Neuroimaging Unit, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, 08005, Spain; Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, 08005, Spain.
Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zürich, Zürich, 8032, Switzerland; Neuroscience Center Zürich, University of Zürich and Swiss Federal Institute of Technology, Zürich, 8057, Switzerland; Zürich Center for Integrative Human Physiology (ZIHP), University of Zürich, Winterthurerstr. 190, Zürich, 8057, Switzerland; Department of Basic Psychological Research and Research Methods, Faculty of Psychology, University of Vienna, Liebiggasse 5, 1010 Vienna, Austria.
Neuroimage. 2019 Sep;198:150-159. doi: 10.1016/j.neuroimage.2019.05.008. Epub 2019 May 16.
Real-time neurofeedback enables human subjects to learn to regulate their brain activity, effecting behavioral changes and improvements of psychiatric symptomatology. Neurofeedback up-regulation and down-regulation have been assumed to share common neural correlates. Neuropsychiatric pathology and aging incur suboptimal functioning of the default mode network. Despite the exponential increase in real-time neuroimaging studies, the effects of aging, pathology and the direction of regulation on neurofeedback performance remain largely unknown. Using real-time fMRI data shared through the Rockland Sample Real-Time Neurofeedback project (N = 136) and open-access analyses, we first modeled neurofeedback performance and learning in a group of subjects with psychiatric history (n = 74) and a healthy control group (n = 62). Subsequently, we examined the relationship between up-regulation and down-regulation learning, the relationship between age and neurofeedback performance in each group and differences in neurofeedback performance between the two groups. For interpretative purposes, we also investigated functional connectomics prior to neurofeedback. Results show that in an initial session of default mode network neurofeedback with real-time fMRI, up-regulation and down-regulation learning scores are negatively correlated. This finding is related to resting state differences in the eigenvector centrality of the posterior cingulate cortex. Moreover, age correlates negatively with default mode network neurofeedback performance, only in absence of psychiatric history. Finally, adults with psychiatric history outperform healthy controls in default mode network up-regulation. Interestingly, the performance difference is related to no up-regulation learning in controls. This finding is supported by marginally higher default mode network centrality during resting state, in the presence of psychiatric history.
实时神经反馈使人类受试者能够学习调节大脑活动，从而实现行为改变和精神症状的改善。人们认为神经反馈的上调和下调具有共同的神经相关物。神经精神病理学和衰老会导致默认模式网络的功能不佳。尽管实时神经影像学研究呈指数级增长，但衰老、病理学以及调节方向对神经反馈表现的影响在很大程度上仍不清楚。我们使用通过 Rockland 样本实时神经反馈项目（N=136）共享的实时 fMRI 数据和开放获取的分析，首先在一组有精神病史的受试者（n=74）和健康对照组（n=62）中对神经反馈表现和学习进行建模。随后，我们研究了上调和下调学习之间的关系，每组中年龄与神经反馈表现之间的关系，以及两组之间神经反馈表现的差异。为了便于解释，我们还在进行神经反馈之前调查了功能连接组学。结果表明，在使用实时 fMRI 进行默认模式网络神经反馈的初始阶段，上调和下调学习评分呈负相关。这一发现与后扣带回皮层特征向量中心的静息状态差异有关。此外，年龄与无精神病史者的默认模式网络神经反馈表现呈负相关。最后，有精神病史的成年人在默认模式网络的上调中表现优于健康对照组。有趣的是，表现差异与对照组无上调学习有关。这一发现得到了在存在精神病史的情况下，静息状态默认模式网络中心性略高的支持。
