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PubMed | University of Tübingen, Neuroelectrical Imaging and BCI Laboratory, University of Würzburg and Clinic for Intensive Care
Type: | Journal: International journal of psychophysiology : official journal of the International Organization of Psychophysiology | Year: 2017

Patients who survive injuries to the brain following accidents or diseases often acquire a disorder of consciousness (DOC). Assessment of the state of consciousness in these patients is difficult since they are usually incapable of reproducible motor movements. The application of event-related potentials (ERP) recorded via EEG constitutes one promising approach to complement the assessment of cognitive functions in DOC patients. For these assessments, a hierarchical approach was suggested which means that paradigms aiming at higher order ERPs are only presented if early responses were found. In this study, 19 behaviorally unresponsive or low-responsive DOC patients were presented with three auditory paradigms using passive instructions. The paradigms aimed at eliciting the Mismatch Negativity (MMN) and N400 and were applied at two time points. One oddball paradigm (MMN) and two semantic paradigms (word-pairs: N400 Words; sentences: N400 Sentences) were included. The majority of patients (n=15) did not show any response to the stimulation. In the MMN paradigm, an MMN was identified in two patients, in the N400 Words paradigm, only an N1 was identified in one patient, and in the N400 Sentences paradigm, a late positive complex (LPC) was identified in two patients. These data contradict the hierarchical approach since the LPC was identified in patients who did not exhibit an MMN. They further support the notion that even higher information processing as addressed with the N400 paradigms is preserved in a minority of DOC patients. Thus, in this sample, around 10% of the DOC patients exhibited indicators of preserved consciousness.

Risetti M.,Neuroelectrical Imaging and BCI Laboratory | Formisano R.,Post Coma Unit | Toppi J.,Neuroelectrical Imaging and BCI Laboratory | Toppi J.,University of Rome La Sapienza | And 8 more authors.
Frontiers in Human Neuroscience | Year: 2013

Disorders of Consciousness (DOC) like Vegetative State (VS), and Minimally Conscious State (MCS) are clinical conditions characterized by the absence or intermittent behavioral responsiveness. A neurophysiological monitoring of parameters like Event-Related Potentials (ERPs) could be a first step to follow-up the clinical evolution of these patients during their rehabilitation phase. Eleven patients diagnosed as VS (n = 8) and MCS (n = 3) by means of the JFK Coma Recovery Scale Revised (CRS-R) underwent scalp EEG recordings during the delivery of a 3-stimuli auditory oddball paradigm, which included standard, deviant tones and the subject own name (SON) presented as a novel stimulus, administered under passive and active conditions. Four patients who showed a change in their clinical status as detected by means of the CRS-R (i.e., moved from VS to MCS), were subjected to a second EEG recording session. All patients, but one (anoxic etiology), showed ERP components such as mismatch negativity (MMN) and novelty P300 (nP3) under passive condition. When patients were asked to count the novel stimuli (active condition), the nP3 component displayed a significant increase in amplitude (p = 0.009) and a wider topographical distribution with respect to the passive listening, only in MCS. In 2 out of the 4 patients who underwent a second recording session consistently with their transition from VS to MCS, the nP3 component elicited by passive listening of SON stimuli revealed a significant amplitude increment (p < 0.05). Most relevant, the amplitude of the nP3 component in the active condition, acquired in each patient and in all recording sessions, displayed a significant positive correlation with the total scores (p = 0.004) and with the auditory sub-scores (p < 0.00001) of the CRS-R administered before each EEG recording. As such, the present findings corroborate the value of ERPs monitoring in DOC patients to investigate residual unconscious and conscious cognitive function. © 2013 Risetti, Formisano, Toppi, Quitadamo, Bianchi, Astolfi, Cincotti and Mattia.

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.

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.

PubMed | University of Rome La Sapienza, Neuroelectrical Imaging and BCI Laboratory, Carnegie Mellon University and University of Minnesota
Type: Journal Article | Journal: PloS one | Year: 2016

The coordinated interactions between individuals are fundamental for the success of the activities in some professional categories. We reported on brain-to-brain cooperative interactions between civil pilots during a simulated flight. We demonstrated for the first time how the combination of neuroelectrical hyperscanning and intersubject connectivity could provide indicators sensitive to the humans degree of synchronization under a highly demanding task performed in an ecological environment. Our results showed how intersubject connectivity was able to i) characterize the degree of cooperation between pilots in different phases of the flight, and ii) to highlight the role of specific brain macro areas in cooperative behavior. During the most cooperative flight phases pilots showed, in fact, dense patterns of interbrain connectivity, mainly linking frontal and parietal brain areas. On the contrary, the amount of interbrain connections went close to zero in the non-cooperative phase. The reliability of the interbrain connectivity patterns was verified by means of a baseline condition represented by formal couples, i.e. pilots paired offline for the connectivity analysis but not simultaneously recorded during the flight. Interbrain density was, in fact, significantly higher in real couples with respect to formal couples in the cooperative flight phases. All the achieved results demonstrated how the description of brain networks at the basis of cooperation could effectively benefit from a hyperscanning approach. Interbrain connectivity was, in fact, more informative in the investigation of cooperative behavior with respect to established EEG signal processing methodologies applied at a single subject level.

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.

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.

Aloise F.,Neuroelectrical Imaging and BCI Laboratory | Aloise F.,University of Rome La Sapienza | Schettini F.,Neuroelectrical Imaging and BCI Laboratory | Schettini F.,University of Rome La Sapienza | And 6 more authors.
Journal of Neural Engineering | Year: 2012

This off-line study aims to assess the performance of five classifiers commonly used in the brain-computer interface (BCI) community, when applied to a gaze-independent P300-based BCI. In particular, we compared the results of four linear classifiers and one nonlinear: Fisher's linear discriminant analysis (LDA), stepwise linear discriminant analysis (SWLDA), Bayesian linear discriminant analysis (BLDA), linear support vector machine (LSVM) and Gaussian supported vector machine (GSVM). Moreover, different values for the decimation of the training dataset were tested. The results were evaluated both in terms of accuracy and written symbol rate with the data of 19 healthy subjects. No significant differences among the considered classifiers were found. The optimal decimation factor spanned a range from 3 to 24 (12 to 94 ms long bins). Nevertheless, performance on individually optimized classification parameters is not significantly different from a classification with general parameters (i.e. using an LDA classifier, about 48 ms long bins). © 2012 IOP Publishing Ltd.

Riccio A.,Neuroelectrical Imaging and BCI Laboratory | Riccio A.,University of Rome La Sapienza | Mattia D.,Neuroelectrical Imaging and BCI Laboratory | Simione L.,University of Rome La Sapienza | And 6 more authors.
Journal of Neural Engineering | Year: 2012

The present review systematically examines the literature reporting gaze independent interaction modalities in non-invasive brain-computer interfaces (BCIs) for communication. BCIs measure signals related to specific brain activity and translate them into device control signals. This technology can be used to provide users with severe motor disability (e.g. late stage amyotrophic lateral sclerosis (ALS); acquired brain injury) with an assistive device that does not rely on muscular contraction. Most of the studies on BCIs explored mental tasks and paradigms using visual modality. Considering that in ALS patients the oculomotor control can deteriorate and also other potential users could have impaired visual function, tactile and auditory modalities have been investigated over the past years to seek alternative BCI systems which are independent from vision. In addition, various attentional mechanisms, such as covert attention and feature-directed attention, have been investigated to develop gaze independent visual-based BCI paradigms. Three areas of research were considered in the present review: (i) auditory BCIs, (ii) tactile BCIs and (iii) independent visual BCIs. Out of a total of 130 search results, 34 articles were selected on the basis of pre-defined exclusion criteria. Thirteen articles dealt with independent visual BCIs, 15 reported on auditory BCIs and the last six on tactile BCIs, respectively. From the review of the available literature, it can be concluded that a crucial point is represented by the trade-off between BCI systems/paradigms with high accuracy and speed, but highly demanding in terms of attention and memory load, and systems requiring lower cognitive effort but with a limited amount of communicable information. These issues should be considered as priorities to be explored in future studies to meet users' requirements in a real-life scenario. © 2012 IOP Publishing Ltd.

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.

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