<?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%">Vansteensel, Mariska J</style></author><author><style face="normal" font="default" size="100%">Klein, Eran</style></author><author><style face="normal" font="default" size="100%">van Thiel, Ghislaine</style></author><author><style face="normal" font="default" size="100%">Gaytant, Michael</style></author><author><style face="normal" font="default" size="100%">Simmons, Zachary</style></author><author><style face="normal" font="default" size="100%">Wolpaw, Jonathan R</style></author><author><style face="normal" font="default" size="100%">Vaughan, Theresa M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards clinical application of implantable brain-computer interfaces for people with late-stage ALS: medical and ethical considerations.</style></title><secondary-title><style face="normal" font="default" size="100%">J Neurol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Neurol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amyotrophic Lateral Sclerosis</style></keyword><keyword><style  face="normal" font="default" size="100%">brain-computer interfaces</style></keyword><keyword><style  face="normal" font="default" size="100%">Electroencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Self-Help Devices</style></keyword><keyword><style  face="normal" font="default" size="100%">Speech</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2023</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">270</style></volume><pages><style face="normal" font="default" size="100%">1323-1336</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Individuals with amyotrophic lateral sclerosis (ALS) frequently develop speech and communication problems in the course of their disease. Currently available augmentative and alternative communication technologies do not present a solution for many people with advanced ALS, because these devices depend on residual and reliable motor activity. Brain-computer interfaces (BCIs) use neural signals for computer control and may allow people with late-stage ALS to communicate even when conventional technology falls short. Recent years have witnessed fast progression in the development and validation of implanted BCIs, which place neural signal recording electrodes in or on the cortex. Eventual widespread clinical application of implanted BCIs as an assistive communication technology for people with ALS will have significant consequences for their daily life, as well as for the clinical management of the disease, among others because of the potential interaction between the BCI and other procedures people with ALS undergo, such as tracheostomy. This article aims to facilitate responsible real-world implementation of implanted BCIs. We review the state of the art of research on implanted BCIs for communication, as well as the medical and ethical implications of the clinical application of this technology. We conclude that the contribution of all BCI stakeholders, including clinicians of the various ALS-related disciplines, will be needed to develop procedures for, and shape the process of, the responsible clinical application of implanted BCIs.&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%">Vansteensel, Mariska J</style></author><author><style face="normal" font="default" size="100%">Hermes, Dora</style></author><author><style face="normal" font="default" size="100%">Aarnoutse, Erik J</style></author><author><style face="normal" font="default" size="100%">Bleichner, Martin G</style></author><author><style face="normal" font="default" size="100%">Gerwin Schalk</style></author><author><style face="normal" font="default" size="100%">van Rijen, Peter C</style></author><author><style face="normal" font="default" size="100%">Leijten, Frans S S</style></author><author><style face="normal" font="default" size="100%">Ramsey, Nick F</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Brain-computer interfacing based on cognitive control.</style></title><secondary-title><style face="normal" font="default" size="100%">Ann Neurol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Ann. Neurol.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cognition</style></keyword><keyword><style  face="normal" font="default" size="100%">Computers</style></keyword><keyword><style  face="normal" font="default" size="100%">Electrodes</style></keyword><keyword><style  face="normal" font="default" size="100%">Electroencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Epilepsy</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Image Processing, Computer-Assisted</style></keyword><keyword><style  face="normal" font="default" size="100%">Magnetic Resonance Imaging</style></keyword><keyword><style  face="normal" font="default" size="100%">Neuropsychological Tests</style></keyword><keyword><style  face="normal" font="default" size="100%">Oxygen</style></keyword><keyword><style  face="normal" font="default" size="100%">Prefrontal Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Psychomotor Performance</style></keyword><keyword><style  face="normal" font="default" size="100%">Spectrum Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Time Factors</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%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2010</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/20517943</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">67</style></volume><pages><style face="normal" font="default" size="100%">809-16</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;Brain-computer interfaces (BCIs) translate deliberate intentions and associated changes in brain activity into action, thereby offering patients with severe paralysis an alternative means of communication with and control over their environment. Such systems are not available yet, partly due to the high performance standard that is required. A major challenge in the development of implantable BCIs is to identify cortical regions and related functions that an individual can reliably and consciously manipulate. Research predominantly focuses on the sensorimotor cortex, which can be activated by imagining motor actions. However, because this region may not provide an optimal solution to all patients, other neuronal networks need to be examined. Therefore, we investigated whether the cognitive control network can be used for BCI purposes. We also determined the feasibility of using functional magnetic resonance imaging (fMRI) for noninvasive localization of the cognitive control network.&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;Three patients with intractable epilepsy, who were temporarily implanted with subdural grid electrodes for diagnostic purposes, attempted to gain BCI control using the electrocorticographic (ECoG) signal of the left dorsolateral prefrontal cortex (DLPFC).&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;All subjects quickly gained accurate BCI control by modulation of gamma-power of the left DLPFC. Prelocalization of the relevant region was performed with fMRI and was confirmed using the ECoG signals obtained during mental calculation localizer tasks.&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;INTERPRETATION:&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 indicate that the cognitive control network is a suitable source of signals for BCI applications. They also demonstrate the feasibility of translating understanding about cognitive networks derived from functional neuroimaging into clinical applications.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue></record></records></xml>