DocumentCode :
3717779
Title :
EEG characteristics related to prediction of what others prefer
Author :
Jonghyeok Park;Taeyang Yang;Hakjin Kim;Sung-Phil Kim
Author_Institution :
Department of Human and Systems Engineering, Ulsan National Institute of Science and Technology, Korea
fYear :
2015
Firstpage :
1790
Lastpage :
1794
Abstract :
Objective: This study aims to investigate EEG characteristics on a single-trial basis when people successfully or errantly predict the preference of others from the rapid evaluation of face images. Background: Empathic processes are associated with dorsal medial prefrontal cortex and right temporoparietal junction areas. Prediction of others´ preference involves emphatic processes. So functional connectivity between prefrontal and right temporoparietal areas would be associated with the others´ preference prediction ability. Methods: Twenty participants (female, average age: 21.86) participated in our others´ preference prediction task using the rapid evaluation of face images. During this experiment, participants´ electroencephalogram was measured. We analyzed spectral band power as well as phase relations between EEG channels. Results: The success and failure trials of the preference prediction task showed differences in phase resetting latency patterns of alpha oscillations between frontal and right posterior regions. To check whether these phase resetting patterns indicated the likelihood of success or failure trials, we changed participants´ response whenever specific phase resetting patterns occurred. This resulted in1.41%pt increase in accuracy when we used an indicator from four pairs (FP2-T4, T4-P4, P4-FP2 and F4-T5) or 16.52%pt decrease in accuracy when we used it from two pairs (Fz-O2 and C3-T6). Conclusion: EEG phase resetting latencies between frontal and right parietal areas could indicate the likelihood of success or failure in a given trial of the others´ preference prediction task.
Keywords :
"Electroencephalography","Face","Atmospheric measurements","Particle measurements","Size measurement","Fourier transforms","Artificial neural networks"
Publisher :
ieee
Conference_Titel :
Control, Automation and Systems (ICCAS), 2015 15th International Conference on
ISSN :
2093-7121
Type :
conf
DOI :
10.1109/ICCAS.2015.7364649
Filename :
7364649
Link To Document :
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