Experimental Psychology Lab, Department of Psychology, European Medical School, Carl von Ossietzky University, Oldenburg, Germany; Research Center Neurosensory Science, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.
Experimental Psychology Lab, Department of Psychology, European Medical School, Carl von Ossietzky University, Oldenburg, Germany.
Int J Psychophysiol. 2014 Jan;91(1):36-45. doi: 10.1016/j.ijpsycho.2013.08.011. Epub 2013 Sep 4.
Neurofeedback training procedures designed to alter a person's brain activity have been in use for nearly four decades now and represent one of the earliest applications of brain-computer interfaces (BCI). The majority of studies using neurofeedback technology relies on recordings of the electroencephalogram (EEG) and applies neurofeedback in clinical contexts, exploring its potential as treatment for psychopathological syndromes. This clinical focus significantly affects the technology behind neurofeedback BCIs. For example, in contrast to other BCI applications, neurofeedback BCIs usually rely on EEG-derived features with only a minimum of additional processing steps being employed. Here, we highlight the peculiarities of EEG-based neurofeedback BCIs and consider their relevance for software implementations. Having reviewed already existing packages for the implementation of BCIs, we introduce our own solution which specifically considers the relevance of multi-subject handling for experimental and clinical trials, for example by implementing ready-to-use solutions for pseudo-/sham-neurofeedback.
神经反馈训练程序旨在改变人的大脑活动,已经使用了近四十年,是脑机接口(BCI)最早的应用之一。大多数使用神经反馈技术的研究都依赖于脑电图(EEG)的记录,并将神经反馈应用于临床环境中,探索其作为治疗精神病理综合征的潜力。这种临床重点显著影响了神经反馈 BCI 背后的技术。例如,与其他 BCI 应用相比,神经反馈 BCI 通常依赖于基于 EEG 的特征,只采用了最少的额外处理步骤。在这里,我们强调了基于 EEG 的神经反馈 BCI 的特点,并考虑了它们对软件实现的相关性。在回顾了已经存在的用于实现 BCI 的软件包之后,我们引入了自己的解决方案,该解决方案特别考虑了多主体处理对于实验和临床试验的相关性,例如通过实现用于伪/假神经反馈的即用型解决方案。