# A Wireless EEG System for Neurofeedback Training
## 4 Materials and Methods
### NF-EEG Procedure  
The developed system was validated via a 12-channel EEG neurofeedback study in a school environment through research on typical-reading children and children with DD (Figure A3). Neurofeedback via evoked EEG oscillations can improve the performance of a child with DD, compensating for their magnocellular deficit during the visual LSF illusion task [2].  
The real-time z-score neurofeedback device (qEEG z-NF) provided a 24-bit conversion with a 256 Hz sampling frequency and second-order notch filtering for removing the powerline noise at 50 Hz, as well as an EEG bandwidth of 0.1-70 Hz with a type II Chebyshev filter. The time-locked trials during the presentation of the flicking Gabor gratings (\(\sim\)250 ms) were frequency-decoded via a Morlet wavelet (MATLAB) in \(\delta\): 3-4, \(\theta\): 4.5-8, \(\alpha\): 8.5-12, \(\beta\): 13.5-20, 20.5-30, and \(\gamma\): 30.5-48, 52-70 Hz. The qEEG z-NF \(\alpha/\theta\) scores were determined from the \(\alpha\) and \(\theta\) frequency peaks assessed in each hemisphere for eight brain regions (Table 3). A mean baseline with a duration of 2.5 min at the first experimental feedback-free session with the eyes opened for each child was applied as a measure to define the z-score's threshold in the software norm data [34]. The absolute qEEG standardized index ( | prior z-score | \(\geq\) 1.0) was used as the target z-score, defined by logarithmic transformation of the qEEG data features to obtain the optimal mean and standard deviation. It minimized the influence of variables affecting the EEG characteristics by tending toward a standard normal distribution with a mean of zero and variance of one. Several brain areas (Table 3) and their abnormal \(\alpha/\theta\) scores were enrolled as candidates for feedback in studies of dyslexia [6; 7]. During the sessions, the z-scores for the seven bands for the selected channels were computed moment by moment during the stimulus duration. Their absolute pre-z-scores \(\geq\)1.0 were highlighted as being the targeted z-scores by site and frequency.  
The z-\(\alpha/\theta\) scores were either up- or down-trained to approximate to the normal score. This allowed specific underlying areas of the brain to be targeted for training and could lead to a reduced number of sessions. The NF latency, or the delivery time of the EEG trial to the observed qEEG-z-NF sign on the monitor, determines the schedule of reinforcement so that it significantly affects the outcome of the operant conditioning [35]. The child received positive feedback as a visual cue when the z-scores fell within a \"target window\" (\(\pm\)1 standard deviation of the normative mean) and the z-score that was outside of the target window moved toward the target window. The visual feedback was marked with a green sign when the z-score was above the threshold, and the mark was a red sign when the z-score was under the threshold. The qEEG z-NF protocol was performed for 10 min (for each brain hemisphere) in 6 sessions twice for the DD group before a visual perceptional training procedure [33] and 4 months after that, and one procedure was carried out for the controls. The mean pre- and post-assessment qEEG z-NF sessions was 12. Afterpreprocessing, the average artifact-free trial number was 772 epochs of data for each group or condition.  
The protocol included (1) the left-hemispheric \(\theta\) decrease and \(\alpha\)-wave augmentation at regions adjacent to the reading functional network (left inferior frontal, posterior superior temporal, ventral occipitotemporal, and middle occipital cortex) and (2) the compensated left-hemispheric \(\alpha/\theta\) score increase and right-hemispheric \(\alpha/\theta\) decrease in brain laterality for the dyslexic group from reducing the slow \(\theta\) waves to reach a new learning information level from the brain.