Identified important EEG channels using recurrent analysis in patients with chronic migraine

This database contains calculated indicators of channel significance based on the application of recurrent analysis to EEG data using the example of the article Runnova A, Selskii A, Emelyanova E, Zhuravlev M, Popova M, Kiselev A, Shamionov R. Modification of Joint Recurrence Quantification Analysis ( JRQA) for assessing individual characteristics from short EEG time series. Chaos. 2021;31(9):093116. doi: 10.1063/5.0055550. For each EEG channel of each subject, the channel significance indicator was separately calculated for all presentations of stimuli in the cognitive test, which are located in the SR folder. The RR_Simple_Hard folder contains the results of calculating significant channels separately for simple presentations - 3 and 4 squares, and complex presentations - 7 and 8 squares. A description of the EEG setup, subjects, and experimental design is provided below. Test subjects volunteered to participate in the experiment. The biomedical data were processed honoring the confidentiality and anonymity of the study respondents. All procedures in studies involving human participants were conducted in accordance with the principles of the Declaration of Helsinki and approved by the Research Ethics Committee at Saratov State Medical University. Written informed consent was given by all participants. The participants were diagnosed in compliance with the diagnostic criteria of the International Classification of Headache Disorders (ICHD-3, beta version). We used the migraine questionnaire to evaluate the data on migraine attacks and disease courses. The exclusion criteria were acute headache, other neurological disorders, and intake of medicines targeting the central nervous system (including medications for migraine prophylaxis) within the preceding 24 h, as well as a Beck Depression Inventory (BDI) score >12 points. The sample comprised 23 subjects. The study group included patients with chronic and recurrent migraine. The subjects had no other serious health problems, or drug or alcohol addictions. Patients were 27–66 years of age. During all experiments, the multichannel EEG data were recorded using the EEG recorder Encephalan-EEGR-19/26 (Medicom MTD, Taganrog, Russian Federation). The data were recorded at a sampling rate of 500 Hz using the conventional monopolar recording technique with two reference electrodes and multiple recording electrodes (n = 31). EEG signals were obtained using special headcaps with prewired Ag/AgCl adhesive electrodes. Two reference electrodes, A1 and A2, were located on the mastoid processes, and the ground electrode (N) was placed above the forehead. EEG signals were filtered using a bandpass filter with cutoff frequencies of 0.5 Hz (high pass filter) and 30 Hz (low pass filter), and a notch filter of 50 Hz. The experiments were carried out in the early afternoon hours at a specially equipped laboratory. During monitoring, the subjects were in a comfortable reclining position in a neurophysiological chair with support for the neck and the back of the head in order to avoid the occurrence of artifacts associated with muscle tension in these areas. The neuropsychological experiment allowed for distinguishing cognitive ERPs. At the beginning and end of the experiment, passive wakefulness was recorded for 10 min each time. In between, the active part of the experiment was recorded for ~40 min. During the active part, short presentations of visual stimuli were delivered in a pseudorandom sequence. For all subjects, the order of stimulus presentation, duration of stimulus presentation, and duration of pauses between stimuli were identical. Each subject observed 350 stimuli. The stimulus was presented for 0.4–0.8 s. After its presentation, during a pause until the next stimulus, the subject saw solely a gray screen. Each visual stimulus per se was an image with a different number of squares (3–8). The task of the subject was to estimate an even or odd number of squares and make a choice by pressing one of two buttons on the remote control.本数据库包含基于递归分析应用于脑电图（Electroencephalogram, EEG）数据所得的通道显著性计算指标，相关方法以Runnova A等人的研究文章为例：Runnova A, Selskii A, Emelyanova E, Zhuravlev M, Popova M, Kiselev A, Shamionov R. Modification of Joint Recurrence Quantification Analysis (JRQA) for assessing individual characteristics from short EEG time series. Chaos. 2021;31(9):093116. doi: 10.1063/5.0055550。针对认知测试中所有刺激呈现场景，本数据集为每名受试者的每一个EEG通道单独计算了通道显著性指标，相关数据存储于SR文件夹中。RR_Simple_Hard文件夹则包含了分别针对简单刺激（呈现3、4个正方形）与复杂刺激（呈现7、8个正方形）的显著通道计算结果。EEG采集设备、受试者信息与实验设计的详细描述如下。 本实验的受试者均为自愿报名参与。所有生物医学数据的处理均遵循研究对象的保密与匿名原则。所有涉及人类受试者的研究操作均符合《赫尔辛基宣言》的相关准则，并经萨拉托夫国立医科大学研究伦理委员会批准。所有受试者均签署了书面知情同意书。受试者的诊断严格遵循《国际头痛疾病分类（International Classification of Headache Disorders, ICHD-3）测试版》的诊断标准，研究采用偏头痛问卷对受试者的偏头痛发作情况与病程数据进行评估。本研究的排除标准包括：24小时内出现急性头痛、其他神经系统疾病、服用作用于中枢神经系统的药物（包括偏头痛预防药物），以及贝克抑郁量表（Beck Depression Inventory, BDI）得分高于12分。本研究最终纳入23名受试者。 本研究组纳入了慢性偏头痛与复发性偏头痛患者。受试者无其他严重健康问题，亦无药物或酒精成瘾史。受试者年龄范围为27~66岁。 所有实验过程中，均采用Encephalan-EEGR-19/26型EEG记录仪（Medicom MTD公司，塔甘罗格，俄罗斯联邦）记录多通道EEG数据。数据以500Hz的采样率采集，采用常规单极记录技术，配备2个参考电极与31个记录电极。EEG信号通过预装预接线氯化银（Ag/AgCl）粘贴电极的专用头帽采集。两个参考电极A1、A2分别置于乳突部位，接地电极（N）置于前额上方。EEG信号经带通滤波器（高通截止频率0.5Hz，低通截止频率30Hz）与50Hz陷波滤波器进行滤波处理。实验均于午后时段在专用实验室中开展。监测过程中，受试者舒适地躺卧于神经生理专用椅中，颈部与枕部均有支撑，以避免该区域肌肉紧张产生伪迹。本神经心理学实验可区分认知事件相关电位（Event-Related Potentials, ERPs）。实验开始与结束阶段，各记录10分钟的静息觉醒状态数据；实验的主动任务阶段时长约40分钟，位于两段静息记录之间。主动任务阶段中，视觉刺激以伪随机序列短时间呈现。所有受试者的刺激呈现顺序、刺激呈现时长与刺激间暂停时长均保持一致。每名受试者需完成350次刺激观测。单次刺激呈现时长为0.4~0.8秒。刺激呈现结束后至下一次刺激呈现前的暂停阶段，受试者仅能看到灰色屏幕。每个视觉刺激本身为包含不同数量正方形（3~8个）的图像。受试者的任务为判断正方形数量为奇数还是偶数，并通过遥控器上的两个按键之一做出选择。