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Rule-based or information-integration category: processing of the self-face

  • Ronghua Zhang
  • Xiaofeng Ma
  • Aibao ZhouEmail author
Research Article
  • 14 Downloads

Abstract

This study investigated the differences between categorizing the self-face and other faces. Additionally, the study aimed to determine whether self-face categorization is consistent with dual-system categorization, such as in the competition between verbal and implicit systems (COVIS) model, or whether the self-face uses different categorizing methods than those used with other faces. The experiment adopted a dual-task paradigm to examine how participants complete rule-based/information-integration categorization tasks of the self-face/other faces and their method of processing when a numerical Stroop task was introduced. Results indicated that participants processed the self-face better than other faces in rule-based categorization, and there was no significant difference between categorization of the self-face and other faces during a single or dual task. This suggests there is a self-processing advantage in classification tasks; however, categorization based on face stimuli is not consistent with the COVIS model. Face categorization has a self-advantage effect, and categorization of human faces is distinctive from other types of categorization.

Keywords

Categorization Face recognition Competition between verbal and implicit systems Dual-task paradigm 

Notes

Funding

This study was supported by the Chinese Ministry of Education of Humanities and Social Science Project (No. 17YCJ190030) and the National Natural Science Foundation of China under grant No. 31860285.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

References

  1. Ashby FG, Maddox WT (2005) Human category learning. Annu Rev Psychol 56(5):149–178CrossRefGoogle Scholar
  2. Ashby FG, Alfonso-Reese LA, Turken AU, Waldron EM (1998) A neuropsychological theory of multiple systems in category learning. Psychol Rev 105(3):442–481CrossRefGoogle Scholar
  3. Brédart S, Delchambre M, Laureys S (2006) One’s own face is hard to ignore. Q J Exp Psychol 59(1):46–52CrossRefGoogle Scholar
  4. Diamond R, Carey S (1986) Why faces are and are not special: an effect of expertise. J Exp Psychol Gen 115(2):107–117CrossRefGoogle Scholar
  5. Kanwisher N, Woods RP, Iacoboni M, Mazziotta JC (1997) A locus in human extrastriate cortex for visual shape analysis. J Cogn Neurosci 9(1):133–142CrossRefGoogle Scholar
  6. Keenan JP, Mccutcheon B, Freund S, Gallup GG, Sanders G, Pascual-Leone A (1999) Left hand advantage in a self-face recognition task. Neuropsychologia 37(12):1421–1425CrossRefGoogle Scholar
  7. Keyes H (2012) Categorical perception effects for facial identity in robustly represented familiar and self-faces: the role of configural and featural information. Q J Exp Psychol 65(4):760–772CrossRefGoogle Scholar
  8. Ma Y, Han S (2010) Why we respond faster to the self than to others? An implicit positive association theory of self-advantage during implicit face recognition. J Exp Psychol Hum Percept Perform 36(3):619CrossRefGoogle Scholar
  9. Maddox WT, Ashby FG (2004) Dissociating explicit and procedural-learning based systems of perceptual category learning. Behav Proc 66(3):309–332CrossRefGoogle Scholar
  10. Maddox WT, Ashby FG, Ing AD, Pickering AD (2004) Disrupting feedback processing interferes with rule-based but not information-integration category learning. Mem Cognit 32(4):582–591CrossRefGoogle Scholar
  11. McKone E, Davies AA, Darke H, Crookes K, Wickramariyaratne T, Zappia S et al (2013) Importance of the inverted control in measuring holistic face processing with the composite effect and part-whole effect. Front Psychol 4:33CrossRefGoogle Scholar
  12. Nosofsky RM, Kruschke JK (2002) Single-system models and interference in category learning: commentary on Waldron and Ashby (2001). Psychon Bull Rev 9(1):169–174CrossRefGoogle Scholar
  13. Richler JJ, Cheung OS, Gauthier I (2011) Holistic processing predicts face recognition. Psychol Sci 22(4):464–471CrossRefGoogle Scholar
  14. Sui J, Zhu Y, Han S (2006) Self-face recognition in attended and unattended conditions: an event-related brain potential study. NeuroReport 17(4):423–427CrossRefGoogle Scholar
  15. Tanaka JW, Gordon I (2011) Features, configuration, and holistic face processing. In: Oxford handbook of face perception.  https://doi.org/10.1093/oxfordhb/9780199559053.013.0010
  16. Tanaka JW, Kiefer M, Bukach CM (2004) A holistic account of the own-race effect in face recognition: evidence from a cross-cultural study. Cognition 93(1):B1–B9CrossRefGoogle Scholar
  17. Waldron EM, Ashby FG (2001) The effects of concurrent task interference on category learning: evidence for multiple category learning systems. Psychon Bull Rev 8(1):168–176CrossRefGoogle Scholar
  18. Young SG, Hugenberg K, Bernstein MJ, Sacco DF (2011) Perception and motivation in face recognition: a critical review of theories of the cross-race effect. Personal Soc Psychol Rev 16(2):116–142CrossRefGoogle Scholar

Copyright information

© Marta Olivetti Belardinelli and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of PsychologyNorthwest Normal UniversityLanzhouChina

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