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The choice of different reference electrodes plays an important role in deciphering the functional meaning of electroencephalography (EEG) signals. In recent years, the infinity zero reference using the reference electrode standard technique (REST) has been increasingly applied, while the average reference (AR) was generally advocated as the best available reference option in previous classical EEG studies. Here, we designed EEG experiments and performed a direct comparison between the influences of REST and AR on EEG-revealed brain activity features for three typical brain behavior states (eyes-closed, eyes-open and music-listening). The analysis results revealed the following observations: (1) there is no significant difference in the alpha-wave-blocking effect during the eyes-open state compared with the eyes-closed state for both REST and AR references; (2) there was clear frontal EEG asymmetry during the resting state, and the degree of lateralization under REST was higher than that under AR; (3) the global brain functional connectivity density (FCD) and local FCD have higher values for REST than for AR under different behavior states; and (4) the value of the small-world network characteristic in the eyes-closed state is significantly (in full, alpha, beta and gamma frequency bands) higher than that in the eyes-open state, and the small-world effect under the REST reference is higher than that under AR. In addition, the music-listening state has a higher small-world network effect than the eyes-closed state. The above results suggest that typical EEG features might be more clearly presented by applying the REST reference than by applying AR when using a 64-channel recording.
Sections 2 and 3 dealt exclusively with issues related to means. For many experiments conducted in our field, however, mean values are not the end goal. For example, we may seek to determine the frequency of a particular defect in a mutant background, which we typically report as either a proportion (e.g., 0.7) or a percentage (e.g., 70%). Moreover, we may want to calculate CIs for our sample percentages or may use a formal statistical test to determine if there is likely to be a real difference between the frequencies observed for two or more samples. In other cases, our analyses may be best served by determining ratios or fold changes, which may require specific statistical tools. Finally, it is often useful, particularly when carrying out genetic experiments, to be able to calculate the probabilities of various outcomes. This section will cover major points that are relevant to our field when dealing with these common situations.
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