Echtzeit-Neurofeedback auf den Ruhezustand des Gehirns: Evaluation des therapeutischen Nutzens zur Anfallsreduktion bei Epilepsie

大脑静息状态的实时神经反馈：评估减少癫痫发作的治疗效果

• 批准号: 216734379
• 负责人: Professorin Dr. Esther Florin
• 金额: --
• 依托单位: Montreal Neurological Institute-Hospital
• 依托单位国家: 德国
• 项目类别: Research Fellowships
• 财政年份: 2012
• 资助国家: 德国
• 起止时间: 2011-12-31 至 2012-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/216734379?language=en
• 关键词: Echtzeit; Neurofeedback; auf; den; Ruhezustand

During the past decade, a connectivity map of brain activity during rest has been identified in humans using functional magnetic resonance imaging (fMRI). The complete functional relevance of this resting-state (RS) network is not known, but recent evidence suggests its significance for the brain’s function and dysfunction. The proposed project takes a multimodal viewpoint on the RS network (i) to better understand the electrophysiological correlates of RS blood-oxygen level dependent fluctuations, (ii) to demonstrate interactions of RS networks with other brain systems, and (iii) to show how therapeutic interventions can benefit from this research. These issues will be analyzed through the lens of medial temporal lobe epilepsy. The specific working hypothesis is that epilepsy alters the spatial and dynamical properties of the RS. It is conjectured that by using advanced neurofeedback, patients can be trained to modulate their RS-activity and thereby reduce their seizure rate. During the first stage, the current knowledge of the RS will be improved by identifying the RS network using time-resolved magnetoencephalography (MEG) source reconstruction. By using MEG source reconstruction, it is intended to identify the connectivity between the different brain areas involved in the RS and the temporal evolution of the RS. This is currently not possible due to fMRI’s low temporal resolution. The second stage intends to demonstrate that by using a new technique of MEG neurofeedback, whereby feedback is provided on the activity of certain brain regions and the connectivity between them, control subjects are able to modulate the spatio-temporal structure of RS networks. Finally a therapeutic perspective is taken: epileptic patients will be trained through neurofeedback to target specific features of their RS activity, e. g., to change the spectral or effective connectivity properties of a targeted brain region. The goal of this training will be to reduce the seizures rate.

在过去的十年中，使用功能性磁共振成像（fMRI）在人类中确定了休息时大脑活动的连接图。这种静息状态（RS）网络的完整功能相关性尚不清楚，但最近的证据表明其对大脑功能和功能障碍的重要性。该项目对RS网络采取多模态观点，（i）更好地理解RS血氧水平依赖性波动的电生理学相关性，（ii）展示RS网络与其他大脑系统的相互作用，以及（iii）展示治疗干预如何从这项研究中受益。这些问题将通过内侧颞叶癫痫的透镜来分析。具体的工作假设是癫痫改变了RS的空间和动力学特性。据证实，通过使用先进的神经反馈，患者可以被训练来调节他们的RS活动，从而降低他们的癫痫发作率。在第一阶段，目前的知识，RS将提高识别RS网络使用时间分辨脑磁图（MEG）源重建。通过使用MEG源重建，旨在识别RS所涉及的不同脑区之间的连接以及RS的时间演变。由于fMRI的时间分辨率较低，目前还无法实现。第二阶段旨在证明，通过使用MEG神经反馈的新技术，从而提供反馈的某些脑区的活动和它们之间的连接，控制主体能够调制RS网络的时空结构。最后，从治疗的角度来看：癫痫患者将通过神经反馈进行训练，以针对其RS活动的特定特征，例如。例如，在一个实施例中，以改变目标大脑区域的光谱或有效连接特性。这一培训的目标将是降低缉获率。