Online Neuronal Connectivity Estimation and Neurofeedback with Transcranial Magnetic Stimulation

脑磁图(MEG)和脑电图(EEG)使研究人员能够研究人类大脑电生理活动的快速时空变化。与此同时，随着离线脑磁图/脑电分析的进步，人们对在线数据处理的兴趣也越来越大。在线处理为更快、更直观地了解瞬时大脑功能铺平了道路，同时也为广泛的神经反馈场景奠定了基础。在之前DFG资助的一个项目中，我们建立并研究了在线估计皮质活动的方法。在下文中，我们介绍了与奥地利合作伙伴小组共同努力的延长提案。首先，我们的目标是建立新的在线连通性估计方法来分析脑网络结构。通过新的在线连通性估计，我们的目标是为神经反馈场景中的稳健特征提取提供输入。此外，我们的目标是将结果在在线3D显示中可视化，以便进行更紧迫的分析。其次，我们希望将依赖于大脑状态的皮质刺激纳入我们的在线处理流程。到目前为止，关于将皮质刺激直接整合到神经反馈或脑计算机接口(BCI)场景中的工作还很少。通过将新的在线方法纳入经颅磁刺激(TMS)，我们希望为即将到来的EEG/TMS研究做准备，并将TMS整合到神经反馈场景中。

Magnetoencephalography (MEG) and Electroencephalography (EEG) enable researchers to investigate fast spatial and temporal changes of electrophysiological activity in the human brain. In parallel, with advances in off-line MEG/EEG analysis there is a growing interest in online data processing. Online processing paves the way for a faster and intuitive insight on instantaneous brain functions and at the same time creates the foundation for a wide range of neurofeedback scenarios. During a prior DFG funded project we established and investigated methods for estimating cortical activity online. In the following, we present the renewal proposal as a joint effort with an Austrian partner group. Firstly, we aim to establish novel online connectivity estimation methods for analyzing brain network structures. With the novel online connectivity estimation, we aim to provide input for robust feature extraction in neurofeedback scenarios. Moreover, we aim to visualize the results in an online 3D display for a more imminent analysis. Secondly, we want to include brain state dependent cortical stimulation into our online processing pipeline. Little work on directly integrating cortical stimulation into a neurofeedback or Brain Computer Interface (BCI) scenario has been proposed so far. By including the new online methods into Transcranial Magnetic Stimulation (TMS) we want to prepare for upcoming EEG/TMS studies and the integration of TMS into neurofeedback scenarios.