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Fig. 11
Example of
pictures from IAPS and the
series of stimuli (Huang
et al.,
2008
)
C and scientific creativity questionnaire C 2 h after that (the tasks and question-
naires are shown in Huang et al.,
2008
).
There are two parts to the EEG analysis in Huang, et al.
s research (
2008
). At
first, the researchers analyzed the EEG data to make sure that the participants
'
'
emotional responses really were induced. The EEG data from task C (neutral affect)
was the baseline of the EEG waveform for individual participants. If the partici-
pants showed more positive than neutral affect, the power value of the alpha
frequency band would be higher. In contrast, if the participants showed more
negative than neutral affect, the power value of the alpha frequency band would
be lower (Huang et al.,
2008
). The data which did not reflect the expected emotions
were rejected. Second, the data which were accepted were analyzed to identify
changes in the power value of the theta frequency band. The theta frequency band is
always identified as the indicator to assess creativity.
The results of the research by Huang et al. (
2008
) showed that, compared to the
natural emotions, scientific creativity is improved with both positive and negative
emotions. Furthermore, the performance of scientific creativity is better with
negative than with positive affect. The most important contribution of their research
is that they used EEG data to ensure that the participants were really inducing the
assigned affect before administering the scientific creativity questionnaires. An
example of the EEG data is shown in Fig.
12
.
Figure
12
shows an example of EEG data with neutral and positive affective
reflection. The left figures indicate the brain activity of natural affect, while the
right figures show the brain activity of positive affect. The criterion of inducing
positive affect is brain activity in the theta band of the frontal lobe.
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