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Effects of Brain Laterality on Decoding Accuracy for Facial Displays of Emotion
Unformatted Document Text:  Effects of Brain 19 .05. Means and standard deviations for each of the six groups (SD males, SD females, MD males, MD females, AD males, AD females) appear in Table 1. Of the six groups, MD females had the highest mean accuracy score. Post-hoc analysis with the Tukey-b test indicated that MD females’ accuracy score was significantly greater than that of MD males (who had the lowest mean accuracy score) and SD males (who had the second-lowest mean accuracy score). Although the main effect of sex was significant, it was rendered uninterpretable by the disordinal nature of the sex-by-hemisphere interaction effect. The main effect of hemispheric dominance was nonsignificant. The fourth research question asked how decoding accuracy would differ among the individual emotions, if at all. To address this issue, we examined decoding accuracy separately for each of the ten emotions. Table 2 reports the percentages of correct decoding for the specific emotions. We computed overall percentages of accuracy as well as the percentages for each of the six groups. For exploratory purposes we also ascertained the most commonly occurring decoding errors for each emotion. Following Leathers and Emigh (1980), we also analyzed participants’ overall decoding accuracy for each individual emotion against chance expectations. In step one of the FMST (used in this study) decoders operating at a chance level would accurately decode one emotion in ten. Based on this expected level of chance agreement, we calculated chi-square values representing the comparison of observed to expected levels of decoding accuracy for each individual emotion. All of the chi-square values were significant. A perusal of Table 2, which reports the percentages of the time that each individual emotional expression was correctly decoded, suggests a clear division between what might be called basic emotions (happiness, sadness, anger, fear, surprise) and complex emotions (interest, bewilderment, determination, contempt, disgust) in terms of people’s abilities to decode facial

Authors: Floyd, Kory. and Mikkelson, Alan.
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Effects of Brain 19
.05. Means and standard deviations for each of the six groups (SD males, SD females, MD
males, MD females, AD males, AD females) appear in Table 1. Of the six groups, MD females
had the highest mean accuracy score. Post-hoc analysis with the Tukey-b test indicated that MD
females’ accuracy score was significantly greater than that of MD males (who had the lowest
mean accuracy score) and SD males (who had the second-lowest mean accuracy score).
Although the main effect of sex was significant, it was rendered uninterpretable by the
disordinal nature of the sex-by-hemisphere interaction effect. The main effect of hemispheric
dominance was nonsignificant.
The fourth research question asked how decoding accuracy would differ among the
individual emotions, if at all. To address this issue, we examined decoding accuracy separately
for each of the ten emotions. Table 2 reports the percentages of correct decoding for the specific
emotions. We computed overall percentages of accuracy as well as the percentages for each of
the six groups. For exploratory purposes we also ascertained the most commonly occurring
decoding errors for each emotion. Following Leathers and Emigh (1980), we also analyzed
participants’ overall decoding accuracy for each individual emotion against chance expectations.
In step one of the FMST (used in this study) decoders operating at a chance level would
accurately decode one emotion in ten. Based on this expected level of chance agreement, we
calculated chi-square values representing the comparison of observed to expected levels of
decoding accuracy for each individual emotion. All of the chi-square values were significant.
A perusal of Table 2, which reports the percentages of the time that each individual
emotional expression was correctly decoded, suggests a clear division between what might be
called basic emotions (happiness, sadness, anger, fear, surprise) and complex emotions (interest,
bewilderment, determination, contempt, disgust) in terms of people’s abilities to decode facial


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