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Grosse-Wentrup M.,Max Planck Institute for Biological Cybernetics | Mattia D.,Neuroelectrical Imaging and BCI Laboratory | Oweiss K.,Michigan State University
Journal of Neural Engineering | Year: 2011

Analyzing neural signals and providing feedback in realtime is one of the core characteristics of a brain-computer interface (BCI). As this feature may be employed to induce neural plasticity, utilizing BCI technology for therapeutic purposes is increasingly gaining popularity in the BCI community. In this paper, we discuss the state-of-the-art of research on this topic, address the principles of and challenges in inducing neural plasticity by means of a BCI, and delineate the problems of study design and outcome evaluation arising in this context. We conclude with a list of open questions and recommendations for future research in this field. © 2011 IOP Publishing Ltd. Source


Daly I.,University of Graz | Billinger M.,University of Graz | Laparra-Hernandez J.,Polytechnic University of Valencia | Aloise F.,Neuroelectrical Imaging and BCI Laboratory | And 5 more authors.
Clinical Neurophysiology | Year: 2013

Objective: Brain-computer interfaces (BCIs) have been proposed as a potential assistive device for individuals with cerebral palsy (CP) to assist with their communication needs. However, it is unclear how well-suited BCIs are to individuals with CP. Therefore, this study aims to investigate to what extent these users are able to gain control of BCIs. Methods: This study is conducted with 14 individuals with CP attempting to control two standard online BCIs (1) based upon sensorimotor rhythm modulations, and (2) based upon steady state visual evoked potentials. Results: Of the 14 users, 8 are able to use one or other of the BCIs, online, with a statistically significant level of accuracy, without prior training. Classification results are driven by neurophysiological activity and not seen to correlate with occurrences of artifacts. However, many of these users' accuracies, while statistically significant, would require either more training or more advanced methods before practical BCI control would be possible. Conclusions: The results indicate that BCIs may be controlled by individuals with CP but that many issues need to be overcome before practical application use may be achieved. Significance: This is the first study to assess the ability of a large group of different individuals with CP to gain control of an online BCI system. The results indicate that six users could control a sensorimotor rhythm BCI and three a steady state visual evoked potential BCI at statistically significant levels of accuracy (SMR accuracies; mean ± STD, 0.821 ± 0.116, SSVEP accuracies; 0.422 ± 0.069). © 2013 International Federation of Clinical Neurophysiology. Source


Kaiser V.,University of Graz | Daly I.,University of Graz | Pichiorri F.,Neuroelectrical Imaging and BCI Laboratory | Mattia D.,Neuroelectrical Imaging and BCI Laboratory | And 2 more authors.
Stroke | Year: 2012

BACKGROUND AND PURPOSE-: New strategies like motor imagery based brain-computer interfaces, which use brain signals such as event-related desynchronization (ERD) or event-related synchronization (ERS) for motor rehabilitation after a stroke, are undergoing investigation. However, little is known about the relationship between ERD and ERS patterns and the degree of stroke impairment. The aim of this work was to clarify this relationship. METHODS-: EEG during motor imagery and execution were measured in 29 patients with first-ever monolateral stroke causing any degree of motor deficit in the upper limb. The strength and laterality of the ERD or ERS patterns were correlated with the scores of the European Stroke Scale, the Medical Research Council, and the Modified Ashworth Scale. RESULTS-: Mean age of the patients was 58±15 years; mean time from the incident was 4±4 months. Stroke lesions were cortical (n=8), subcortical (n=11), or mixed (n=10), attributable to either an ischemic event (n=26) or a hemorrhage (n=3), affecting the right (n=16) or left (n=13) hemisphere. Higher impairment was related to stronger ERD in the unaffected hemisphere and higher spasticity was related to stronger ERD in the affected hemisphere. Both were related to a relatively stronger ERS in the affected hemisphere. CONCLUSION-: The results of this study may have implications for the design of potential poststroke rehabilitation interventions based on brain-computer interface technologies that use neurophysiological signals like ERD or ERS as neural substrates for the mutual interaction between brain and machine and, ultimately, help stroke patients to regain motor control. © 2012 American Heart Association, Inc. Source


De Vico Fallani F.,French Institute of Health and Medical Research | De Vico Fallani F.,Neuroelectrical Imaging and BCI Laboratory | De Vico Fallani F.,University of Rome La Sapienza | Pichiorri F.,Neuroelectrical Imaging and BCI Laboratory | And 5 more authors.
NeuroImage | Year: 2013

In recent years, network analyses have been used to evaluate brain reorganization following stroke. However, many studies have often focused on single topological scales, leading to an incomplete model of how focal brain lesions affect multiple network properties simultaneously and how changes on smaller scales influence those on larger scales. In an EEG-based experiment on the performance of hand motor imagery (MI) in 20 patients with unilateral stroke, we observed that the anatomic lesion affects the functional brain network on multiple levels. In the beta (13-30. Hz) frequency band, the MI of the affected hand (Ahand) elicited a significantly lower smallworldness and local efficiency (Eloc) versus the unaffected hand (Uhand). Notably, the abnormal reduction in Eloc significantly depended on the increase in interhemispheric connectivity, which was in turn determined primarily by the rise of regional connectivity in the parieto-occipital sites of the affected hemisphere. Further, in contrast to the Uhand MI, in which significantly high connectivity was observed for the contralateral sensorimotor regions of the unaffected hemisphere, the regions with increased connectivity during the Ahand MI lay in the frontal and parietal regions of the contralaterally affected hemisphere. Finally, the overall sensorimotor function of our patients, as measured by Fugl-Meyer Assessment (FMA) index, was significantly predicted by the connectivity of their affected hemisphere. These results improve on our understanding of stroke-induced alterations in functional brain networks. © 2013 Elsevier Inc. Source


Riccio A.,Neuroelectrical Imaging and BCI Laboratory | Riccio A.,University of Rome La Sapienza | Simione L.,University of Rome La Sapienza | Simione L.,CNR Institute of Cognitive Sciences and Technologies | And 9 more authors.
Frontiers in Human Neuroscience | Year: 2013

The purpose of this study was to investigate the support of attentional and memory processes in controlling a P300-based brain-computer interface (BCI) in people with amyotrophic lateral sclerosis (ALS). Eight people with ALS performed two behavioral tasks: (i) a rapid serial visual presentation (RSVP) task, screening the temporal filtering capacity and the speed of the update of the attentive filter, and (ii) a change detection task, screening the memory capacity and the spatial filtering capacity. The participants were also asked to perform a P300-based BCI spelling task. By using correlation and regression analyses, we found that only the temporal filtering capacity in the RSVP task was a predictor of both the P300-based BCI accuracy and of the amplitude of the P300 elicited performing the BCI task. We concluded that the ability to keep the attentional filter active during the selection of a target influences performance in BCI control. © 2013 Riccio, Simione, Schettini, Pizzimenti, Inghilleri, Belardinelli, Mattia and Cincotti. Source

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