## 2 Materials and Methods
### Induced Oscillatory Activity Analysis  
Using the BioSemi ActiveTwo system, 64 channels of scalp EEG data were captured throughout the training tasks at a sampling rate of 2048 Hz using the international 10-20 configuration. For the induced oscillatory activity analysis, 64-channel EEG data from 5 subjects in the Experimental Group and 10 subjects in the Placebo Group were collected and analyzed. EEG data from the other 5 subjects in the Experimental could not be used since the full 64-channel single-trial data were not saved for later off-line analyses in the version used for those subjects, while the behavioral and single-trial EEG classification analysis could be applied to all the 20 subjects.  
A template-matching approach was utilized to decode the attended stream from single-trial EEG signals and deliver neurofeedback to the Experimental Group [13]. EEG recordings from linked mastoids were averaged and re-referenced to the front-central channels (Fz, FCz, FC1, FC2, and Cz). After baseline correction and bandpass filtering between 1 and 9 Hz, EEG data were compared to two template waveforms created from grand-average cortical evoked responses to the single \"up\" and \"down\" streams while passive listening in silence. The attention was decoded by choosing the template that has a larger correlation coefficient with the single-trial EEG data. The fixation cross was then moved upward or downward on the computer screen to provide visual feedback in response to the detection of attention on the \"up\" stream or \"down\" stream, respectively.  
The spectrograms were processed from the resampled EEG signal per channel and trial based on a 256-sample fast Fourier transform with a period of 64 samples and an overlap of 63 samples in 256 Hz sampling rate. These spectrograms were categorized into \"up\" or \"down\", and weeks. The paired t-tests between \"up\" and \"down\" every week were taken. Furthermore, the paired t-test between \"up\"-\"down\" in week 4 and \"up\"-\"-\"down\"  
Figure 1: An example of the neurofeedback training’s trial structure assigned to the Experimental Group. An attend-_down_ case is shown [11].  
in week 1 were taken to explore the difference in the attentional modulation. In addition, the cluster-based permutation analysis was performed to find the significantly different clusters of attentional modulation between week 4 and week 1 for the Experimental Group and the Placebo Group [38]. To observe the difference between week 4 and week 1 in each alpha and beta oscillation, we selected frequency bands for each alpha and beta range (8-13 Hz and 24-29 Hz, respectively), set the minimum cluster length as around 50 ms, and set the p-values for the t-test as 0.05 in the spectrograms. For the Experimental Group and the Placebo Group, the cluster-based permutation analysis was performed separately in each alpha and beta band and the obtained clusters implied the statistically significant difference between week 4 and week 1 for each group.  
Source localization is needed to analyze temporal dynamics with the estimated source spatial distribution because sensor data in some channels may not sufficiently capture the geographic distribution of neural sources and the temporal dynamics of ERP components [39]. The inverse operator was estimated using minimum norm estimation (MNE) [40; 41; 42] based on assumptions of multiple sparse priors [43] on an average template brain in order to project the sensor space data into source space. By using the inverse operator, source space time courses of ERPs were acquired over all cortical voxels in both hemispheres. As a method of noise normalization, they were projected onto the cortical maps to create dynamic statistical parametric maps (dSPMs) [44]. Each cluster for beta and alpha waves in the preparatory period was selected and all voxels were averaged during each selected cluster for beta and alpha waves. The timely averaged voxels were presented as snapshots of the clusters for the Experimental Group and the Placebo Group.