Women EEG mu-supression index
Description
Here we try to answer the question if some social factors including self-reported psychological traits (anxiety, empathy level), availability of kids or age are interconnected with the activity of EEG mu-rhythm as a marker of MNS activity. 40 female participants ages 22 to 39 (26 have children, mean age 34 years; 14 have no children, mean age 28 years) took part in this study. Inclusion criteria: right-handedness, ages 21 to 40, up to 3 children, time elapsed since last birth at least 2 years, have not breastfed for more than a year (for women who have children), completed higher education, working at least 20 hours a week, married/living with a partner. Exclusion criteria: diagnosed depression, epilepsy, moderate and severe head injury, alcohol and drug addiction, neurological diseases, taking neuroleptic drugs during the last 6 months. All the participants had completed higher education, worked and lived in Moscow or the Moscow region and were interested in psychology or neuroscience.
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Steps to reproduce
Following the EEG electrodes preparation and reaching of an acceptable signal, the registration of a 32-channel EEG began according to a given scenario with a duration of about 30 minutes. Videos with three demonstrators (a female, a male, a 6-year-old boy) and four types of hand movements were prepared in advance and recorded with the same camera. The following movements were used in the mirroring tasks: clenching a hand, fist-palm motion, moving a ball into a box and clapping hands. The subjects were asked to perform the observed movement synchronously with a demonstrator. The 32-channel EEG was recorded using the BrainAmp DC Amplifier (Brain Products GmbH, Germany) and Ag/AgCl electrodes located in accordance with the International 10–20 system (referent in the Fz position). The data was sampled at 512 Hz; the impedance was maintained below 15 kΩ; a low-pass filter of 70 Hz, a high-pass filter of 1 Hz and a 50 Hz notch filters were used. Subsequent data processing was undertaken by the MNE-Python package (Gramfort, et al., 2013). Previously, all samples for each participant were "stitched" into one array, the data was filtered (low-pass 40 Hz, high-pass 4 Hz), independent components were calculated using the Infomax algorithm ICA. Then a Fast Fourier Transformation (FFT) was used to calculate the spectral power in the range of 8-13 Hz (the mu-rhythm range) separately for each sample, for all independent components. Then the power values of the component at rest with closed and open eyes and at the simple motor task, visual evaluation of the signal and spatial topograms were used for the left-hemisphere mu-rhythm components selection. To estimate the level of mu-rhythm desynchronization or suppression in each experimental task, relative changes in signal power in decibels were calculated: 10LOG (P task/ P baseline), dB.