Pattern of EEG voltage and oscillations under stimulation of Mozart's music and white noise for visual learning process

The focus on behavioural data as a prominent indicator for evaluating the effect of stimulation on human cognitive function neglects the understanding of the body's physiological responses. Another remain limitation is the physiological features usually analyzed from learning encode databases. Hence, the current research objectively investigates the correlation of EEG voltage and oscillations pattern from visual learning encoding and recognition stages under stimulation of various circumstances based on EEG patterns with behavioural data. The acquired EEG signal from visual assessment under no-audio and audio circumstances was processed using the Daubhecies wavelet function. The most affected EEG channels were identified according to the peak mean voltage from each electrode channel. The statistical features of mean, standard deviation, peak amplitude, and relative power were obtained from brain rhythms. The evaluation showed that the most affected EEG channel was at the Fp2 electrode with a voltage of about 0.1 V. It was related to the state of subjects that were required to identify the symbol and position of provided assessment. Most EEG features gained the highest value for recognition than the encoding stage, especially the relative power showed a statistically significant value with a p-value < 0.05. This revealed that brain oscillations were higher during recognition than encoding because the brain needed to work hard to retrieve the stored visual information. The behavioural data were parallel and in line with EEG rhythms pattern, where the highest brain oscillation led to better visual score performance. Throughout the evaluation, it was found that the EEG voltage and rhythms pattern during encoding were correlated with recognition and behavioural data.