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Categorized EEG Neurofeedback Performance Unveils Simultaneous fMRI Deep Brain Activation

机译:分类的脑电图神经反馈表现出了同时功能磁共振成像深层大脑激活

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Decades of Electroencephalogram-NeuroFeedback (EEG-NF) practice have proven that people can be effectively trained to selectively regulate their brain activity, thus potentially improving performance. A common protocol of EEG-NF training aims to guide people via a closed-loop operation shifting from high-amplitude of alpha (8-14Hz) to high-amplitude of theta (4-7 Hz) oscillations resulting in greater theta/alpha ratio (T/A). The induction of such a shift in EEG oscillations has been shown to be useful in reaching a state of relaxation in psychiatric conditions of anxiety and mood disorders. However, the clinical implication of this practice remains elusive and is considered to have relatively low therapeutic yield, possibly due to its poor specificity to a unique brain mechanism. The current project aims to use simultaneous acquisition of Functional Magnetic Resonance Imaging (fMRI) and EEG in order to unfold in high spatial and temporal resolutions, respectively the neural modulations induced via T/A EEG-NF. We used real time EEG preprocessing and analysis during the simultaneous T/A EEG-NF/fMRI. A data driven algorithm was implemented off-line to categorize individual scans into responders and non-responders to the EEG-NF practice via a temporal signature of T/A continuous modulation. Comparing the two groups along with their parasympathetic Heart-Rate reactivity profile verified the relaxed state of the responders. Projection of responders variations in the T/A power to the fMRI whole brain maps revealed networks of correlated and inversely correlated activity reflecting induced relaxation, uniquely among responders.keywords{neuro-feedback, simultaneous fMRI/EEG, theta /alpha ratio, limbic network }
机译:数十年的脑电图神经反馈(EEG-NF)实践证明,可以有效地训练人们以选择性地调节其大脑活动,从而有可能改善其性能。 EEG-NF训练的通用协议旨在通过闭环操作来指导人们,该操作从高振幅的α(8-14Hz)转变为高振幅的theta(4-7 Hz)振荡,从而导致更大的theta / alpha比(T / A)。已经显示出诱发EEG振荡的这种转变对于在焦虑和情绪障碍的精神病状态中达到放松状态是有用的。但是,这种做法的临床意义仍然难以捉摸,并被认为具有相对较低的治疗效果,这可能是由于其对独特脑机制的特异性差。当前项目旨在使用功能性磁共振成像(fMRI)和EEG的同步采集,以便在高空间和时间分辨率下展开,分别通过T / A EEG-NF诱导神经调节。我们在同时进行T / A EEG-NF / fMRI的过程中使用了实时EEG预处理和分析。脱机实施了一种数据驱动算法,以通过T / A连续调制的时间特征将单个扫描分为对EEG-NF实践的响应者和非响应者。比较这两组以及他们的副交感性心率反应性曲线,可以证实反应者的放松状态。在功能磁共振成像全脑图上预测响应者在T / A功率中的变化,揭示了反映诱发弛豫的相关和反相关活动网络,在响应者之间是唯一的。\关键词{神经反馈,同时fMRI / EEG,θ/ alpha比,边缘网络 }

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