Real-time decoding of covert attention in higher-order visual areas.

Real-time decoding of covert attention in higher-order visual areas.
复制标题

DOI:
10.1016/j.neuroimage.2017.12.019
复制
发表时间:
2018-04-01
期刊:
影响因子:
5.7
通讯作者:
Rees G
Rees G
中科院分区:
医学1区
文献类型:
--
作者:
Ekanayake J;Hutton C;Ridgway G;Scharnowski F;Weiskopf N;Rees G

文献摘要

参考文献

被引文献

相似文献

脑机接口(BCI)提供了一种使用人脑激活来控制通信设备的方法。到目前为止,这只在主要的运动和感觉脑区得到了证明,使用外科植入物或非侵入性神经成像技术。在这里,我们提供了使用涉及复杂认知过程(如注意力)的高阶大脑区域的原理证明。使用实时fMRI,我们实施了一种在线“赢者通吃方法”,具有特定象限的参数估计,以实现大脑激活的单块分类。这些都与注意力的隐蔽分配,以现实世界的图像呈现在4象限的位置。在三个目标区域的准确性显着高于机会,与个人的解码准确率高达70%。通过利用更高阶的心理过程,“认知脑机接口”的访问方式多种多样,因此信息更通用,可能为因脑损伤而无法说话或移动的患者提供交流平台。使用实时功能磁共振成像的“认知脑机接口”的原理证明。高级视觉大脑区域用于解码注意力的分配。4象限空间注意力对真实世界图像的在线单块分类。通过使用“m序列”使大脑信号检测更有效。更高阶的心理过程产生更多的信息用于交流界面。
Brain-computer-interfaces (BCI) provide a means of using human brain activations to control devices for communication. Until now this has only been demonstrated in primary motor and sensory brain regions, using surgical implants or non-invasive neuroimaging techniques. Here, we provide proof-of-principle for the use of higher-order brain regions involved in complex cognitive processes such as attention. Using realtime fMRI, we implemented an online ‘winner-takes-all approach’ with quadrant-specific parameter estimates, to achieve single-block classification of brain activations. These were linked to the covert allocation of attention to real-world images presented at 4-quadrant locations. Accuracies in three target regions were significantly above chance, with individual decoding accuracies reaching upto 70%. By utilising higher order mental processes, ‘cognitive BCIs’ access varied and therefore more versatile information, potentially providing a platform for communication in patients who are unable to speak or move due to brain injury. Proof-of-principle of a ‘cognitive brain-computer-interface’ using realtime fMRI. Higher order visual brain regions used to decode the allocation of attention. Online single-block classification of 4-quadrant spatial attention to realworld images. Brain signal detection made more efficient by using ‘m-sequences’. Higher order mental processes produce more information for communication interfaces.
DOI: 10.1523/jneurosci.1776-08.2008
发表时间: 2008-10-01
期刊: The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子: --
作者:
Bressler SL;Tang W;Sylvester CM;Shulman GL;Corbetta M
通讯作者: Corbetta M
DOI: 10.1016/j.cub.2016.04.054
发表时间: 2016-07-11
期刊: CURRENT BIOLOGY
影响因子: 9.2
作者:
Astrand, Elaine;Wardak, Claire;Ben Hamed, Suliann
通讯作者: Ben Hamed, Suliann
DOI: 10.1016/j.cortex.2009.08.015
发表时间: 2011-01-01
期刊: CORTEX
影响因子: 3.6
作者:
Carlson, Thomas;Hogendoorn, Hinze;Verstraten, Frans A. J.
通讯作者: Verstraten, Frans A. J.
DOI: 10.1016/j.neuroimage.2010.09.044
发表时间: 2011-02-01
期刊: NEUROIMAGE
影响因子: 5.7
作者:
Cichy, Radoslaw Martin;Chen, Yi;Haynes, John-Dylan
通讯作者: Haynes, John-Dylan
DOI: 10.1007/s10548-012-0252-z
发表时间: 2013-01-01
期刊: BRAIN TOPOGRAPHY
影响因子: 2.7
作者:
Andersson, Patrik;Pluim, Josien P. W.;Ramsey, Nick F.
通讯作者: Ramsey, Nick F.