Niels Birbaumer

University of Tuebingen, Tübingen, Baden-Württemberg, Germany

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Publications (448)1538.65 Total impact

  • Ander Ramos-Murguialday, Niels Birbaumer
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    ABSTRACT: Non-invasive brain-computer-interfaces (BCI) coupled with prosthetic devices were recently introduced in the rehabilitation of chronic stroke and other disorders of the motor system. These BCI systems and motor rehabilitation in general involve several motor tasks for training. This study investigates the neurophysiological bases of an EEG-oscillations-driven BCI combined with a neuroprosthetic device in order to define the specific oscillatory signature of the BCI-task. We recorded EEG while 9 healthy participants performed five different motor tasks consisting of closing and opening of the hand: 1) motor imagery without any external feedback and without overt hand movement, 2) motor imagery which moves the orthosis proportional to the produced brain oscillation change with online proprioceptive and visual feedback of the hand moving through a neuroprosthetic device (BCI-condition), 3) passive and 4) active movement of the hand with feedback (seeing and feeling the hand moving) and 5) rest. We analyzed brain activity during the 5 conditions using time-frequency domain bootstrap based statistical comparisons and Morlet transforms. Activity during rest condition was used as reference. Significant contralateral and ipsilateral event related desynchronization of sensorimotor rhythm was present during all motor tasks, largest in contralateral-post-central, medio-central and ipsilateral-pre-central areas identifying the ipsilateral pre-central cortex as an integral part of motor regulation. Changes in task specific frequency power when compared to rest were similar between motor tasks and only significant differences in the time course and some narrow specific frequency bands were observed between motor tasks. We identified EEG features representing proprioception, active intention and passive involvement differentiating brain oscillations during motor tasks that could substantially support the design of novel motor BCI-based rehabilitation therapies. The BCI task induced significantly different brain activity compared to the other motor tasks indicating neural processes unique to the use of body actuators control in a BCI-context. Copyright © 2013, Journal of Neurophysiology.
    Journal of Neurophysiology 03/2015; DOI:10.1152/jn.00467.2013 · 3.04 Impact Factor
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    ABSTRACT: Psychopathic individuals are characterized by impaired affective processing, impulsivity, sensation-seeking, poor planning skills and heightened aggressiveness with poor self-regulation. Based on brain self-regulation studies using neurofeedback of Slow Cortical Potentials (SCPs) in disorders associated with a dysregulation of cortical activity thresholds and evidence of deficient cortical functioning in psychopathy, a neurobiological approach seems to be promising in the treatment of psychopathy. The results of our intensive brain regulation intervention demonstrate, that psychopathic offenders are able to gain control of their brain excitability over fronto-central brain areas. After SCP self-regulation training, we observed reduced aggression, impulsivity and behavioral approach tendencies, as well as improvements in behavioral-inhibition and increased cortical sensitivity for error-processing. This study demonstrates improvements on the neurophysiological, behavioral and subjective level in severe psychopathic offenders after SCP-neurofeedback training and could constitute a novel neurobiologically-based treatment for a seemingly change-resistant group of criminal psychopaths.
    Scientific Reports 03/2015; 5. DOI:10.1038/srep09426 · 5.08 Impact Factor
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    ABSTRACT: Task performance depends on ongoing brain activity which can be influenced by attention, arousal, or motivation. However, such modulating factors of cognitive efficiency are unspecific, can be difficult to control, and are not suitable to facilitate neural processing in a regionally specific manner. Here, we non-pharmacologically manipulated regionally specific brain activity using technically sophisticated real-time fMRI neurofeedback. This was accomplished by training participants to simultaneously control ongoing brain activity in circumscribed motor and memory-related brain areas, namely the supplementary motor area and the parahippocampal cortex. We found that learned voluntary control over these functionally distinct brain areas caused functionally specific behavioral effects, i.e. shortening of motor reaction times and specific interference with memory encoding. The neurofeedback approach goes beyond improving cognitive efficiency by unspecific psychological factors such as attention, arousal, or motivation. It allows for directly manipulating sustained activity of task-relevant brain regions in order to yield specific behavioral or cognitive effects. Copyright © 2015. Published by Elsevier B.V.
    Biological psychology 03/2015; 220. DOI:10.1016/j.biopsycho.2015.03.009 · 3.47 Impact Factor
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    ABSTRACT: Background. Eye trackers are widely used among people with amyotrophic lateral sclerosis, and their benefits to quality of life have been previously shown. On the contrary, Brain-computer interfaces (BCIs) are still quite a novel technology, which also serves as an access technology for people with severe motor impairment. Objective. To compare a visual P300-based BCI and an eye tracker in terms of information transfer rate (ITR), usability, and cognitive workload in users with motor impairments. Methods. Each participant performed 3 spelling tasks, over 4 total sessions, using an Internet browser, which was controlled by a spelling interface that was suitable for use with either the BCI or the eye tracker. At the end of each session, participants evaluated usability and cognitive workload of the system. Results. ITR and System Usability Scale (SUS) score were higher for the eye tracker (Wilcoxon signed-rank test: ITR T = 9, P = .016; SUS T = 12.50, P = .035). Cognitive workload was higher for the BCI (T = 4; P = .003). Conclusions. Although BCIs could be potentially useful for people with severe physical disabilities, we showed that the usability of BCIs based on the visual P300 remains inferior to eye tracking. We suggest that future research on visual BCIs should use eye tracking-based control as a comparison to evaluate performance or focus on nonvisual paradigms for persons who have lost gaze control. © The Author(s) 2015.
    Neurorehabilitation and neural repair 03/2015; DOI:10.1177/1545968315575611 · 4.62 Impact Factor
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    ABSTRACT: The brain-computer interface (BCI) field has grown dramatically over the past few years, but there are still no coordinated efforts to ensure efficient communication and collaboration among key stakeholders. The European Commission (EC) has recently renewed their efforts to establish such a coordination effort by funding a coordination and support action for the BCI community called ‘BNCI Horizon 2020’ after the ‘Future BNCI’ project. Major goals of this new project include developing a roadmap for the next decade and beyond, encouraging discussion and collaboration within the BCI community, fostering communication with the general public, and the foundation of an international BCI Society. We present a short overview of current and past EU-funded BCI projects and provide evidence of a growing research and industrial community. Efficient communication also entails the establishment of clear terminology, which is a major goal of BNCI Horizon 2020. To this end, we give a brief overview of current BCI-related terms and definitions. A major networking activity in the project was the BNCI Horizon 2020 Retreat in Hallstatt, Austria. Over 60 experts participated in this event to discuss the future of the BCI field in a series of plenary talks, targeted discussions, and parallel focus sessions. A follow-up event was the EU BCI Day at the 6th International Brain-Computer Interface Conference in Graz, Austria. This networking event included plenary talks by eight companies and representatives from all seven ongoing EU research projects, poster presentations, demos, and discussions. Another goal of BNCI Horizon 2020 is the foundation of an official BCI Society. In this article, we summarize the current status of this process. Finally, we present visions for future BCI applications developed within BNCI Horizon 2020 using input from external BCI experts as well. We identify common themes and conclude with six exemplary use cases.
    02/2015; DOI:10.1080/2326263X.2015.1008956
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    ABSTRACT: Objective Stroke is a leading cause of long-term motor disability. Stroke patients with severe hand weakness do not profit from rehabilitative treatments. Recently, brain-controlled robotics and sequential functional electrical stimulation allowed some improvement. However, for such therapies to succeed, it is required to decode patients' intentions for different arm movements. Here, we evaluated whether residual muscle activity could be used to predict movements from paralyzed joints in severely impaired chronic stroke patients. Methods Muscle activity was recorded with surface-electromyography (EMG) in 41 patients, with severe hand weakness (Fugl-Meyer Assessment [FMA] hand subscores of 2.93 ± 2.7), in order to decode their intention to perform six different motions of the affected arm, required for voluntary muscle activity and to control neuroprostheses. Decoding of paretic and nonparetic muscle activity was performed using a feed-forward neural network classifier. The contribution of each muscle to the intended movement was determined. Results Decoding of up to six arm movements was accurate (>65%) in more than 97% of nonparetic and 46% of paretic muscles. Interpretation These results demonstrate that some level of neuronal innervation to the paretic muscle remains preserved and can be used to implement neurorehabilitative treatments in 46% of patients with severe paralysis and extensive cortical and/or subcortical lesions. Such decoding may allow these patients for the first time after stroke to control different motions of arm prostheses through muscle-triggered rehabilitative treatments.
    01/2015; 7. DOI:10.1002/acn3.122
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    ABSTRACT: The loss of hand function can result in severe physical and psychosocial impairment. Thus, compensation of a lost hand function using assistive robotics that can be operated in daily life is very desirable. However, versatile, intuitive, and reliable control of assistive robotics is still an unsolved challenge. Here, we introduce a novel brain/neural-computer interaction (BNCI) system that integrates electroencephalography (EEG) and electrooculography (EOG) to improve control of assistive robotics in daily life environments. To evaluate the applicability and performance of this hybrid approach, five healthy volunteers (HV) (four men, average age 26.5±3.8 years) and a 34-year-old patient with complete finger paralysis due to a brachial plexus injury (BPI) used EEG (condition 1) and EEG/EOG (condition 2) to control grasping motions of a hand exoskeleton. All participants were able to control the BNCI system (BNCI control performance HV: 70.24±16.71%, BPI: 65.93±24.27%), but inclusion of EOG significantly improved performance across all participants (HV: 80.65±11.28, BPI: 76.03±18.32%). This suggests that hybrid BNCI systems can achieve substantially better control over assistive devices, e.g., a hand exoskeleton, than systems using brain signals alone and thus may increase applicability of brain-controlled assistive devices in daily life environments.
    Biomedizinische Technik/Biomedical Engineering 12/2014; DOI:10.1515/bmt-2014-0126 · 2.43 Impact Factor
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    ABSTRACT: Introduction: Different techniques for neurofeedback of voluntary brain activations are currently being explored for clinical application in brain disorders. One of the most frequently used approaches is the self-regulation of oscillatory signals recorded with electroencephalography (EEG). Many patients are, however, unable to achieve sufficient voluntary control of brain activity. This could be due to the specific anatomical and physiological changes of the patient’s brain after the lesion, as well as to methodological issues related to the technique chosen for recording brain signals. Methods: A patient with an extended ischemic lesion of the cortex did not gain volitional control of sensorimotor oscillations when using a standard EEG-based approach. We provided him with neurofeedback of his brain activity from the epidural space by electrocorticography (ECoG). Results: Ipsilesional epidural recordings of field potentials facilitated self-regulation of brain oscillations in an online closed-loop paradigm and allowed reliable neurofeedback training for a period of 4 weeks. Conclusion: Epidural implants may decode and train brain activity even when the cortical physiology is distorted following severe brain injury. Such practice would allow for reinforcement learning of preserved neural networks and may well provide restorative tools for those patients who are severely afflicted.
    Frontiers in Behavioral Neuroscience 12/2014; 8. DOI:10.3389/fnbeh.2014.00429 · 4.16 Impact Factor
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    ABSTRACT: Stroke is among the leading causes of long-term disabilities leaving an increasing number of people with cognitive, affective and motor impairments depending on assistance in their daily life. While function after stroke can significantly improve in the first weeks and months, further recovery is often slow or non-existent in the more severe cases encompassing 30-50% of all stroke victims. The neurobiological mechanisms underlying recovery in those patients are incompletely understood. However, recent studies demonstrated the brain's remarkable capacity for functional and structural plasticity and recovery even in severe chronic stroke. As all established rehabilitation strategies require some remaining motor function, there is currently no standardized and accepted treatment for patients with complete chronic muscle paralysis. The development of brain-machine interfaces (BMIs) that translate brain activity into control signals of computers or external devices provides two new strategies to overcome stroke-related motor paralysis. First, BMIs can establish continuous high-dimensional brain-control of robotic devices or functional electric stimulation (FES) to assist in daily life activities (assistive BMI). Second, BMIs could facilitate neuroplasticity, thus enhancing motor learning and motor recovery (rehabilitative BMI). Advances in sensor technology, development of non-invasive and implantable wireless BMI-systems and their combination with brain stimulation, along with evidence for BMI system's clinical efficacy suggest that BMI-related strategies will play an increasing role in neurorehabilitation of stroke. Copyright © 2014. Published by Elsevier Inc.
    Neurobiology of Disease 12/2014; DOI:10.1016/j.nbd.2014.11.025 · 5.20 Impact Factor
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    ABSTRACT: The combination of Brain-Computer Interface (BCI) technology, allowing online monitoring and decoding of brain activity, with virtual and mixed reality (MR) systems may help to shape and guide implicit and explicit learning using ecological scenarios. Real-time information of ongoing brain states acquired through BCI might be exploited for controlling data presentation in virtual environments. Brain states discrimination during mixed reality experience is thus critical for adapting specific data features to contingent brain activity. In this study we recorded electroencephalographic (EEG) data while participants experienced MR scenarios implemented through the eXperience Induction Machine (XIM). The XIM is a novel framework modeling the integration of a sensing system that evaluates and measures physiological and psychological states with a number of actuators and effectors that coherently reacts to the user's actions. We then assessed continuous EEG-based discrimination of spatial navigation, reading and calculation performed in MR, using linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Dynamic single trial classification showed high accuracy of LDA and SVM classifiers in detecting multiple brain states as well as in differentiating between high and low mental workload, using a 5 s time-window shifting every 200 ms. Our results indicate overall better performance of LDA with respect to SVM and suggest applicability of our approach in a BCI-controlled MR scenario. Ultimately, successful prediction of brain states might be used to drive adaptation of data representation in order to boost information processing in MR.
    Frontiers in Behavioral Neuroscience 11/2014; 8(415). DOI:10.3389/fnbeh.2014.00415 · 4.16 Impact Factor
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    ABSTRACT: (1) compared with amateurs and young elite, expert table tennis players are characterized by enhanced cortical activation in the motor and fronto-parietal cortex during motor imagery in response to table tennis videos; (2) in elite athletes, world rank points are associated with stronger cortical activation. To this aim, electroencephalographic data were recorded in 14 expert, 15 amateur and 15 young elite right-handed table tennis players. All subjects watched videos of a serve and imagined themselves responding with a specific table tennis stroke. With reference to a baseline period, power decrease/increase of the sensorimotor rhythm (SMR) during the pretask- and task period indexed the cortical activation/deactivation (event-related desynchronization/synchronization, ERD/ERS). Regarding hypothesis (1), 8-10 Hz SMR ERD was stronger in elite athletes than in amateurs with an intermediate ERD in young elite athletes in the motor cortex. Regarding hypothesis (2), there was no correlation between ERD/ERS in the motor cortex and world rank points in elite experts, but a weaker ERD in the fronto-parietal cortex was associated with higher world rank points. These results suggest that motor skill in table tennis is associated with focused excitability of the motor cortex during reaction, movement planning and execution with high attentional demands. Among elite experts, less activation of the fronto-parietal attention network may be necessary to become a world champion.
    Frontiers in Behavioral Neuroscience 10/2014; 8:370. DOI:10.3389/fnbeh.2014.00370 · 4.16 Impact Factor
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    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, ~7 and ~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).
    Frontiers in Human Neuroscience 10/2014; 8:861. DOI:10.3389/fnhum.2014.00861 · 2.90 Impact Factor
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    ABSTRACT: This pilot study aimed to explore whether criminal psychopaths can learn volitional regulation of the left anterior insula with real-time fMRI neurofeedback. Our previous studies with healthy volunteers showed that learned control of the blood oxygenation-level dependent (BOLD) signal was specific to the target region, and not a result of general arousal and global unspecific brain activation, and also that successful regulation modulates emotional responses, specifically to aversive picture stimuli but not neutral stimuli. In this pilot study, four criminal psychopaths were trained to regulate the anterior insula by employing negative emotional imageries taken from previous episodes in their lives, in conjunction with contingent feedback. Only one out of the four participants learned to increase the percent differential BOLD in the up-regulation condition across training runs. Subjects with higher Psychopathic Checklist-Revised (PCL:SV) scores were less able to increase the BOLD signal in the anterior insula than their lower PCL:SV counterparts. We investigated functional connectivity changes in the emotional network due to learned regulation of the successful participant, by employing multivariate Granger Causality Modeling (GCM). Learning to up-regulate the left anterior insula not only increased the number of connections (causal density) in the emotional network in the single successful participant but also increased the difference between the number of outgoing and incoming connections (causal flow) of the left insula. This pilot study shows modest potential for training psychopathic individuals to learn to control brain activity in the anterior insula.
    Frontiers in Behavioral Neuroscience 10/2014; 8:344. DOI:10.3389/fnbeh.2014.00344 · 4.16 Impact Factor
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    ABSTRACT: This study contrasted the neurological correlates of calendar calculating (CC) between those individuals with autism spectrum disorder (ASD) and typically developing individuals. CC is the ability to correctly and quickly state the day of the week of a given date. Using magnetoencephalography (MEG), we presented 126 calendar tasks with dates of the present, past, and future. Event-related magnetic fields (ERF) of 3000 ms duration and brain activation patterns were compared in three savant calendar calculators with ASD (ASDCC) and three typically developing calendar calculators (TYPCC). ASDCC outperformed TYPCC in correct responses, but not in answering speed. Comparing amplitudes of their ERFs, there was a main effect of group between 1000 and 3000 ms, but no further effects of hemisphere or sensor location. We conducted CLARA source analysis across the entire CC period in each individual. Both ASDCC and TYPCC exhibited activation maxima in prefrontal areas including the insulae and the left superior temporal gyrus. This is in accordance with verbal fact retrieval and working memory as well as monitoring and coordination processes. In ASDCC, additional activation sites at the right superior occipital gyrus, the right precuneus, and the right putamen point to visual-spatial strategies and are in line with the preference of autistic individuals for engaging posterior regions relatively more strongly in various reasoning and problem solving tasks.
    Brain and Cognition 10/2014; 90:157–164. DOI:10.1016/j.bandc.2014.07.003 · 2.68 Impact Factor
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    ABSTRACT: Background: Recent experimental evidence has indicated that the motor system coordinates muscle activations through a linear combination of muscle synergies that are specified at the spinal or brainstem networks level. After stroke upper limb impairment is characterized by abnormal patterns of muscle activations or synergies. Objective: This study aimed at characterizing the muscle synergies in severely affected chronic stroke patients. Furthermore, the influence of integrity of the sensorimotor cortex on synergy modularity and its relation with motor impairment was evaluated. Methods: Surface electromyography from 33 severely impaired chronic stroke patients was recorded during 6 bilateral movements. Muscle synergies were extracted and synergy patterns were correlated with motor impairment scales. Results: Muscle synergies extracted revealed different physiological patterns dependent on the preservation of the sensorimotor cortex. Patients without intact sensorimotor cortex showed a high preservation of muscle synergies. On the contrary, patients with intact sensorimotor cortex showed poorer muscle synergies preservation and an increase in new generated synergies. Furthermore, the preservation of muscle synergies correlated positively with hand functionality in patients with intact sensorimotor cortex and subcortical lesions only. Conclusion: Our results indicate that severely paralyzed chronic stroke patient with intact sensorimotor cortex might sculpt new synergy patterns as a response to maladaptive compensatory strategies.
    Frontiers in Human Neuroscience 09/2014; 8:744. DOI:10.3389/fnhum.2014.00744 · 2.90 Impact Factor
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    ABSTRACT: In order to enable communication through a brain-computer interface (BCI), it is necessary to discriminate between distinct brain responses. As a first step, we probed the possibility to discriminate between affirmative (“yes”) and negative (“no”) responses using a semantic classical conditioning paradigm, within an fMRI setting. Subjects were presented with congruent and incongruent word-pairs as conditioned stimuli (CS), respectively eliciting affirmative and negative responses. Incongruent word-pairs were associated to an unpleasant unconditioned stimulus (scream, US1) and congruent word-pairs were associated to a pleasant unconditioned stimulus (baby-laughter, US2), in order to elicit emotional conditioned responses (CR). The aim was to discriminate between affirmative and negative responses, enabled by their association with the positive and negative affective stimuli. In the late acquisition phase, when the US were not present anymore, there was a strong significant differential activation for incongruent and congruent word-pairs in a cluster comprising the left insula and the inferior frontal triangularis. This association was not found in the habituation phase. These results suggest that the difference in affirmative and negative brain responses was established as an effect of conditioning, allowing to further investigate the possibility of using this paradigm for a binary choice BCI.
    Frontiers in Behavioral Neuroscience 07/2014; 8. DOI:10.3389/fnbeh.2014.00247 · 4.16 Impact Factor
  • Sunjung Kim, Niels Birbaumer
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    ABSTRACT: Purpose of review The aim of this review is to provide a critical overview of recent research in the field of neuroscientific and clinical application of real-time functional MRI neurofeedback (rtfMRI-nf). Recent findings RtfMRI-nf allows self-regulating activity in circumscribed brain areas and brain systems. Furthermore, the learned regulation of brain activity has an influence on specific behaviors organized by the regulated brain regions. Patients with mental disorders show abnormal activity in certain regions, and simultaneous control of these regions using rtfMRI-nf may affect the symptoms of related behavioral disorders. Summary The promising results in clinical application indicate that rtfMRI-nf and other metabolic neurofeedback, such as near-infrared spectroscopy, might become a potential therapeutic tool. Further research is still required to examine whether rtfMRI-nf is a useful tool for psychiatry because there is still lack of knowledge about the neural function of certain brain systems and about neuronal markers for specific mental illnesses.
    Current Opinion in Psychiatry 07/2014; 27(5). DOI:10.1097/YCO.0000000000000087 · 3.55 Impact Factor
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    ABSTRACT: In this paper, we present an experimental approach to design systems sensitive to emotion. We describe a system for the detection of emotional states based on physiological signals and an application use case utilizing the detected emotional state. The application is an emotion management system to be used for the support in the improvement of life conditions of users suffering from cerebral palsy (CP). The system presented here combines effectively biofeedback sensors and a set of software algorithms to detect the current emotional state of the user and to react to them appropriately.
    Computers Helping People with Special Needs, Paris France; 07/2014
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    ABSTRACT: In amyotrophic lateral sclerosis (ALS), cognition is affected. Cortical atrophy in frontal and temporal areas has been associated with the cognitive profile of patients. Additionally, reduced metabolic turnover and regional cerebral blood flow in frontal areas indicative of reduced neural activity have been reported for ALS. We hypothesize that functional connectivity in non-task associated functional default mode network (DMN) is associated with cognitive profile and white matter integrity. This study focused on specific cognitive tasks known to be impaired in ALS such as verbal fluency and attention, and the relationship with functional connectivity in the DMN and white matter integrity. Nine patients and 11 controls were measured with an extensive neuropsychological battery. Resting-state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data were acquired. Results showed that ALS patients performed significantly worse in attention and verbal fluency task. Patients showed increased functional connectivity in parahippocampal and parietal areas of the non-task associated DMN compared to controls. The more pronounced the cognitive deficits, the stronger the increase in functional connectivity in those areas. White matter integrity was reduced in frontal areas in the patients. In conclusion, increased connectivity in the DMN in parahippocampal and parietal areas might represent recruitment of accessory brain regions to compensate for dysfunctional frontal networks.
    Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration 05/2014; DOI:10.3109/21678421.2014.911914 · 2.59 Impact Factor
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    ABSTRACT: Introduction: Prostheses for upper-limb amputees are currently controlled by either myoelectric or peripheral neural signals. Performance and dexterity of these devices is still limited, particularly when it comes to controlling hand function. Movement-related brain activity might serve as a complementary bio-signal for motor control of hand prosthesis. Methods: We introduced a methodology to implant a cortical interface without direct exposure of the brain surface in an upper-limb amputee. This bi-directional interface enabled us to explore the cortical physiology following long-term transhumeral amputation. In addition, we investigated neurofeedback of electrocorticographic brain activity related to the patient's motor imagery to open his missing hand, i.e., phantom hand movement, for real-time control of a virtual hand prosthesis. Results: Both event-related brain activity and cortical stimulation revealed mutually overlapping cortical representations of the phantom hand. Phantom hand movements could be robustly classified and the patient required only three training sessions to gain reliable control of the virtual hand prosthesis in an online closed-loop paradigm that discriminated between hand opening and rest. Conclusion: Epidural implants may constitute a powerful and safe alternative communication pathway between the brain and external devices for upper-limb amputees, thereby facilitating the integrated use of different signal sources for more intuitive and specific control of multi-functional devices in clinical use.
    Frontiers in Human Neuroscience 05/2014; 8:285. DOI:10.3389/fnhum.2014.00285 · 2.90 Impact Factor

Publication Stats

20k Citations
1,538.65 Total Impact Points


  • 1977–2015
    • University of Tuebingen
      • • Institute of Medical Psychology and Behavioral Neurobiology
      • • Department of Psychology
      Tübingen, Baden-Württemberg, Germany
  • 2013–2014
    • Fondazione Ospedale San Camillo, Venezia
      Venetia, Veneto, Italy
  • 2011–2013
    • Ospedale di San Raffaele Istituto di Ricovero e Cura a Carattere Scientifico
      Milano, Lombardy, Italy
    • Institut Philippe-Pinel de Montréal
      Montréal, Quebec, Canada
  • 2012
    • Universitätsklinikum Tübingen
      • Department of Otolaryngology, Head and Neck Surgery
      Tübingen, Baden-Württemberg, Germany
    • Boca Raton Regional Hospital
      Boca Raton, Florida, United States
  • 2007–2011
    • National Institutes of Health
      • National Institute of Neurological Disorders and Stroke (NINDS)
      Bethesda, MD, United States
    • University of Arkansas for Medical Sciences
      Little Rock, Arkansas, United States
  • 2010
    • University of Zaragoza
      Caesaraugusta, Aragon, Spain
  • 2008
    • University of Wuerzburg
      Würzburg, Bavaria, Germany
  • 1988–2007
    • Pennsylvania State University
      • Department of Psychology
      State College, PA, United States
  • 2006
    • Max Planck Institute for Biological Cybernetics
      Tübingen, Baden-Württemberg, Germany
    • Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.
      München, Bavaria, Germany
    • University of Bonn
      Bonn, North Rhine-Westphalia, Germany
  • 2002–2006
    • Università degli Studi di Trento
      Trient, Trentino-Alto Adige, Italy
  • 2005
    • University of Colorado at Boulder
      Boulder, Colorado, United States
  • 1998
    • Humboldt-Universität zu Berlin
      Berlín, Berlin, Germany
  • 1994–1998
    • University of Padova
      • Department of General Psychology
      Padua, Veneto, Italy
  • 1997
    • Universität Konstanz
      • Department of Psychology
      Constance, Baden-Württemberg, Germany
  • 1992
    • Università degli Studi del Sannio
      Benevento, Campania, Italy
  • 1985
    • Yale University
      New Haven, Connecticut, United States
  • 1984
    • Universität Ulm
      • Institute of Clinical and Biological Psychology
      Ulm, Baden-Württemberg, Germany