@article{MeuleFathRealetal.2013, author = {Meule, Adrian and Fath, Katharina and Real, Ruben G. L. and S{\"u}tterlin, Stefan and V{\"o}gele, Claus and K{\"u}bler, Andrea}, title = {Quality of life, emotion regulation, and heart rate variability in individuals with intellectual disabilities and concomitant impaired vision}, series = {Psychology of Well-Being: Theory, Research and Practice}, journal = {Psychology of Well-Being: Theory, Research and Practice}, doi = {10.1186/2211-1522-3-1}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-96247}, year = {2013}, abstract = {Background Positive associations have been found between quality of life, emotion regulation strategies, and heart rate variability (HRV) in people without intellectual disabilities. However, emotion regulation and HRV have rarely been investigated in people with intellectual disabilities. Assessment of subjectively reported quality of life and emotion regulation strategies in this population is even more difficult when participants are also visually impaired. Methods Subjective and objective quality of life, emotion regulation strategies, and HRV at rest were measured in a sample of people with intellectual disabilities and concomitant impaired vision (N = 35). Heart rate was recorded during a 10 min resting period. For the assessment of quality of life and emotion regulation, custom made tactile versions of questionnaire-based instruments were used that enabled participants to grasp response categories. Results The combined use of reappraisal and suppression as emotion regulation strategies was associated with higher HRV and quality of life. HRV was associated with objective quality of life only. Emotion regulation strategies partially mediated the relationship between HRV and quality of life. Conclusions Results replicate findings about associations between quality of life, emotion regulation, and HRV and extend them to individuals with intellectual disabilities. Furthermore, this study demonstrated that quality of life and emotion regulation could be assessed in such populations even with concomitant impaired vision with modified tactile versions of established questionnaires. HRV may be used as a physiological index to evaluate physical and affective conditions in this population.}, 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{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{HalderHammerKleihetal.2013, author = {Halder, Sebastian and Hammer, Eva Maria and Kleih, Sonja Claudia and Bogdan, Martin and Rosenstiel, Wolfgang and Birbaumer, Nils and K{\"u}bler, Andrea}, title = {Prediction of Auditory and Visual P300 Brain-Computer Interface Aptitude}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-77992}, 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.}, subject = {Psychologie}, language = {en} } @article{AndreattaMuehlbergerGlotzbachSchoonetal.2013, author = {Andreatta, Marta and M{\"u}hlberger, Andreas and Glotzbach-Schoon, Evelyn and Pauli, Paul}, title = {Pain predictability reverses valence ratings of a relief-associated stimulus}, series = {Front in Systems Neuroscience}, volume = {7}, journal = {Front in Systems Neuroscience}, number = {53}, doi = {10.3389/fnsys.2013.00053}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-129275}, year = {2013}, abstract = {Relief from pain is positively valenced and entails reward-like properties. Notably, stimuli that became associated with pain relief elicit reward-like implicit responses too, but are explicitly evaluated by humans as aversive. Since the unpredictability of pain makes pain more aversive, this study examined the hypotheses that the predictability of pain also modulates the valence of relief-associated stimuli. In two studies, we presented one conditioned stimulus \((_{FORWARD}CS+)\) before a painful unconditioned stimulus (US), another stimulus \((_{BACKWARD}CS+)\) after the painful US, and a third stimulus (CS-) was never associated with the US. In Study 1, \(_{FORWARD}CS+\) predicted half of the USs while the other half was delivered unwarned and followed by \(_{BACKWARD}CS+\). In Study 2, all USs were predicted by \(_{FORWARD}CS+\) and followed by \(_{BACKWARD}CS+\). In Study 1 both \(_{FORWARD}CS+\) and \(_{BACKWARD}CS+\) were rated as negatively valenced and high arousing after conditioning, while \(_{BACKWARD}CS+\) in Study 2 acquired positive valence and low arousal. Startle amplitude was significantly attenuated to \(_{BACKWARD}CS+\) compared to \(_{FORWARD}CS+\) in Study 2, but did not differ among CSs in Study 1. In summary, predictability of aversive events reverses the explicit valence of a relief-associated stimulus.}, language = {en} } @article{PlatteHerbertPaulietal.2013, author = {Platte, Petra and Herbert, Cornelia and Pauli, Paul and Breslin, Paul A. S.}, title = {Oral Perceptions of Fat and Taste Stimuli Are Modulated by Affect and Mood Induction}, series = {PLoS ONE}, journal = {PLoS ONE}, doi = {10.1371/journal.pone.0065006}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-96421}, year = {2013}, abstract = {This study examined the impact of three clinical psychological variables (non-pathological levels of depression and anxiety, as well as experimentally manipulated mood) on fat and taste perception in healthy subjects. After a baseline orosensory evaluation, 'sad', 'happy' and 'neutral' video clips were presented to induce corresponding moods in eighty participants. Following mood manipulation, subjects rated five different oral stimuli, appearing sweet, umami, sour, bitter, fatty, which were delivered at five different concentrations each. Depression levels were assessed with Beck's Depression Inventory (BDI) and anxiety levels were assessed via the Spielberger's STAI-trait and state questionnaire. Overall, subjects were able to track the concentrations of the stimuli correctly, yet depression level affected taste ratings. First, depression scores were positively correlated with sucrose ratings. Second, subjects with depression scores above the sample median rated sucrose and quinine as more intense after mood induction (positive, negative and neutral). Third and most important, the group with enhanced depression scores did not rate low and high fat stimuli differently after positive or negative mood induction, whereas, during baseline or during the non-emotional neutral condition they rated the fat intensity as increasing with concentration. Consistent with others' prior observations we also found that sweet and bitter stimuli at baseline were rated as more intense by participants with higher anxiety scores and that after positive and negative mood induction, citric acid was rated as stronger tasting compared to baseline. The observation that subjects with mild subclinical depression rated low and high fat stimuli similarly when in positive or negative mood is novel and likely has potential implications for unhealthy eating patterns. This deficit may foster unconscious eating of fatty foods in sub-clinical mildly depressed populations.}, language = {en} } @article{EhrenfeldHerbortButz2013, author = {Ehrenfeld, Stephan and Herbort, Oliver and Butz, Martin V.}, title = {Modular neuron-based body estimation: maintaining consistency over different limbs, modalities, and frames of reference}, series = {Frontiers in Computational Neuroscience}, volume = {7}, journal = {Frontiers in Computational Neuroscience}, number = {148}, doi = {10.3389/fncom.2013.00148}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-122253}, year = {2013}, abstract = {This paper addresses the question of how the brain maintains a probabilistic body state estimate over time from a modeling perspective. The neural Modular Modality Frame (nMMF) model simulates such a body state estimation process by continuously integrating redundant, multimodal body state information sources. The body state estimate itself is distributed over separate, but bidirectionally interacting modules. nMMF compares the incoming sensory and present body state information across the interacting modules and fuses the information sources accordingly. At the same time, nMMF enforces body state estimation consistency across the modules. nMMF is able to detect conflicting sensory information and to consequently decrease the influence of implausible sensor sources on the fly. In contrast to the previously published Modular Modality Frame (MMF) model, nMMF offers a biologically plausible neural implementation based on distributed, probabilistic population codes. Besides its neural plausibility, the neural encoding has the advantage of enabling (a) additional probabilistic information flow across the separate body state estimation modules and (b) the representation of arbitrary probability distributions of a body state. The results show that the neural estimates can detect and decrease the impact of false sensory information, can propagate conflicting information across modules, and can improve overall estimation accuracy due to additional module interactions. Even bodily illusions, such as the rubber hand illusion, can be simulated with nMMF. We conclude with an outlook on the potential of modeling human data and of invoking goal-directed behavioral control.}, language = {en} } @article{Meule2013, author = {Meule, Adrian}, title = {Impulsivity and overeating: a closer look at the subscales of the Barratt Impulsiveness Scale}, series = {Frontiers in Psychology}, volume = {4}, journal = {Frontiers in Psychology}, issn = {1664-1078}, doi = {10.3389/fpsyg.2013.00177}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-190497}, year = {2013}, abstract = {No abstract available.}, language = {en} } @article{FoersterPfisterSchmidtsetal.2013, author = {Foerster, Anna and Pfister, Roland and Schmidts, Constantin and Dignath, David and Kunde, Wilfried}, title = {Honesty saves time (and justifications)}, series = {Frontiers in Psychology}, volume = {4}, journal = {Frontiers in Psychology}, issn = {1664-1078}, doi = {10.3389/fpsyg.2013.00473}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-190451}, year = {2013}, abstract = {A commentary on Honesty requires time (and lack of justifications) by Shalvi, S., Eldar, O., and Bereby-Meyer, Y. (2012). Psychol. Sci. 23, 1264-1270. doi: 10.1177/0956797612443835}, language = {en} }