<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Murguialday, A Ramos</style></author><author><style face="normal" font="default" size="100%">Jeremy Jeremy Hill</style></author><author><style face="normal" font="default" size="100%">Bensch, M</style></author><author><style face="normal" font="default" size="100%">Martens, S M M</style></author><author><style face="normal" font="default" size="100%">S Halder</style></author><author><style face="normal" font="default" size="100%">Nijboer, F</style></author><author><style face="normal" font="default" size="100%">Schoelkopf, Bernhard</style></author><author><style face="normal" font="default" size="100%">Niels Birbaumer</style></author><author><style face="normal" font="default" size="100%">Gharabaghi, A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Transition from the locked in to the completely locked-in state: a physiological analysis.</style></title><secondary-title><style face="normal" font="default" size="100%">Clin Neurophysiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Clin Neurophysiol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Amyotrophic Lateral Sclerosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Area Under Curve</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain</style></keyword><keyword><style  face="normal" font="default" size="100%">Communication Aids for Disabled</style></keyword><keyword><style  face="normal" font="default" size="100%">Disease Progression</style></keyword><keyword><style  face="normal" font="default" size="100%">Electroencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Electromyography</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Processing, Computer-Assisted</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2011</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/20888292</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">122</style></volume><pages><style face="normal" font="default" size="100%">925-33</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;h4 style=&quot;font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;&quot;&gt;OBJECTIVE:&amp;nbsp;&lt;/h4&gt;
&lt;p style=&quot;margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;To clarify the physiological and behavioral boundaries between locked-in (LIS) and the completely locked-in state (CLIS) (no voluntary eye movements, no communication possible) through electrophysiological data and to secure&amp;nbsp;&lt;span class=&quot;highlight&quot;&gt;brain-computer-interface&lt;/span&gt;&amp;nbsp;(&lt;span class=&quot;highlight&quot;&gt;BCI&lt;/span&gt;) communication.&lt;/p&gt;
&lt;h4 style=&quot;font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;&quot;&gt;METHODS:&amp;nbsp;&lt;/h4&gt;
&lt;p style=&quot;margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;Electromyography from facial muscles, external anal sphincter (EAS), electrooculography and electrocorticographic data during different psychophysiological tests were acquired to define electrophysiological differences in an amyotrophic lateral sclerosis (ALS) patient with an intracranially implanted grid of 112 electrodes for nine months while the patient passed from the LIS to the CLIS.&lt;/p&gt;
&lt;h4 style=&quot;font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;&quot;&gt;RESULTS:&amp;nbsp;&lt;/h4&gt;
&lt;p style=&quot;margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;At the very end of the LIS there was no facial muscle activity, nor external anal sphincter but eye control. Eye movements were slow and lasted for short periods only. During CLIS event related&amp;nbsp;&lt;span class=&quot;highlight&quot;&gt;brain&lt;/span&gt;potentials (ERP) to passive limb movements and auditory stimuli were recorded, vibrotactile stimulation of different body parts resulted in no ERP response.&lt;/p&gt;
&lt;h4 style=&quot;font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;&quot;&gt;CONCLUSIONS:&amp;nbsp;&lt;/h4&gt;
&lt;p style=&quot;margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;The results presented contradict the commonly accepted assumption that the EAS is the last remaining muscle under voluntary control and demonstrate complete loss of eye movements in CLIS. The eye muscle was shown to be the last muscle group under voluntary control. The findings suggest ALS as a multisystem disorder, even affecting afferent sensory pathways.&lt;/p&gt;
&lt;h4 style=&quot;font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;&quot;&gt;SIGNIFICANCE:&amp;nbsp;&lt;/h4&gt;
&lt;p style=&quot;margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;Auditory and proprioceptive&amp;nbsp;&lt;span class=&quot;highlight&quot;&gt;brain-computer-interface&lt;/span&gt;&amp;nbsp;(&lt;span class=&quot;highlight&quot;&gt;BCI&lt;/span&gt;) systems are the only remaining communication channels in CLIS.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hinterberger, T.</style></author><author><style face="normal" font="default" size="100%">Widman, Guido</style></author><author><style face="normal" font="default" size="100%">Lal, T.N</style></author><author><style face="normal" font="default" size="100%">Jeremy Jeremy Hill</style></author><author><style face="normal" font="default" size="100%">Tangermann, Michael</style></author><author><style face="normal" font="default" size="100%">Rosenstiel, W.</style></author><author><style face="normal" font="default" size="100%">Schölkopf, B</style></author><author><style face="normal" font="default" size="100%">Elger, Christian</style></author><author><style face="normal" font="default" size="100%">Niels Birbaumer</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Voluntary brain regulation and communication with electrocorticogram signals.</style></title><secondary-title><style face="normal" font="default" size="100%">Epilepsy Behav</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Epilepsy Behav</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Biofeedback, Psychology</style></keyword><keyword><style  face="normal" font="default" size="100%">Cerebral Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Communication Aids for Disabled</style></keyword><keyword><style  face="normal" font="default" size="100%">Dominance, Cerebral</style></keyword><keyword><style  face="normal" font="default" size="100%">Electroencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Epilepsies, Partial</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Imagination</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Motor Activity</style></keyword><keyword><style  face="normal" font="default" size="100%">Motor Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Processing, Computer-Assisted</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Somatosensory Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Theta Rhythm</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword><keyword><style  face="normal" font="default" size="100%">Writing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/18495541</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">300-6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;Brain-computer interfaces&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;&amp;nbsp;(BCIs) can be used for communication in writing without muscular activity or for learning to control seizures by voluntary regulation of&amp;nbsp;&lt;/span&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;brain&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;&amp;nbsp;signals such as the electroencephalogram (EEG). Three of five patients with epilepsy were able to spell their names with electrocorticogram (ECoG) signals derived from motor-related areas within only one or two training sessions. Imagery of finger or tongue movements was classified with support-vector classification of autoregressive coefficients derived from the ECoG signals. After training of the classifier, binary classification responses were used to select letters from a&amp;nbsp;&lt;/span&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;computer&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;-generated menu. Offline analysis showed increased theta activity in the unsuccessful patients, whereas the successful patients exhibited dominant sensorimotor rhythms that they could control. The high spatial resolution and increased signal-to-noise ratio in ECoG signals, combined with short training periods, may offer an alternative for communication in complete paralysis, locked-in syndrome, and motor restoration.&lt;/span&gt;&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mellinger, Jürgen</style></author><author><style face="normal" font="default" size="100%">Gerwin Schalk</style></author><author><style face="normal" font="default" size="100%">Christoph Braun</style></author><author><style face="normal" font="default" size="100%">Preissl, Hubert</style></author><author><style face="normal" font="default" size="100%">Rosenstiel, W.</style></author><author><style face="normal" font="default" size="100%">Niels Birbaumer</style></author><author><style face="normal" font="default" size="100%">Kübler, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An MEG-based brain-computer interface (BCI).</style></title><secondary-title><style face="normal" font="default" size="100%">Neuroimage</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Neuroimage</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Artifacts</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain</style></keyword><keyword><style  face="normal" font="default" size="100%">Electroencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Electromagnetic Fields</style></keyword><keyword><style  face="normal" font="default" size="100%">Electromyography</style></keyword><keyword><style  face="normal" font="default" size="100%">Feedback</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Foot</style></keyword><keyword><style  face="normal" font="default" size="100%">Hand</style></keyword><keyword><style  face="normal" font="default" size="100%">Head Movements</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Magnetic Resonance Imaging</style></keyword><keyword><style  face="normal" font="default" size="100%">Magnetoencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Movement</style></keyword><keyword><style  face="normal" font="default" size="100%">Principal Component Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Processing, Computer-Assisted</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2007</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/17475511</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">581-93</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;Brain-computer interfaces (BCIs) allow for communicating intentions by mere brain activity, not involving muscles. Thus, BCIs may offer patients who have lost all voluntary muscle control the only possible way to communicate. Many recent studies have demonstrated that BCIs based on&amp;nbsp;&lt;/span&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;electroencephalography&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;(&lt;/span&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;EEG&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;) can allow healthy and severely paralyzed individuals to communicate. While this approach is safe and inexpensive, communication is slow. Magnetoencephalography (MEG) provides signals with higher spatiotemporal resolution than&amp;nbsp;&lt;/span&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;EEG&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;&amp;nbsp;and could thus be used to explore whether these improved signal properties translate into increased BCI communication speed. In this study, we investigated the utility of an MEG-based BCI that uses voluntary amplitude modulation of sensorimotor mu and beta rhythms. To increase the signal-to-noise ratio, we present a simple spatial filtering method that takes the geometric properties of signal propagation in MEG into account, and we present methods that can process artifacts specifically encountered in an MEG-based BCI. Exemplarily, six participants were successfully trained to communicate binary decisions by imagery of limb movements using a feedback paradigm. Participants achieved significant mu rhythm self control within 32 min of feedback training. For a subgroup of three participants, we localized the origin of the amplitude modulated signal to the motor cortex. Our results suggest that an MEG-based BCI is feasible and efficient in terms of user training.&lt;/span&gt;&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jeremy Jeremy Hill</style></author><author><style face="normal" font="default" size="100%">Lal, T.N</style></author><author><style face="normal" font="default" size="100%">Schröder, Michael</style></author><author><style face="normal" font="default" size="100%">Hinterberger, T.</style></author><author><style face="normal" font="default" size="100%">Wilhelm, Barbara</style></author><author><style face="normal" font="default" size="100%">Nijboer, F</style></author><author><style face="normal" font="default" size="100%">Mochty, Ursula</style></author><author><style face="normal" font="default" size="100%">Widman, Guido</style></author><author><style face="normal" font="default" size="100%">Elger, Christian</style></author><author><style face="normal" font="default" size="100%">Schölkopf, B</style></author><author><style face="normal" font="default" size="100%">Kübler, A.</style></author><author><style face="normal" font="default" size="100%">Niels Birbaumer</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Classifying EEG and ECoG signals without subject training for fast BCI implementation: comparison of nonparalyzed and completely paralyzed subjects.</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Trans Neural Syst Rehabil Eng</style></secondary-title><alt-title><style face="normal" font="default" size="100%">IEEE Trans Neural Syst Rehabil Eng</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Artificial Intelligence</style></keyword><keyword><style  face="normal" font="default" size="100%">Cluster Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer User Training</style></keyword><keyword><style  face="normal" font="default" size="100%">Electroencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Evoked Potentials</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Imagination</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Paralysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Pattern Recognition, Automated</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2006</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/16792289</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">183-6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;We summarize results from a series of related studies that aim to develop a motor-imagery-&lt;/span&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;based&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;&amp;nbsp;&lt;/span&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;brain-computer interface&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;&amp;nbsp;using a single recording session of electroencephalogram (EEG) or electrocorticogram (ECoG) signals for each subject. We apply the same experimental and analytical methods to 11 nonparalysed subjects (eight EEG, three ECoG), and to five paralyzed subjects (four EEG, one ECoG) who had been unable to communicate for some time. While it was relatively easy to obtain classifiable signals quickly from most of the nonparalyzed subjects, it proved impossible to classify the signals obtained from the paralyzed patients by the same methods. This highlights the fact that though certain BCI paradigms may work well with healthy subjects, this does not necessarily indicate success with the target user group. We outline possible reasons for this failure to transfer.&lt;/span&gt;&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kübler, A.</style></author><author><style face="normal" font="default" size="100%">Nijboer, F</style></author><author><style face="normal" font="default" size="100%">Mellinger, Jürgen</style></author><author><style face="normal" font="default" size="100%">Theresa M Vaughan</style></author><author><style face="normal" font="default" size="100%">Pawelzik, H</style></author><author><style face="normal" font="default" size="100%">Gerwin Schalk</style></author><author><style face="normal" font="default" size="100%">Dennis J. McFarland</style></author><author><style face="normal" font="default" size="100%">Niels Birbaumer</style></author><author><style face="normal" font="default" size="100%">Jonathan Wolpaw</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface.</style></title><secondary-title><style face="normal" font="default" size="100%">Neurology</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Neurology</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Amyotrophic Lateral Sclerosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Electroencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Evoked Potentials, Motor</style></keyword><keyword><style  face="normal" font="default" size="100%">Evoked Potentials, Somatosensory</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Imagination</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Motor Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Movement</style></keyword><keyword><style  face="normal" font="default" size="100%">Paralysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Photic Stimulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Prostheses and Implants</style></keyword><keyword><style  face="normal" font="default" size="100%">Somatosensory Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Treatment Outcome</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2005</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/15911809</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">64</style></volume><pages><style face="normal" font="default" size="100%">1775-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;People with severe motor disabilities can maintain an acceptable quality of life if they can communicate.&amp;nbsp;&lt;/span&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;Brain-computer interfaces&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;&amp;nbsp;(BCIs), which do not depend on muscle control, can provide communication. Four people severely disabled by ALS learned to operate a BCI with EEG rhythms recorded over sensorimotor cortex. These results suggest that a sensorimotor rhythm-&lt;/span&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;based&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;&amp;nbsp;BCI could help maintain quality of life for people with ALS.&lt;/span&gt;&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue></record></records></xml>