Offline EEG

We compared resting state EEG recordings of the two groups in 1 min eyes closed (EC) and 1 min eyes open (EO) condition at the pre-, post-NFT and the follow up sessions. Participants sat in a comfortable chair with a backrest and were instructed not to move their eyes during the recordings. EEG data was acquired using a Neuron-Spectrum-4 system (Neurosoft, Ivanovo, Russia) at a sampling rate of 1,000 Hz and with a bandpass filter between 0.1 and 50 Hz. The EEG electrodes were placed in accordance with the international 10–20 system: 18 electrodes were positioned in four regions: left fronto-central (LFC: Fp1, F3, C3, F7, T3,), right fronto-central (RFC: Fp2, C4, T4, F4, F8), left posterior-occipital (LPO: T5, P3, O1), and right posterior-occipital (RPO: T6, P3, O2), and signal was averaged within each area. Two reference electrodes were fixed at M1 and M2. The ground electrode was placed at Fp1 site. Impedance was kept below 5 kΩ. Data was anti-aliasing/low-pass filtered at 30 Hz.

The EEG data were analyzed using WinEEG software (Mitsar Co., St. Petersburg, Russia). Eye-blink artifacts were removed using Independent Component Analysis, then the recording was divided into 4.096-s-long epochs using a Hanning window (epochs were overlapped by 50%). Only records showing an amplitude above 10 μV² were included in the analysis. Analysis of EEG characteristics was carried out according to our previously published approach (Bazanova and Aftanas, 2010). Briefly, individual alpha peak frequency and alpha frequency band limits were determined at every electrode site for every participant using data from the last 30 s of EC and first 8 s of EO conditions. Frequency bands that were decreased in power by more than 20% during the EO vs. EC conditions were selected as individual alpha bands. Frequency showing the highest spectral amplitude within this band was identified as individual alpha peak frequency (IAPF). Lower and upper limits of the band [i.e., theta (TF) and beta (BF) transition frequencies] were determined where EO curve crossed the EC curve closest to IAPF. Theta and beta bands were defined between 3 Hz and TF, as well as between BF and 20 Hz, respectively. These adjusted band ranges were also used for the NFT. The alpha1 and alpha2 sub-bands were also adjusted: the alpha1 ranged from the lower limit to the individual alpha peak frequency, while the alpha2 ranged from the individual alpha peak frequency to the upper limit (Figure ​(Figure2).2). The alpha amplitude suppression magnitude (ASM) in response to eyes open was measured as: ASM = log [(mean alpha power in EC condition – mean alpha power in EO condition) ^* 100%] / mean alpha power in EC condition). Alpha1 to alpha2 ratio (a1/a2) was also calculated.

Identifying individual alpha band and derived metrics based on comparing EEG spectral power in eyes closed (black line) and eyes open (red line) conditions. IAPF, TF, and BF represent individual alpha peak frequency, theta and beta transition frequencies, respectively.