Employing an active mental task to enhance the performance of auditory attention-based brain-computer interfaces

被引:19
|
作者
Xu, Honglai [1 ]
Zhang, Dan [1 ]
Ouyang, Minhui [1 ]
Hong, Bo [1 ]
机构
[1] Tsinghua Univ, Sch Med, Dept Biomed Engn, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Active mental task; Brain-computer interfaces; Auditory evoked potentials; LATE POSITIVE COMPLEX; P300 SPELLING SYSTEM; ERP COMPONENTS; DIVIDED ATTENTION; POTENTIAL ERP; DIFFICULTY; COMMUNICATION; TRANSIENT; P3A; ALS;
D O I
10.1016/j.clinph.2012.06.004
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Objective: A majority of auditory brain-computer interfaces (BCIs) use the attentional modulation of auditory event-related potentials (ERPs) for communication and control. This study investigated whether the performance of an ERP-based auditory BCI can be further improved by increasing the mental efforts associated with the execution of the attention-related task. Methods: Subjects mentally selected a target among a random sequence of spoken digits. Upon the detection of the target digit, the subjects were required to perform an active mental task (AMT) - mentally discriminating the gender property of the target voice. The total number of presented digits was manipulated to investigate possible influences of the number of choices. The subjects also participated in two control experiments, in which they were asked to (1) press a button to report their discrimination results or (2) simply count the appearance of the target digit without performing the AMT. Results: Two ERP components, that is, a negative shift around 200 ms (Nd) over the fronto-central area and a positive deflection during 500-600 ms (late positive component, LPC) over the central-parietal area, were modulated by execution of the AMT. Compared to a counting task, the AMT resulted in paradigm-specific enhanced LPC responses. The latency of the LPC was significantly correlated with the behavioural reaction time, indicating that the LPC could originate from a response-related brain network similar to P3b. The AMT paradigm resulted in an increase of 4-6% in BCI classification accuracies, compared to a counting paradigm that was considered to represent the traditional auditory attention BCI paradigms (p < 0.05). In addition, the BCI classification accuracies were not significantly affected by the number of BCI choices in the AMT paradigm. Conclusions: (1) LPC was identified as the AMT-specific ERP component and (2) the performance of auditory BCIs can be improved from the human response side by introducing additional mental efforts when executing attention-related tasks. Significance: The neurophysiological characteristics of the recently proposed auditory BCI paradigm using an AMT were explored. The results suggest the proposed paradigm as a candidate for improving the performance of auditory BCIs. (C) 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:83 / 90
页数:8
相关论文
共 50 条
  • [41] An online brain-computer interface based on shifting attention to concurrent streams of auditory stimuli
    Hill, N. J.
    Schoelkopf, B.
    JOURNAL OF NEURAL ENGINEERING, 2012, 9 (02)
  • [42] Decoding auditory and tactile attention for use in an EEG-based brain-computer interface
    An, Winko W.
    Si-Mohammed, Hakim
    Huang, Nicholas
    Gamper, Hannes
    Lee, Adrian K. C.
    Holz, Christian
    Johnston, David
    Jalobeanu, Mihai
    Emmanouilidou, Dimitra
    Cutrell, Edward
    Wilson, Andrew
    Tashev, Ivan
    2020 8TH INTERNATIONAL WINTER CONFERENCE ON BRAIN-COMPUTER INTERFACE (BCI), 2020, : 42 - 47
  • [43] A CUSTOM-DESIGNED MENTAL TASK-BASED BRAIN-COMPUTER INTERFACE
    Faradji, Farhad
    Ward, Rabab K.
    Birch, Gary E.
    2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS, 2009, : 529 - 532
  • [44] Is Neural Activity Detected by ERP-Based Brain-Computer Interfaces Task Specific?
    Wenzel, Markus A.
    Almeida, Ines
    Blankertz, Benjamin
    PLOS ONE, 2016, 11 (10):
  • [45] Conformal in-ear bioelectronics for visual and auditory brain-computer interfaces
    Wang, Zhouheng
    Shi, Nanlin
    Zhang, Yingchao
    Zheng, Ning
    Li, Haicheng
    Jiao, Yang
    Cheng, Jiahui
    Wang, Yutong
    Zhang, Xiaoqing
    Chen, Ying
    Chen, Yihao
    Wang, Heling
    Xie, Tao
    Wang, Yijun
    Ma, Yinji
    Gao, Xiaorong
    Feng, Xue
    NATURE COMMUNICATIONS, 2023, 14 (01)
  • [46] Improving Auditory Paradigms for Consciousness Detection by Brain-Computer Interfaces Technique
    Agoiz Badia, Daniel
    Dinares-Ferran, Josep
    Swift, James
    Xu, Ren
    Ortner, Rupert
    Rodriguez, Javier
    Guger, Christoph
    Giraldo, Beatriz F.
    Edlinger, Guenter
    2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2018, : 63 - 66
  • [47] Conformal in-ear bioelectronics for visual and auditory brain-computer interfaces
    Zhouheng Wang
    Nanlin Shi
    Yingchao Zhang
    Ning Zheng
    Haicheng Li
    Yang Jiao
    Jiahui Cheng
    Yutong Wang
    Xiaoqing Zhang
    Ying Chen
    Yihao Chen
    Heling Wang
    Tao Xie
    Yijun Wang
    Yinji Ma
    Xiaorong Gao
    Xue Feng
    Nature Communications, 14
  • [48] Performance Analysis of Brain-Computer Interfaces in Aerial Drone
    North, Sarah
    Rashied, Adnan
    Walters, Jason
    Alissa, Ahmad
    Cooper, Josh
    Rawls, Eric
    Sancho, Cheyenne
    Sahin, Utku 'Victor'
    Randell, Kate
    Rego, Heather
    ACMSE '18: PROCEEDINGS OF THE ACMSE 2018 CONFERENCE, 2018,
  • [49] Design of auditory P300-based brain-computer interfaces with a single auditory channel and no visual support
    Choi, Yun-Joo
    Kwon, Oh-Sang
    Kim, Sung-Phil
    COGNITIVE NEURODYNAMICS, 2023, 17 (06) : 1401 - 1416
  • [50] Design of auditory P300-based brain-computer interfaces with a single auditory channel and no visual support
    Yun-Joo Choi
    Oh-Sang Kwon
    Sung-Phil Kim
    Cognitive Neurodynamics, 2023, 17 : 1401 - 1416