2026-10-14T05:07:28Z https://www.scidb.cn/oai

10.57760/sciencedb.psych.00742 2025-09-23T16:01:07Z

2025-09-23 The symbolic numerical processing of mathematical anxious individual experimental dataset doi:10.57760/sciencedb.psych.00742 en The EEG data were collected using a Brain Products system with 64 Ag/AgCl scalp electrodes positioned according to the extended international 10–20 system. EEG activity was recorded with FCz as the reference electrode, and offline preprocessing re-referenced the signals to the average of all electrodes. Data were band-pass filtered between 0.01 and 30 Hz with a sampling rate of 1000 Hz. Electrode impedances were maintained below 10 kΩ. The raw data were segmented, and independent component analysis (ICA) was applied to remove artifacts. Segments containing artifacts were rejected, and the remaining trials were averaged for further analysis. Independent component analysis (ICA; Delorme & Makeig, 2004), implemented in EEGLAB, was used to eliminate ocular and muscular artifacts. Segments with amplitudes exceeding ±80 μV were excluded, resulting in the removal of 1.19% of trials. The dataset initially comprised 60 participants. Two participants were excluded due to excessive EEG artifacts (i.e., fewer than 75% of trials retained for analysis). The final sample consisted of 58 participants (32 females; mean age = 21.19 years, SD = 2.16). mathematical anxiety; symptomatic number; cognitive component; ERPs; N170 Liu Jie Yao Xiaohuan Lin Yuefan Yan Peiqing Han Shangfeng RESTRICTED dataset Science Data Bank