The Time Course of Facial Expression Recognition Using Spatial Frequency Information: Comparing Pain and Core Emotions.

We are able to recognize others' experience of pain from their facial expressions. However, little is known about what makes the recognition of pain possible and whether it is similar or different from core emotions. This study investigated the mechanisms underpinning the recognition of pain expressions, in terms of spatial frequency (SF) information analysis, and compared pain with 2 core emotions (ie, fear and happiness). Two experiments using a backward masking paradigm were conducted to examine the time course of low- and high-SF information processing, by manipulating the presentation duration of face stimuli and target-mask onset asynchrony. Overall, we found a temporal advantage of low-SF over high-SF information for expression recognition, including pain. This asynchrony between low- and high-SF happened at a very early stage of information extraction, which indicates that the decoding of low-SF expression information is not only faster but possibly occurs before the processing of high-SF information. Interestingly, the recognition of pain was also found to be slower and more difficult than core emotions. It is suggested that more complex decoding process may be involved in the successful recognition of pain from facial expressions, possibly due to the multidimensional nature of pain experiences. PERSPECTIVE: Two studies explore the perceptual and temporal properties of the decoding of pain facial expressions. At very early stages of attention, the recognition of pain was found to be more difficult than fear and happiness. It suggests that pain is a complex expression, and requires additional time to detect and process.

Duke Scholars

Author Shan Wang DKU Faculty