There has been a great deal of progress in understanding how complex visual objects, in particular, human faces, are processed by the cortex. At the same time, sophisticated neural network models have been developed that do many of the same tasks required by these cortical areas.
The aim of this proposal is to extend these simplifying models toward an understanding of the extent to which facial expression processing is """"""""universal,"""""""" versus the extent to which it is experientially mediated. In particular, we focus upon elucidating the following issues through modeling: (1) Understanding cultural variation in expression recognition: contrasting the influence of other race effects versus cultural display rules; (2) Understanding how we become face """"""""experts."""""""" Why does the same region of the Fusiform Gyrus get recruited for faces as well as other visual tasks we may be expert in? (3) Understanding the dynamics of facial expertise: How are eye movements planned for efficient feature extraction? In each case, we have developed or will develop a neurocomputational model of the process. Cultural and other-race experience will be modeled by the composition of the internal representations and the training signals of our model. Facial expertise is modeled as a combination of different task requirements (varying the level of categorization required) and length of training. Eye movement modeling will be based on novel and traditional methods for extracting the informative locations on the face for each task. We will develop a theoretical criterion for saccade targets the face based upon mutual information between feature values and the categories required for the task. We also will be performing behavioral experiments to test the predictions of our model. The project will shed light on the way faces are represented and processed by the brain, and should give insights into the problems underlying deficits in face processing such as prosopagnosia.
| Hsiao, Janet H; Cipollini, Ben; Cottrell, Garrison W (2013) Hemispheric asymmetry in perception: a differential encoding account. J Cogn Neurosci 25:998-1007 |
| Nelson, Jonathan D; McKenzie, Craig R M; Cottrell, Garrison W et al. (2010) Experience matters: information acquisition optimizes probability gain. Psychol Sci 21:960-9 |
| Dailey, Matthew N; Joyce, Carrie; Lyons, Michael J et al. (2010) Evidence and a computational explanation of cultural differences in facial expression recognition. Emotion 10:874-93 |
| Hsiao, Janet H; Cottrell, Garrison W (2009) Not all visual expertise is holistic, but it may be leftist: the case of Chinese character recognition. Psychol Sci 20:455-63 |
| Kanan, Christopher; Tong, Mathew H; Zhang, Lingyun et al. (2009) SUN: Top-down saliency using natural statistics. Vis cogn 17:979-1003 |
| Hsiao, Janet Hui-wen; Cottrell, Garrison (2008) Two fixations suffice in face recognition. Psychol Sci 19:998-1006 |
| Zhang, Lingyun; Tong, Matthew H; Marks, Tim K et al. (2008) SUN: A Bayesian framework for saliency using natural statistics. J Vis 8:32.1-20 |
| McCleery, Joseph P; Zhang, Lingyun; Ge, Liezhong et al. (2008) The roles of visual expertise and visual input in the face inversion effect: behavioral and neurocomputational evidence. Vision Res 48:703-15 |
| Barrington, Luke; Marks, Tim K; Hsiao, Janet Hui-wen et al. (2008) NIMBLE: a kernel density model of saccade-based visual memory. J Vis 8:17.1-14 |
| Tong, Matthew H; Joyce, Carrie A; Cottrell, Garrison W (2008) Why is the fusiform face area recruited for novel categories of expertise? A neurocomputational investigation. Brain Res 1202:14-24 |
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