The expectancy of a forthcoming pain stimulus reduced the performance of high hypochondriacal subjects in both parts of the test. Low hypochondriacal subjects, on the other hand, displayed significantly better performance in the first, pain-free compared to the second, pain-related part of the test. Thermal pain thresholds were assessed at four measuring sites (thenar, neck, collar-bone, abdomen), but no relations with hypochondriasis sum scores and locus of pain stimulation were found. A stepwise multiple regression of pain threshold by individual Illness Attitude Scales (IAS) led to 66\% of the variance being explained by the scales 'concern about pain', 'worry about illness', and 'disease phobia'. Results are discussed in terms of amplifying somatic style, preoccupation with or attentional bias toward bodily symptoms, and experimental induction of a hypochondriacal state.}, language = {en} } @article{PauliRauZhuangetal.1993, author = {Pauli, Paul and Rau, Harald and Zhuang, Ping and Brody, Stuart and Birbaumer, Niels}, title = {Effects of smoking on thermal pain threshold in deprived and minimally-deprived habitual smokers}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-32607}, year = {1993}, abstract = {This study examined the antinociceptive effects of smoking in nine habitual smokers under deprived (12 h) and minimally-deprived (< 30min) conditions. Pain threshold for thermal stimuli, heart rate, blood pressure and ratings of mood, arousal, dominance and well-being were assessed before and after smoking a cigarette. Overall, smoking affected all measured variables in the expected direction, leading to increased physiological activity, elevated pain threshold and improved mood. However, most of these effects depended on the deprivation status of the subjects, such that smoking after deprivation increased pain threshold whereas smoking after minimal deprivation did not. Pain threshold before smoking was the same for both groups. Deprived subjects had lower pre-smoke diastolic blood pressure, heart rate, and arousal levels, which rose to equal minimally-deprived subjects scores after smoking.}, language = {en} } @article{MatuzBirbaumerHautzingeretal., author = {Matuz, Tamara and Birbaumer, Niels and Hautzinger, Martin and K{\"u}bler, Andrea}, title = {Psychosocial adjustment to ALS: a longitudinal study}, series = {Frontiers in Psychology}, volume = {6}, journal = {Frontiers in Psychology}, number = {1197}, issn = {1664-1078}, doi = {10.3389/fpsyg.2015.01197}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-190208}, abstract = {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.}, language = {en} }