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Are faces special?. Brain damage can produce problems in face recognition - even own reflection (Bodamer, 1947) Prosopagnosia usually results from localized.

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Presentation on theme: "Are faces special?. Brain damage can produce problems in face recognition - even own reflection (Bodamer, 1947) Prosopagnosia usually results from localized."— Presentation transcript:

1 Are faces special?

2 Brain damage can produce problems in face recognition - even own reflection (Bodamer, 1947) Prosopagnosia usually results from localized brain damage Prosopagnosia

3 Farah (1990) reported that 94% of prosopagnosia patients had damage in the right hemisphere Damage usually occurs in the ventral occipital or temporal lobes. This led to the idea of a face-specific module that resides in the right ventral occipitotemporal regions of the brain Prosopagnosia

4 The Thatcher Illusion

5

6 Features analysed independently Each feature coded relative to gravity

7 Humans are most attuned to upright faces Yin (1970) studied patients with Right hemisphere damage Recognition test with pictures of faces and houses Items presented upright and upside down R hemisphere patients did as well as normal subjects in recognising inverted faces, but were worse at recognising upright faces The inversion effect

8 Yin’s interpretation = when faces are upright they are processed by special mechanism in the right hemisphere Faces presented upside down do not stimulate this mechanism and are treated like objects The inversion effect

9 First face detection cells were discovered by Gross et al (1972) Monkey temporal cortex Cells did not respond to simple stimuli nor to other complex objects Face detection cells

10 Brain activity - Faces vs. objects FFA – fusiform face area From FMRI in awake humans

11 Brain Asymmetry Brain pathways Visual and motor pathways crossed Sensory input more direct from contra-lateral side Motor output stronger to contra-lateral limbs

12 Brain Asymmetry Brain pathways In other words… The left hemisphere processes information from and controls the right side of the body The right hemisphere processes information from and controls the left side of the body

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14 Face expression More prevalent on left side of the face (80%) Explanation Emotional/motor control bias to right hemisphere rightleft

15 Who is More Masculine?

16 Same faces – different halves

17 Why is Face Perception Biased? rightleft

18 Brain asymmetry in face processing Perceptual bias Judgments of face identity, sex, age, attractiveness are biased to left side of face Explanation Left ½ face projects to observer's right hemisphere Facial identification is a right hemisphere specialization

19 Facial recognition

20 Visual Cues for Face Recognition Features Internal features (eyes, mouth, nose, etc) External features (hair)

21 Visual Cues for Face Recognition Features Internal features (eyes, mouth, nose, etc) External features (hair) Configuration (features have to be in the right place) Familiar and unfamiliar faces External features more important for unfamiliar faces Internal features more important for famous faces

22 Making Facial Averages ++ Warp

23 Which looks most like Jack Nicholson? (The Joker in ‘Batman’, ‘The Shining’) Accurate drawing Caricature exaggerating difference from average 100%

24 Hugh Grant?

25 Recognising Familiar Faces 4 stages: –Form description of seen face –Match to stored representations of known faces –Access semantic information –Recall person’s name

26 26 Image of Face Stored Descriptions of faces (Face Recognition Units) Person Identities Names Face Recognition Description of face Other routes to identity (e.g. Voice, name)

27 Neuropsychological Evidence Prosopagnosic patients: fail to recognise familiar people from their faces (PH, de Haan et al., 1987) Semantic impairments: faces seem familiar but unable to recall semantic info or name (ME, de Haan et al., 1991) Anomia: Faces familiar, semantic info accessed but unable to recall name (EST, Flude et al., 1989)

28 Experimental Evidence Latencies of Decisions to Faces Young, McWeeny, Ellis & Hay (1986a): –Familiarity decisions (774 ms) made faster than semantic decisions (929 ms). Young et al., (1986b): –Semantic decisions (934 ms) made faster than naming (1290 ms)

29 Experimental Evidence Repetition Priming Bruce & Valentine (1985) –Face familiarity decision to a face is faster if it was presented earlier –Long lasting –Within-domain: names don’t prime faces êSuggests existence of representations of faces to which names don’t have access (Face Recognition Units)

30 30 Image of Face Stored Descriptions of faces (Face Recognition Units) Person Identities Names Face Recognition Description of face Other routes to identity (e.g. Voice, name) Repetition Priming

31 Experimental Evidence Interference Effects Young et al. (1986) –Names interfere with face naming but not face classification Bill Clinton ê faces have indirect access to names (via semantics)

32 32 Image of Face Stored Descriptions of faces (Face Recognition Units) Person Identities Name Generation Face Recognition Description of face Other routes to identity (e.g. Voice)

33 Other Meanings We can derive several types of socially important meanings from faces -Identity -age -gender -mood -speech -gaze & attention

34 STRUCTURAL ENCODING FACE RECOGNITION UNITS PERSON IDENTITY NODES NAME GENERATION COGNITIVE SYSTEM EXPRESSION ANALYSIS FACIAL SPEECH ANALYSIS DIRECTED VISUAL PROCESSING Bruce & Young (1986) EXPRESSION ANALYSIS FACIAL SPEECH ANALYSIS

35 Expressions and Identity Expression tasks unaffected by familiarity (e.g. Bruce, 1986; Young et al., 1986) Double dissociation in neurological patients (e.g. Young et al., 1993) ) –Prosopagnosics can often do expressions –Opposite pattern also found Different cells in primate temporal lobe (e.g. Perrett et al., 1984, Hasselmo et al, 1989) Different brain regions in humans (Sergent et al, 1994)

36 Summary Sequence of stages proposed for identification stood up against evidence B & Y (1986) model proposes independent routes for the processing of expression, facial speech and identities

37 Facial attractiveness

38 Peahens prefer peacocks with more elaborate trains Improved growth and survival of offspring of peacocks with more elaborate trains Petrie et al. 1991, Anim. Behav. Petrie 1994, Nature

39 Sexual Dimorphism in Human Faces Masculine facial traits (large jaws, prominent brows) in males are testosterone dependent Testosterone suppresses the immune system and handicaps the individual producing it Only high quality individuals can afford this handicap So masculine face traits should be attractive in males

40 Sexual Dimorphism in Human Faces Feminine facial traits in females are oestrogen dependent Oestrogen is related to health and fertility So feminine face traits should be attractive in females

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42 FeminisedMasculinised Preferred in UK and Japan Perrett et al. 1998, Nature

43 FeminisedMasculinised Preferred in UK and Japan Perrett et al. 1998, Nature

44 Masculine Vs. Feminine Male Faces Masculine male: Dominant Low warmth Bad parent Feminine male: Honest Warm Good parent Perrett et al. 1998, Nature

45 Non-Human Species Preferences for Symmetry Female barn swallows prefer males with symmetrical tail feathers Female zebra finches prefer symmetrical males Møller, 1994, Anim Behav Swaddle & Cuthill, 1994, Nature

46 Symmetry Most features are supposed to be symmetrical: any deviation from symmetry is a reflection of imperfect development Only high quality individuals can maintain symmetric development under environmental and genetic stress Symmetry thus serves as a measure of quality

47 Symmetry Across many species males with low asymmetry have more mating success Symmetric human males report more sexual partners than more asymmetric men Møller & Thornhill 1998 Thornhill & Gangestad 1994

48 Measuring Symmetry Penton-Voak, et al. 2001, Proc Royal Soc Attractiveness ratings of women correlate with measured symmetry r s =.28, p = 0.02, n=66

49 Computer Graphics Which Face is Most Attractive? 15 face pairs – % symmetry preference = number of symmetrical faces selected out of 15

50 Symmetry Manipulation The lower images are made using the left/right average of the 224 feature points (only 4 are Marked here)

51 Symmetry is found attractive in both male and female faces Perrett et al. 1999, Evo Human Behav; Little et al. 2001, Proc Royal Soc Original Symmetric

52 Averageness How similar a face is to a population mean influences its attractiveness Average appearance may indicate diverse mixture of genes With composite images, the more faces that go into an image the more attractive the face becomes Langlois et al., 1991, Psych Science

53 Averageness 3 images 6 images12 images

54 Averageness Little & Hancock, 2002, 3 faces 6 faces 12 faces

55 Averageness Little & Hancock, 2002 OriginalAverage textureAverage shape

56 Averageness

57 General Preferences Femininity, symmetry and averageness appear to be universally attractive traits

58 What you should know… The evidence that face processing may be a specialised module in the brain Bruce & Young’s model of face recognition The biological basis of some attractive features: femininity/symmetry/averageness

59 Next lecture… Friday 3pm – visual deficits & illusions

60 Reading Recognition Are faces special? –Kanwisher (2000) Domain specificity in face perception, Nature Neurosci (see website to download) Cheaters –Gaulin: Place in brain- prospoagnosia –Gaulin:, Kanwisher (2000) Attractiveness Masculinity & averageness –Introduction of Little & Hancock (2002) Brit J of Psychology (see website) Symmetry –Gaulin: p


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