Neural computation as a tool to differentiate perceptual from emotional processes: The case of anger superiority effect

Cognition

Volumn 110, Issue 3, 2009, Pages 346-357

  Mermillod, Martial ^a   Vermeulen, Nicolas ^b   Lundqvist, Daniel ^c   Niedenthal, Paula M ^d  

^a UNIVERSITÉ CLERMONT AUVERGNE   (France)

^b UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

^c KAROLINSKA INSTITUTE   (Sweden)

^d CNRS   (France)

Author keywords

Anger superiority effect; Cognition; Emotion; Neural Computation; Perception

Indexed keywords

ALGORITHM; ANGER SUPERIORITY EFFECT; ARTICLE; BEHAVIOR; COGNITION; COMPREHENSION; EMOTION; FACIAL EXPRESSION; HUMAN; NERVE CELL NETWORK; PERCEPTION; PRIORITY JOURNAL; SIMULATION; VISUAL STIMULATION;

ALGORITHMS; ANGER; COMPUTER SIMULATION; EMOTIONS; FACIAL EXPRESSION; HUMANS; NEURAL NETWORKS (COMPUTER); PERCEPTION; PHOTIC STIMULATION;

EID: 59649124417     PISSN: 00100277     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cognition.2008.11.009     Document Type: Article

References (26)

1. Abdi H., Valentin D., Edelman B.E., and O'Toole A.J. More about the difference between men and women: Evidence from linear neural networks and the principal component approach. Perception 24 (1995) 539-562
2. Dailey M.N., and Cottrell G.W. Organization of face and object recognition in modular neural networks. Neural Networks 12 7-8 (1999) 1053-1074
3. Dailey M.N., Cottrell G.W., Padgett C., and Adolphs R. EMPATH: A neural network that categorizes facial expressions. Journal of Cognitive Neuroscience 14 8 (2002) 1158-1173
4. De Valois R.L., and De Valois K.K. Spatial vision (1988), Oxford University Press, New York
5. French R.M., Mareschal D., Mermillod M., and Quinn P.C. The role of bottom-up processing in perceptual categorization by 3- to 4-month-old infants: Simulations and data. Journal of Experimental Psychology: General 133 3 (2004) 382-397
6. Hansen C.H., and Hansen R.D. Finding the face in the crowd - an anger superiority effect. Journal of Personality and Social Psychology 54 6 (1988) 917-924
7. Jones J.P., and Palmer L.A. The two-dimensional spatial structure of simple receptive fields in cat striate cortex. Journal of Neurophysiology 58 (1987) 1187-1211
8. Jones J.P., Stepnoski A., and Palmer L.A. The two-dimensional spectral structure of simple receptive fields in cat striate cortex. Journal of Neurophysiology 58 6 (1987) 1212-1232
9. Juth P., Lundqvist D., Karlsson A., and Ohman A. Looking for foes and friends: Perceptual and emotional factors when finding a face in the crowd. Emotion 5 4 (2005) 379-395
10. Lundqvist D., and Litton J.E. The Karolinska directed faces (1998), Karolinska Institute
11. Lyons, M. J., Akamatsu, S., Kamachi, M., & Gyoba, J. (1998). Coding facial expressions with gabor wavelets. In Proceedings of the third IEEE international conference on automatic face and gesture recognition (pp. 200-205). Nara Japan: IEEE Computer Society.
12. Lyons M.J., Budynek J., and Akamatsu S. Automatic classification of single facial images. IEEE Transactions on Pattern Analysis and Machine Intelligence 21 12 (1999) 1357-1362
13. Mareschal D., French R.M., and Quinn P.C. A connectionist account of asymmetric category learning in early infancy. Developmental Psychology 36 (2000) 635-645
14. McClelland J.L., and Rogers T.T. The parallel distributed processing approach to semantic cognition. Nature Reviews Neuroscience 4 (2003) 1-14
15. Mermillod M., Chauvin A., and Guyader N. Efficiency of orientation channels in the striate cortex for distributed categorization process. Brain & Cognition 55 2 (2004) 352-354
16. Mermillod, M., Vuilleumier, P., Peyrin, C., Alleysson, D., & Marendaz, C. (in press). The importance of low spatial frequency information for recognizing fearful facial expressions. Connection Science.
17. Mermillod M., Guyader N., and Chauvin A. Improving generalisation skills in a neural network on the basis of neurophysiological data. Brain & Cognition 58 2 (2005) 246-248
18. Mermillod M., Guyader N., and Chauvin A. The Coarse-to-fine Hypothesis Revisited: Evidence from neuro-computational modeling. Brain & Cognition 57 2 (2005) 151-157
19. Öhman A., Lundqvist D., and Esteves F. The face in the crowd revisited: A threat advantage with schematic stimuli. Journal of Personality and Social Psychology 80 3 (2001) 381-396
20. Pothos E.M., and Close J. One or two dimensions in spontaneous classification: A simplicity approach. Cognition 107 2 (2008) 581-602
21. Purcell D.G., Stewart A.L., and Skov R.B. It takes a confounded face to pop out of a crowd. Perception 25 9 (1996) 1091-1108
22. Rumelhart, D. E., Hinton, G. E., & McClelland, J. L. (1986). A general framework for parallel distributed processing. In D. E. Rumelhart, J. L. McClelland, and the PDP Research Group (Eds.), Parallel distributed processing: Explorations in the microstructure of cognition (Vol. 1). Foundations. Cambridge, MA: MIT Press.
23. Russell J.A. Is there universal recognition of emotion from facial expressions? A review of the cross-cultural studies. Psychological Bulletin 115 (1994) 102-141
24. Valentin D., and Abdi H. Can a linear autoassociator recognize faces from new orientations?. Journal of the Optical Society of America, Series A 13 (1996) 717-724
25. Wiskott L. Phantom faces for face analysis. Pattern Recognition 30 6 (1997) 837-846
26. Zhang, Z., Lyons, M., Schuster, M., & Akamatsu, S. (1998). Comparison between geometry-based and gabor-wavelets-based facial expression recognition using multi-layer perception. In Proceedings of the third IEEE international conference on automatic face and gesture recognition (pp. 454-459). Nara Japan: IEEE Computer Society.