Using neurophysiological signals that reflect cognitive or affective state: six recommendations to avoid common pitfalls.
Using neurophysiological signals that reflect cognitive or affective state: six recommendations to avoid common pitfalls.
复制标题
DOI：
10.3389/fnins.2015.00136
复制
发表时间：
2015
影响因子：
4.3
通讯作者：
Bronkhorst AW
中科院分区：
文献类型：
--
作者：
Brouwer AM;Zander TO;van Erp JB;Korteling JE;Bronkhorst AW
从神经生理信号中估计认知或情感状态，并设计利用这些信息的应用程序，需要许多学科的专业知识，如神经生理学、机器学习、实验心理学和人为因素。这使得在各个方面都很强的研究很难进行，也很难根据研究或应用的优点来判断。在专题“使用反映认知或情感状态的神经生理信号”之际，我们在这里总结了经常出现的陷阱，并为作者（研究人员）和读者提供了如何避免这些陷阱的建议。它们涉及到定义感兴趣的状态，预期参与感兴趣状态的神经生理过程，混淆因素，无意中“欺骗”分类分析，洞察成功状态估计的基础，以及最后，在应用程序背景下神经生理测量的附加价值。我们希望这篇论文将支持社区产生高质量的研究和经过充分验证的有用的应用。
Estimating cognitive or affective state from neurophysiological signals and designing applications that make use of this information requires expertise in many disciplines such as neurophysiology, machine learning, experimental psychology, and human factors. This makes it difficult to perform research that is strong in all its aspects as well as to judge a study or application on its merits. On the occasion of the special topic “Using neurophysiological signals that reflect cognitive or affective state” we here summarize often occurring pitfalls and recommendations on how to avoid them, both for authors (researchers) and readers. They relate to defining the state of interest, the neurophysiological processes that are expected to be involved in the state of interest, confounding factors, inadvertently “cheating” with classification analyses, insight on what underlies successful state estimation, and finally, the added value of neurophysiological measures in the context of an application. We hope that this paper will support the community in producing high quality studies and well-validated, useful applications.
登录
查看更多内容
影响因子：
4.3
作者：
Casson AJ
通讯作者：
Casson AJ
影响因子：
4
作者：
De Vos, Maarten;Kroesen, Markus;Debener, Stefan
通讯作者：
Debener, Stefan
影响因子：
4
作者：
Brouwer, Anne-Marie;Hogervorst, Maarten A.;Oostenveld, Robert
通讯作者：
Oostenveld, Robert
影响因子：
3
作者：
Enriquez-Geppert S;Huster RJ;Figge C;Herrmann CS
通讯作者：
Herrmann CS
影响因子：
3.7
作者：
Codispoti, M;Bradley, MM;Lang, PJ
通讯作者：
Lang, PJ