Linear Regression Model

Transcranial Magnetic Stimulation (TMS) is a neuromodulation procedure used to treat psychiatric and neurological disorders. When electroencephalography (EEG), a neuroimaging technique, is applied in conjunction with TMS, the analysis of resting-state EEG activity can be used to quantify functional connectivity (FC) in the brain. These modulations can then be related to a subject’s resting motor threshold (RMT), a baseline parameter in TMS therapy that determines the treatment intensity (dose) of subjects undergoing TMS. Due to the highly variable nature of RMT, previous work has attempted to predict individual values by examining specific EEG nodes suspected to relate to motor activity, and their calculated average FC values in relation to all other nodes. We continue this with an investigation of the relationship of the FC values of a larger set of EEG scalp electrodes to RMT values collected from experimental participants. Through the global and pairwise FC analysis of these nodes, it is shown that the pairwise FC of the scalp electrodes CP2 and P8 in the delta powerband is the strongest predictor of RMT. This could have clinical implications for TMS therapy by providing an accessible way to determine the optimal dosing parameters for treatment.

经颅磁刺激（Transcranial Magnetic Stimulation，简称TMS）是一种用于治疗精神疾病和神经疾病的神经调节程序。当将脑电图（Electroencephalography，简称EEG）这一神经影像技术应用于TMS时，通过分析静息态脑电图活动，可以量化大脑中的功能连接（Functional Connectivity，简称FC）。这些调节与受试者的静息运动阈值（Resting Motor Threshold，简称RMT）相关，RMT是TMS治疗中的基线参数，它决定了接受TMS治疗的受试者的治疗强度（剂量）。由于RMT的高度可变性，先前的研究试图通过检查与运动活动相关的特定脑电图节点及其相对于所有其他节点的平均FC值，来预测个体值。本研究在此基础上，对更大范围的脑电图头皮电极与从实验参与者收集到的RMT值之间的关系进行了调查。通过对这些节点的全局和成对FC分析表明，头皮电极CP2和P8在delta功率频段内的成对FC是RMT的最强预测因子。这可能在TMS治疗中具有临床意义，因为它提供了一种确定治疗最佳剂量参数的便捷方法。