Sensory-Motor Laboratory (SeMoLa), Jules-Gonin Eye Hospital/Fondation Asile des Aveugles, Department of Ophthalmology/University of Lausanne, Lausanne, Switzerland; InBrain Lab, Department of Physics, University of São Paulo, Ribeirão Preto, Brazil; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zürich, Switzerland.
Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zürich, Switzerland.
Neuroimage. 2020 Nov 1;221:117194. doi: 10.1016/j.neuroimage.2020.117194. Epub 2020 Jul 23.
The brain regions supporting sustained attention (sustained attention network; SAN) and mind-wandering (default-mode network; DMN) have been extensively studied. Nevertheless, this knowledge has not yet been translated into advanced brain-based attention training protocols. Here, we used network-based real-time functional magnetic resonance imaging (fMRI) to provide healthy individuals with information about current activity levels in SAN and DMN. Specifically, 15 participants trained to control the difference between SAN and DMN hemodynamic activity and completed behavioral attention tests before and after neurofeedback training. Through training, participants improved controlling the differential SAN-DMN feedback signal, which was accomplished mainly through deactivating DMN. After training, participants were able to apply learned self-regulation of the differential feedback signal even when feedback was no longer available (i.e., during transfer runs). The neurofeedback group improved in sustained attention after training, although this improvement was temporally limited and rarely exceeded mere practice effects that were controlled by a test-retest behavioral control group. The learned self-regulation and the behavioral outcomes suggest that neurofeedback training of differential SAN and DMN activity has the potential to become a non-invasive and non-pharmacological tool to enhance attention and mitigate specific attention deficits.
支持持续注意力（持续注意力网络；SAN）和走神（默认模式网络；DMN）的大脑区域已经得到了广泛的研究。然而，这些知识尚未转化为先进的基于大脑的注意力训练方案。在这里，我们使用基于网络的实时功能磁共振成像（fMRI）为健康个体提供关于 SAN 和 DMN 血流动力学活动当前水平的信息。具体来说，15 名参与者接受了训练，以控制 SAN 和 DMN 血液动力学活动之间的差异，并在神经反馈训练前后完成了行为注意力测试。通过训练，参与者改善了控制 SAN-DMN 反馈信号差异的能力，这主要是通过使 DMN 去激活来实现的。训练后，即使没有反馈（即转移运行期间），参与者也能够应用所学的自我调节差异反馈信号。神经反馈组在训练后注意力得到了提高，尽管这种提高在时间上是有限的，而且很少超过由测试-重测行为对照组控制的单纯练习效应。所学到的自我调节和行为结果表明，对 SAN 和 DMN 活动差异的神经反馈训练有可能成为一种非侵入性和非药物的工具，以增强注意力和减轻特定的注意力缺陷。
