It is important to consider how each step in our MUSE analysis tree is manipulating our data and which settings will allow us to get the best picture of the data. Here, we show the effects of different analysis settings using an Oddball data set with ~1100 participants.
Effects of Re-Referencing
Implicit referencing (to FPz)
Re-reference all channels to AF7 and AF8
Re-reference all channels to TP9 and TP10
Re-reference TP9 and TP10 to AF7 and AF8
Re-reference AF7 and AF8 to TP9 and TP10
Effects of Filtering
To show the effect of increasing the filter frequency in our data analysis, we analyzed the same data set of 1177 MUSE participants with different high notch filters. As you can see, we lose more participants as filter frequency increases. This is due to the higher volume of channel artifacts passing through the filter and decreasing data quality.