Theory L3 - Face Processing Flashcards
What kind of information do we extract from faces?
INVARIANT information - identity, race, sex - these do not change.
VARIABLE information - age, health, attractiveness, emotional state, attentional focus - these are subject to change.
STATIC and DYNAMIC cues
What kinds of CUES can we extract from faces?
STATIC cues - nose shapes, distance between eyes
DYNAMIC cues - emotional expressions, gaze direction (can lead to attitude)
What is the evidence for face processing being innate?
- Newborns prefer to look at schematic faces than concentric circle patterns (Fantz, 1963) - they like face stimuli more than anything else.
- Newborns (~9mins) track face-like patterns more than control patterns containing rearrangements of the same features.
- Investigated using the preferential looking paradigm - the longer a baby looks at a stimulus = the more interested they are.
great for adaption :)
What is the Bruce & Young (1986) Model?
- Faces are processed holistically and orientation- specifically (structural encoding)
- Familiar faces are recognised by matching with stored FRUs (face recognition units), gaining semantic information from PINs (personal identity nodes)–> name generation
- Unfamiliar faces are processed via directed visual processing
if you encounter someone once or more than once, you will begin to develop a FRU…
Supporting the Bruce & Young Model, what is the evidence that information for facial recognition is stored separately from names?
- People often experience a ‘tip of the tongue’ state for someone’s name. You can get someone’s semantic info without knowing their name. It’s never the other way round.
- Naming a face takes longer than determining whether the face belongs to an actor or politician (semantic category discrim. faster than name retrieval).
What is evidence supporting Bruce & Young Model?
- Common facial recognition errors involve not recognising a person, recognising a person but not remembering their name, misidentifying a person and feeling familiarity for a person but not recognising identity.
Thus - all this information must be stored seperately. - Also, T-O-T- phenomenon for someoen’s name, despite recognising them.
- Naming a face takes longer than category discrimination (Semantic info)
What model is the competitor for bruce & young model?
Interactive Activation Model
What is the interactive Activation and competition model?
- Dev. by Burton et al., 1990
- based on Bruce & Young Model
- Adopts connectionist architecture, and does not attempt to explain how faces are recognised (eg. starting with names or FRUs.)
- Starts with Facial-recognition units and Name recognition Units > PINs > Semantic info units
What is configural processing?
This is when we process faces configurally - eg. the spatial interrelationship between features.
processes faces as a whole, not by their features.
This is how adults/experts perceive faces.
What is featural processing?
This is when we process faces using their featural information - eg. the local information contained in individual parts - shape of nose, colour of eyes.
This is how children often process faces, and how everyone processes non-face objects,
Why is facial processing difficult?
Because faces always have the same arrangement - same basic information - we need to make within-category discriminations.
Faces differ configurally and featurally.
What have composite faces shown us about facial processing?
It is evidence that we process faces configurally/hollistically.
- We take longer to identify the top half of a composite face when it is aligned. When mis-alligned, we can identify featurally.
- Decisions about whether composite faces are the same person are faster when it is alligned - when we configurally process.
what has the face inversion effect shown us about facial processing?
When we view an inverted face the up-side down, it is not grotesque.
But, when we view an inverted face the right way up, it looks grotesque.
This is because when faces are UPSIDE DOWN we cannot process CONFIGURALLY
but when it is turned up right we process CONFIGURALLY and see that the features are oriented incorrectly.
What did Langer et al. (2010) show us about face processing?
- we are able to detect CONFIGURAL changes in UPRIGHT faces - eg. eye spacing
- we are better able to detect FEATURAL changes in UPSIDE DOWN faces - because we cannot engage in configural processing.
What is the difference in the processing of a person’s sex and identity?
Cloutier et al, 2015
showed that judgements about a model’s sex were not affected by inversion - so they do not need configural processing
judgements about a model’s identity are sensitive to inversion - indicating configural processing
Can configural processing occur with non-human faces?
Yes.
Expertise lead to configural processing of non human faces.
Eg - dog breeders rely on configural processing to identify individual dogs. Face inversion disrupts recognition of individual dogs by expert breeders.
if you’re not a expert - you will process it featurally.
Based on this, it was thought that face processing is controlled by brain regions involved in making discriminations between structurally similar category exemplars - domain generality instead of domain specificity.