Cognitive Neuroscience Lecture 9: Face and Scene Recognition

*L9: Face and Scene*
Recognition

The dress: color constancy

Specialization in ventral occipital cortex

Sub-regions specialized for particular visual
categories

o
E.g. faces, places, words, bodies, other ppl’s
thoughts

Face vs. Scene Area

Fusiform Face Area (FFA): **right fusiform gyrus**: Faces>scenes

Parahippocampal place area (PPA):
Scenes>faces

PPA is superior and medial to FFA

Fusiform & Parahippocampal gyrus: ***WHICH OF THESE DO WE NEED TO***
KNOW?

Fusiform: lateralish; right ffa.

Parahippocampal: medialish

“If neuroimaging is the answer, what is the question?”

It’s not good enough to just put a bunch of people
thru an fMRI during a task and then retroactively assign meaning to the
observed activated parts

You should have targeted question about targeted
area

Useful types of imaging studies:

Characterization of a single neuron’s responses

o
What happens with one vs another

fMRI study on Face

o
Kanwisher FFA paper most successful empirical
fMRI paper (not method/survey paper)

o
Studied macaque temporal lobe

§
Showed cells that specifically responded to
faces, not scrambled faces or other obj

o
Humans lose ability to recognize faces but not
other objs

§
Prosopagnosia

o
Human fusiform gyrus was implicated in face in
earlier PET studies

§
They gave it a catchy name

Background: fusiform gyrus activated for faces,
but control stim weren’t controlled for

Question: is processing of faces distinct from
processing of obj when other confounds are eliminated?

Face localizer scans

a.
Faces vs objs.

b.
Block design (faces, fixation, objs, fixation)

c.
Higher during face blocks

d.
**Subtraction**
method**: faces – objs = face specific area**

ID ROI in each individual

a.
Is there a place in each individual that
responds more to faces than obj?

b.
Is this place the same in all subjects?

c.
yes in 12/15 subjects

Test alternative hyps in ROIs: low level diffs,
exemplars, animate?

a.
Could be that FFA is for any **low-level feature differences** (overall
contrast, luminance, shape?)

i.
If FFA is truly face selective, it should
respond more to faces than **scrambled**
faces

ii.
This would mean it’s not responding just to
anything with differences in luminance/contrast

iii.
Block design of Scrambled vs Intact faces shows
it does

b.
Could also be that FFA is for anything that is **exemplar** of a category

i.
Faces are exemplars of a face category but there
are multiple basic-level category of objects

ii.
If FFA is truly face selective, it should respond
more to faces than houses even though individual **houses**, like faces, are exemplars within a category of similar objs

c.
Could be that FFA is for anything **animate**

 i.
If FFA is truly face selective, it should
respond more to faces than **hands**

 ii.
It does (block face vs. hands)

iii.
What if it’s just for anything that requires
more attention?

iv.
When 1 back task forced attention to hands, it
still didn’t light up for handsà
not attention

Conclusions

A part of **right**
fusiform gyrus **is preferentially active during face viewing**

“faces are special”à not just another stim

Why was this paper so successful?

Discovered area that became hugely studied

Goal was not just localization but a deeper
understanding of brain activation patterns

Theoretically driven

o
“are faces special”

o
Relates well to other lit

Unambiguous

o
Good controls

Beginning of controversy

o
Category specificity

o
Nature vs. nurture

At what level does the brain represent categories?

Many more questions…viewpoint, ID vs appearance,
facial expression, facial parts, “special”

**fMRI adaptation:** what
counts as the same in the brain?

If you show a stim twice in a row, you get a
reduced response the second time

fMRI adaptation/attenuation

o
“different” trial: high response both times

o
“same” trial: low response second time

o
When you do it a second time, neurons are tired
and you get less activity if you do the same thing twice (same neurons
activated)

Why is adaptation useful?

o
Now we can ask what it takes for stim to be
considered “Same”

o
E.g. viewpoint

Repeated individual, diff viewpoint

o
Possibility 1: **viewpoint specificity** (Area codes face as diff when viewpt changes;
high response)

o
Possibility 2: **viewpoint invariance** (area codes face as same despite viewpt
change)

Results

o
Identical<Translation=size<rotation<different
face

But is it ID of faces or physical appearance?

o
Test Maggie vs. Marilyn Monroe: facial identity

o
Identicalà
repetition, fMRI adaptation

o
Within: Physical different, identity
repeated…will it be treated as identical or between?

§
Physical difference % is same in within and
between, (30% in both cases) but in “between” it crosses identity boundary
while in “within” it does not

o
Within is more similar to identical than to
between

§
Suggests that FFA codes for identity

o
Within behaves similar to identical in FFA, but
within behaves similar to between in OFA

§
OFA doesn’t code for identity; codes for
PHYSICAL changes

o
**Identity**
in rFFA, physical in OFA

Facial expressions

o
Superior temporal sulcus (right below superior
temporal gyrus)

o
2 hypotheses: categorical (discrete) and graded
(continuous)

o
Facial expression & emotion in superior
temporal sulcus

§
**Left STS:**
graded

§
**Right**
STS: categorical (clusters)

Facial Parts

o
TMS à
virtual lesion, test causality

§
FFA is too medial for TMS

o
Occipital face area (OFA)

o
Same or different parts?

o
If you disrupt right OFA, it gets fewer correct
than control

o
Facial parts processed early (before 100 ms of
presentation) in OFA

§
Possible because TMS has higher temporal res

Are faces special, really?

o
We are all **experts**
on faces

o
Car experts had FFA active for cars

o
Bird experts had FFA active for birds

o
Can you train people to be experts and see if
FFA activates? YES (e.g. greeble)

o
However **face-like**
isinnate **(infants look longer**
at faces)

§
Experience also important though

§
Prefer familiar/female/same race (mediated by
exposure though)

Monkey deprivation study: is the preference for
faces innate?

o
Infants raised by humans & deprived of face
exposure

o
Only exposed to obj

o
Initial exposure to either human OR monkey face

o
After 1 month: both

o
Before exposure, monkeys preferred
humans&monkeys in photos over objects

§
Goes against expertise

o
Suggests **experience-independent**
ability for face processing **(innate)**

**Summary:** At what level does brain
represent categories?

o   What happens if you change
viewpoint?

§  Sensitive to viewpoint changes
(rotation)

o   Is it ID or physical appearance?

§  Identity in rFFA

o   How about facial expressions?

§  Facial expressions in STS (left
= graded and right = categorical)

o   How about facial parts?

§  Facial parts processed early in
OFA

o   Are faces special, really?

§  Yes and no (innate [monkeys] and
can be learned [greeble])

**Category selectivity**
in Ventral Visual Cortex

Parahippocampal cortex: **Parahippocampal Place Area (PPA)**

o
Scenes > Faces/ objects

PPA: right above cerebellum, right below
ventricles

Parahippocampal gyrus: below the hippocampus,
left side

Fusiform gyrus: lateral

PPA: Empty room, furnished room, lego room,
fractured room as long as spatial layout intact, houses&landmark, geometry

o
Not furniture

Perhaps PPA computes features that describe *geometry* of scene

o
Nope; real scenes give higher % signal change
than scrambled scenes, rooms, objs

Viewpoint invariance or specificity in PPA? Ask
using fMRI adaptation paradigm

o
Obj change, viewpoint change, place change

o
Identical<obj<<viewpoint change
(VIEWPOINT SENSITIVE)

o
Viewpoint change treated as entirely different
images

Scene processing network

o
Both for landscapes and cityscapes

**Retrosplenial**
Cortex:location task, familiar
scenes; WIDER WORLD

o
**Both**
needed for location ID task, but RSC more preference for it

o
Responds to location ID more than category or
situation ID

o
More active during location and orientation
compared to simple familiarity tasks

o
More active for familiar scenes compared to unfamiliar
scenes

PPA vs RSC

o   PPA doesn’t care as long as it’s
a scene

§  Just processes visual
information of scenes & geometry of space

§  Contextual association, not
scenes per se

o   RSC is more for familiar scenes,
location tasks, and orientation tasks

§  Recruiting memory representation

§  Navigation/orientation

o
RSC damage:

§
Can ID scenes/landmarks

§
CANNOT orient selves in wider world

§
Expansive representations  allow current scene to be placed in larger
spatial framework

o
PPA damage:

§
CANNOT ID scenes/landmarks

§
PPA represents visuospatial structure of
individual scene

Contextual objects

o
Do scene specific areas only care about 3d
layout and location, or do they also care about obj associations and schemas?

o
Contextual objects (e.g. beach chair) activate
scene-specific areas

o
So, PPA is not for scenes specifically…just
things that associate with scenes

o
Some evidence for object schemas in PPA and RSC

o
Areas not just layout; also association

Lateral Occipital Complex

Matches damaged region in agnosia patients

Object **shape**
and luminance, not dependent on motion patterns

SPECIFICALLY for objects, not just textures

Represents ‘perceived’ object shape; bars in
front don’t matter, texture doesn’t matter

**Size**
invariant**: sensitive to semantic changes, but not size changes**

Extrastriate Body Area: mostly left hem

Body parts except faces

Weak response to objs

Intermediate response to facial parts or mammals

**Bodies>other**
objs/shape

Modular vs distributed code for categories? Still ongoing
debate

Different categories show different patterns
across ventral visual cortex; ffa responds to shoesàDistributed coding of objects
throughout entire ventral visual cortex

Evidence for category-selective processing
(modular view): Triple dissociation with TMS of objects, bodies, and facesà supports modular
coding of ventral visual cortex

**^ Evidence for both.**

We don’t know of other localized categories yet.

Maybe organization too fine for fMRI res

Maybe another way to think of obj representation

Evolutionary reason for categorization

Shape selectivity in LOC

New shape on old texture gives almost as big a
spike in LOC as new shape on new texture

Shows that it really only cares about shape