{"title":"Increasing brain-computer interface media depictions: pressing ethical concerns","authors":"Frederic Gilbert, C. Pham, J. Viaña, W. Gillam","doi":"10.1080/2326263x.2019.1655837","DOIUrl":"https://doi.org/10.1080/2326263x.2019.1655837","url":null,"abstract":"This article explores how brain-computer interfaces (BCI) are depicted in the English-speaking media, especially by news outlets. We use the FACTICA database to analyze depictions of BCIs from the first time the term appeared in the media (1993) up until 31 December 2017. We found a sample of over 4064 articles on BCIs. Results indicate that 76.91% of articles portrayed BCI positively, including 25.27% that were overly positive, while 26.64 % of the total articles contain claims about BCI-enabled enhancement. In contrast, 1.6% of articles had a negative tone and only 2.7% of articles flag issues explicitly related to ethical concerns surrounding BCI technology. We propose: 1) A proactive effort by the scientific community to push-out to the media stories focused on the limits and actual capabilities of BCIs, separating science from science fiction; 2) More influence should be brought to bear on the technological risks and process of informed consent.","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"31 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2019-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82964339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Personalized adaptive instruction design (PAID) for brain–computer interface using reinforcement learning and deep learning: simulated data study","authors":"A. Eliseyev, T. Aksenova","doi":"10.1080/2326263X.2019.1651570","DOIUrl":"https://doi.org/10.1080/2326263X.2019.1651570","url":null,"abstract":"ABSTRACTBrain–computer interface (BCI) systems may require the user to perform a set of mental tasks, such as imagining different types of motion. The performance demonstrated on these tasks varies...","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"25 6 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2019-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90603302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Soheil Borhani, R. Abiri, Yang Jiang, T. Berger, Xiaopeng Zhao
{"title":"Brain connectivity evaluation during selective attention using EEG-based brain-computer interface","authors":"Soheil Borhani, R. Abiri, Yang Jiang, T. Berger, Xiaopeng Zhao","doi":"10.1080/2326263X.2019.1651186","DOIUrl":"https://doi.org/10.1080/2326263X.2019.1651186","url":null,"abstract":"ABSTRACTAttentional deficits may be caused by neurological diseases, including Attention-Deficit/Hyperactivity Disorder (ADHD), Alzheimer’s disease (AD), Traumatic Brain Injuries (TBI), etc. This w...","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"16 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2019-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87646465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Online detection of error-related potentials in multi-class cognitive task-based BCIs","authors":"R. Yousefi, Alborz Rezazadeh Sereshkeh, T. Chau","doi":"10.1080/2326263X.2019.1614770","DOIUrl":"https://doi.org/10.1080/2326263X.2019.1614770","url":null,"abstract":"ABSTRACTOne method for improving the accuracy and hence the rate of communication of a brain–computer interface (BCI) is to automatically correct erroneous classifications by exploiting error-relat...","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"65 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2019-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/2326263X.2019.1614770","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72502923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michelle Pham, S. Goering, M. Sample, J. Huggins, E. Klein
{"title":"Asilomar survey: researcher perspectives on ethical principles and guidelines for BCI research","authors":"Michelle Pham, S. Goering, M. Sample, J. Huggins, E. Klein","doi":"10.1080/2326263X.2018.1530010","DOIUrl":"https://doi.org/10.1080/2326263X.2018.1530010","url":null,"abstract":"ABSTRACTBrain-computer Interface (BCI) research is rapidly expanding, and it engages domains of human experience that many find central to our current understanding of ourselves. Ethical principles...","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"49 5 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2018-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89203276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A comparison of a broad range of EEG acquisition devices – is there any difference for SSVEP BCIs?","authors":"R. Zerafa, T. Camilleri, O. Falzon, K. Camilleri","doi":"10.1080/2326263X.2018.1550710","DOIUrl":"https://doi.org/10.1080/2326263X.2018.1550710","url":null,"abstract":"ABSTRACTThis study compared the signal quality of six commercially available electroencephalography (EEG) signal acquisition systems in order to evaluate their application in a brain-computer inter...","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"6 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2018-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77008195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Caregiver and special education staff perspectives of a commercial brain-computer interface as access technology: a qualitative study","authors":"S. Taherian, T. C. Davies","doi":"10.1080/2326263X.2018.1505191","DOIUrl":"https://doi.org/10.1080/2326263X.2018.1505191","url":null,"abstract":"ABSTRACTThis study sought to understand the perceptions of special education staff and caregivers (n = 6) who took part in a brain-computer interface (BCI) technology trial for individuals with severe cerebral palsy. Participants were interviewed post-trials regarding the different BCI components. The transcripts were coded and analyzed using thematic analysis. Results showed that BCIs are not suitable for independent use outside of clinical/laboratory settings. The hardware needs to be configurable, comfortable and accommodate physical support needs. The training approach needs to be less cognitively demanding, motivating and support personalized mental tasks. For BCIs to transition into the real world, there should be adequate technological support, improved reliability, and a systemic assessment of how the technology will fit into the lives of end users. Participants emphasized the on-going need to involve users and individuals who support them, to create a system that truly meets the needs of the users.","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"21 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88915053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Guger, J. Millán, D. Mattia, J. Ushiba, S. Soekadar, V. Prabhakaran, N. Mrachacz‐Kersting, K. Kamada, B. Allison
{"title":"Brain-computer interfaces for stroke rehabilitation: summary of the 2016 BCI Meeting in Asilomar","authors":"C. Guger, J. Millán, D. Mattia, J. Ushiba, S. Soekadar, V. Prabhakaran, N. Mrachacz‐Kersting, K. Kamada, B. Allison","doi":"10.1080/2326263X.2018.1493073","DOIUrl":"https://doi.org/10.1080/2326263X.2018.1493073","url":null,"abstract":"ABSTRACTBrain-computer interfaces (BCIs) based on motor imagery have been gaining attention as tools to facilitate recovery from movement disorders resulting from stroke or other causes. These BCIs can detect imagined movements that are typically required within conventional rehabilitation therapy. This information about the timing, intensity, and location of imagined movements can help assess compliance and control feedback mechanisms such as functional electrical stimulation (FES) and virtual avatars. Here, we review work from eight groups that each presented recent results with BCI-based rehabilitation at a workshop during the 6th International Brain-Computer Interface Meeting. We also present major directions and challenges for future research.","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"1 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79888963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Dijkstra, P. Brunner, A. Gunduz, W. Coon, A. Ritaccio, J. Farquhar, G. Schalk
{"title":"Identifying the Attended Speaker Using Electrocorticographic (ECoG) Signals.","authors":"K. Dijkstra, P. Brunner, A. Gunduz, W. Coon, A. Ritaccio, J. Farquhar, G. Schalk","doi":"10.1080/2326263X.2015.1063363","DOIUrl":"https://doi.org/10.1080/2326263X.2015.1063363","url":null,"abstract":"People affected by severe neuro-degenerative diseases (e.g., late-stage amyotrophic lateral sclerosis (ALS) or locked-in syndrome) eventually lose all muscular control. Thus, they cannot use traditional assistive communication devices that depend on muscle control, or brain-computer interfaces (BCIs) that depend on the ability to control gaze. While auditory and tactile BCIs can provide communication to such individuals, their use typically entails an artificial mapping between the stimulus and the communication intent. This makes these BCIs difficult to learn and use. In this study, we investigated the use of selective auditory attention to natural speech as an avenue for BCI communication. In this approach, the user communicates by directing his/her attention to one of two simultaneously presented speakers. We used electrocorticographic (ECoG) signals in the gamma band (70-170 Hz) to infer the identity of attended speaker, thereby removing the need to learn such an artificial mapping. Our results from twelve human subjects show that a single cortical location over superior temporal gyrus or pre-motor cortex is typically sufficient to identify the attended speaker within 10 s and with 77% accuracy (50% accuracy due to chance). These results lay the groundwork for future studies that may determine the real-time performance of BCIs based on selective auditory attention to speech.","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"47 1","pages":"161-173"},"PeriodicalIF":2.1,"publicationDate":"2015-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73776057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mood Recognition System Using EEG Signal of Song Induced Activities","authors":"R. Deore, S. Mehrotra","doi":"10.1007/978-3-319-10978-7_13","DOIUrl":"https://doi.org/10.1007/978-3-319-10978-7_13","url":null,"abstract":"","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"95 1","pages":"337-374"},"PeriodicalIF":2.1,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80436997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}