Login / Signup

Perceptual integration and the composite face effect.

Chang Hong LiuAndrew W YoungGovina BasraNaixin RenWenfeng Chen
Published in: Quarterly journal of experimental psychology (2006) (2020)
The composite face paradigm is widely used to investigate holistic perception of faces. In the paradigm, parts from different faces (usually the top and bottom halves) are recombined. The principal criterion for holistic perception is that responses involving the component parts of composites in which the parts are aligned into a face-like configuration are disrupted compared with the same parts in a misaligned (not face-like) format. This is often taken as evidence that seeing a whole face in the aligned condition interferes with perceiving its separate parts, but the extent to which the effect is perceptually driven remains unclear. We used salient perceptual categories of gender (male or female) and race (Asian or Caucasian appearance) to create composite stimuli from parts of faces that varied orthogonally on these characteristics. In Experiment 1, participants categorised the gender of the parts of aligned composite and misaligned images created from parts with the same (congruent) or different (incongruent) gender and the same (congruent) or different (incongruent) race. In Experiment 2, the same stimuli were used but the task changed to categorising race. In both experiments, there was a strong influence of the task-relevant manipulation on the composite effect, with slower responses to aligned stimuli with incongruent gender in Experiment 1 and incongruent race in Experiment 2. In contrast, the task-irrelevant variable (race in Experiment 1, gender in Experiment 2) did not exert much influence on the composite effect in either experiment. These findings show that although holistic integration of salient visual properties makes a strong contribution to the composite face effect, it clearly also involves targeted processing of an attended visual characteristic.
Keyphrases
  • mental health
  • magnetic resonance imaging
  • drug delivery
  • deep learning
  • gold nanoparticles
  • machine learning
  • convolutional neural network