IMotions Unpack Human Behavior



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iMotions EEG Guide 2019
1. Pre-process the data. Procedures vary from study to study, so general recommendations cannot be given. Excellent starting points for finding an optimal sequence of steps are the original papers on frontal asymmetry as well as the books of Luck (2014) and
Cohen (2014).
2. Epoch the data. In this step, the continuous EEG data during each of the advertisements is broken into smaller parts. Scientific studies recommend overlapping epochs with durations of up to 2 seconds. If you test an advertisement of 60 seconds, this will give you sixty 2-second windows which are overlapping by 1 second.


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Taken together, frontal asymmetries of beta and gamma frequency bands can be interpreted with respect to the amount of motivation towards (approach) or away from
(avoidance) a stimulus or mental image. Frontal asymmetry can be extracted from EEG headsets with electrodes located at frontal scalp regions (ideally, F3 and F4), allowing you to analyze short-term changes in motivation over the course of a stimulus presentation.
3. Apply the frequency transformation to each epoch to determine which frequencies underlie the data. You can focus on the power in the beta band
(12 – 25 Hz).
4. Compute the frontal asymmetry for each
epoch:
Higher asymmetry is associated with feelings related to approach behavior while lower asymmetry is associated with feelings related to avoidance.
5. Plot the frontal asymmetry. The procedure generates one asymmetry score per epoch. You can now plot the time-course of the scores to visualize the change in motivation/engagement over the course of the stimulus. Additionally, you can average values across all epochs to get a global frontal asymmetry index.
front left right back
(1) Channel Activity (µV)
(2) Frequency Band Power (µV2)
(3) Frontal Asymmetry Index f4 alpha f3 alpha
© iMotions 2019
ln
( )
Frontal Asymmetry Index = ln
alpha power right F4
(
alpha power left F3
)

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