Topic 10: Faces Flashcards

1
Q

What is Pareidolia?
Where in the brain is involved?

A

The ability to detect faces and patterns in organisms and nature leads to a phenomenon called Pareidolia.

The L+R fusiform gyrus

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2
Q

New borns have preference for … faces
6 month old can …
9 month old (and adults) can …

A

New-born babies show preference for (cartoonish) faces
6 month old infants can discriminate both human and monkey faces
9 months old infants (and adults) can discriminate human faces but lose the ability to discriminate monkey faces

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3
Q

Face perception: features vs configuration
Holistic (configural) face processing

A

Features: Eyes, mouth, nose etc. Each are identifiable parts that vary in subtle ways across individuals
Configuration: the arrangement of face features (spacing, symmetry, position within face outline)
Holistic processing:Involves integrating information from an entire object
There is evidence that faces (but not other objects) are recognized through holistic processing

Do we engage in featural processing or configural processing or both at the same time (holistic processing)?
Are individual features recognised/remembered?
Features are identified regardless of orientation (no inversion effect)
Recognition of face configuration is poor with upside-down faces

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4
Q

Configural processing: Getting a ‘likeness’

A

Configural processing is crucial for getting a ‘likeness’ in a portrait, meaning it is crucial to person recognition.
Face recognition is difficult when configuration is disrupted.
Experiments use “composite faces” (separates top and bottom)
Recognition is dramatically impaired; arguing for importance of configuration processing.
The details of the features are less important.
‘Likeness’ appears to be largely carried by the configuration

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5
Q

What is the identity after effect?

A

A 50:50 mixture of two people’s faces looks like both of them or neither of them in equal measure.
We might expect cells sensitive to the two individuals to be equally active.
Prolonged viewing of one of the two individuals results in cells sensitive to that individual adapting – inhibition over time.
Subsequent viewing of the 50:50 mix results in it appearing more like the other individual.
The neural code has been biased in favour of the “less familiar” or previously un-viewed individual.
Evidence for face-identity cells?
Or evidence of adaptation to local features?

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6
Q

What is the emotion after effect?

A

Adapting to a happy face makes a neutral one look angry
and vice versa.

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7
Q

What is Bruce and Young ‘face model’ A psychological face processing model

A

Two main stages:
Structural encoding occurs first (deals with viewpoint, lighting and visual analysis of visual object)
Extended processing splits to two separate pathways Expression analysisFace recognition
Coding expression (changeable) and coding identity (fixed) use separate pathways.

Familiar and unfamiliar faces are processed differently.

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8
Q

A model of the distributed human neural system for face perception Haxby, Hoffman, and Gobbini (2000)

A

Forward-backward interaction.
LTM influences (early) structural encoding stage.
Emotion expression is more tightly linked to person knowledge (identity) and can also influence structural encoding.

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9
Q

ERP’s (Event related potentials) and faces: N170

A

Put surface electrodes on the scalp; record tiny voltages changes.
Start voltage measurement when a picture onsets.
Do this many times.
Average the signals in a time locked manner.
The resultant waveform is called an ERP.
A strong negative going signal appears about 170ms post-stimulus when faces are presented as stimuli.
This is called the N170 and is an ERP signature for faces.
N170 is more obvious with face pictures than other objects
Assumed to reflect structural encoding because it does not generally vary with
expression
familiarity
viewpoint
But… N170 may be also caused by expertise or simply by highly similar stimuli.
Used different stimuli and recorded ERPs. Real faces and cartoon both yield N170.
Shows that brain processes able to extract “faceness” from abstractions of faces.

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10
Q

fMRI and face processing

A

Basic experiment
Present a series of images in different categories
Face
Houses
Chairs, etc.
Scrambled non-object images
Subtract activation for ‘scrambled’ from each of the object categories.
Find specific areas of brain that are activated more by one category than other.

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11
Q

Right OFA is critical for part based identification
Is it possible to pinpoint the time this is taking place?

A
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12
Q

Repetition Suppression Effect (adaptation)

A

Repetition Suppression (RS): Brain activity reduced for stimulus repetition.
Brain areas that show RS are selectively sensitive to the repeated feature.
Sample study.
Condition 1:
Present different images of the same person making different expressions (ID repetition).
If RS occurs, then the brain area is sensitive to face identity and is not sensitive to facial expression.
Finding: RS is found in FFA and posterior STS.
These areas “see” identity; not expression.
Condition 2:
Present images of different people making the same expression (expression repetition).
If RS occurs, then the area is sensitive to face expression and not sensitive to face identity.
Finding: RS is found in anterior STS. Codes expression, not identity
Conclusion: face identity and face expression are coded by separate networks in the brain.

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13
Q

Prosopagnosia and Capgras delusion

A

Prosopagnosia results in a failure to overtly recognise people even if covert measures suggest recognition.
Ventral route affected.
May include
FFA.
Capgras delusion or syndrome results in a feeling that people are imposters even though they are overtly recognised. Dorsal route affected. May include STS.

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14
Q

How do we read facial expressions?

A

Face muscles and eyes play a key role.
Positive expressions:
Involves muscles near eyes & mouth.
A “genuine” smile (b) involves eyes + mouth
a polite smile (a) involves only the mouth (social conversation technique)

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15
Q

Face expression

A

Face muscles and eyes play a key role.
Negative expressions: eyes, eyebrows, mouth
Different muscles are used for neg versus positive expressions

Reading a face requires attention to eye muscles, mouth position and their effects on nose, cheeks & chin
Eye movements to faces reveal how information is acquired

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16
Q

Problems reading face expressions - amygdala and autism

A

Patients with amygdala damage.
Autism. Autistic children spend more time looking at the mouth than the eyes; typically developing children fixate the eyes more than the mouth. This is apparent at very young ages.
Reduced performance in differentiating faces based on both sex and individual identity in autism
No evidence for face inversion effect (reduced holistic processing)
Reduced brain activation for faces
Correlation between reduced face processing and more ASD behaviours
Difficulty identifying emotions in face stimuli
But comparable levels of face discrimination
Fixating on the eyes or the mouth?

17
Q

Face space

A

A theory of face recognition.
Faces have many features (e.g. nose length, eye separation).
Imagine a multidimensional space (MDS) where each important features has its own axis. This is face space. Each face has a unique location within this MDS.
The average face is at the centre.
The brain represents this MDS via a network of specialized neurons.
Individuals are recognized by how a set of features deviates from the centre (Valentine, 2000). The magnitude of these deviations are coded and then used to identify an individual.

18
Q

Implications of ‘face space’ theory

A

Each person has their own “average face” because the MDS for each face category is developed from personal experience.
The average face determines attractiveness: average = “beautiful”.
‘Who you see is who you like’
Effects of social media? TV? Your own social group?
A powerful idea that may explain aspects of societal divisions & cohesion.
‘Average face’ also determines recognition. Recognition is generally better the further a face is from average.

19
Q

Face (Object) Space Implications

A

Different MDS “spaces” for different categories of faces (or objects), e.g., races, ages, genders.
More experience with diverse faces develops more elaborate MDS. Less experience means simpler MDS.

‘Other Race’ and ‘Other Age’ Effect (ORE, OAE)
Difficulty recognising faces of other races. Note: Between-race differences in faces are smaller than within race differences.
ORE is reduced by experience.
OAE may depend on how intergenerational social groups are.
Social media: Using filters to “improve” selfies.
Excessive viewing of social media enhanced faces should change your ‘face space’, making real faces seem further away from the mean. A dangerous game!
Whose definition of attractiveness is making image enhancement algorithms?

20
Q

Face summary

A

Faces are special to humans. [new-born babies]
Configural processing. [inversion and composite effects]
Identify vs. Expression in face processing.
Face processing models (Bruce & Young; Haxby)
Brain imaging of face processing [face selective brain regions; repetitions suppression]
Atypical face processing [expression processing in autism, atypical brain activation in FFA]
Face space [MDS based on faces we encounter]

21
Q

Visual speech

A

Supports understanding of auditory speech through tracking the articulation movement
Important in noisy environment
Difficulty in Autism (characterised by social/communication differences)
Visual movement
- motion processing
Speech production
- motor processing
Is motion processing or motor production of speech drive visual speech differences in autism

22
Q

Is motion processing or motor production of speech drive visual speech differences in autism?

A

Motion processing per se.(V5/MT) appears to underlie difficulty in visual speech perception in autism