This is the reading for my Cognitive Science class. I’m going to post my notes
here and print them in the morning.

S. Smith, Kanwisher, Uttal

1. What does the acronym fMRI refer to?

Functional Magnetic Resonance Imaging

2. What does fMRI measure?

Increased blood flow to activated areas of the brain. Holy Shit, it’s cooler
than I thought. I just read this other article from Oxford.

Magnetic resonance
imaging: seeing brain structure

What connection could an ancient Greek shepherd have with modern brain science?
The answer is magnetism. Two thousand years ago a shepherd
named Magnes came across a rock with very peculiar qualities. It attracted bits
of iron and seemed to orient itself as if magically when held from a string.
The rock was magnetite and the observations were the first in a long history
of physical studies of magnetism that extend to this day.

The connection with brain science comes because magnetism allows us to see
the living brain. You may not realise this, but your brain is composed of billions
upon billions of tiny magnets. Each of the hydrogen atoms in each of the molecules
of water in your brain is a tiny magnetic dipole. There are over 100,000,000,000,000,000,000,000
in even a teaspoon-size scoop of your brain! When these tiny magnets in the
brain tissue are placed inside of a very strong magnetic field, they align with
the field just as a compass aligns with the earth’s magnetic field. Of
course, a very strong magnetic field is needed to make this happen. Typically,
a supercooled (to a temperature of about 270o below zero) magnet over 50,000
times more powerful than of the earth’s magnetic field is used.

howstuffworks.com says:

Because
of the power of these magnets, the MRI suite can be a very dangerous place if
strict precautions are not observed. Metal objects can become dangerous projectiles
if they are taken into the scan room. For example, paperclips, pens, keys, scissors,
hemostats, stethoscopes and any other small objects can be pulled out of pockets
and off the body without warning, at which point they fly toward the opening
of the magnet (where the patient is placed) at very high speeds, posing a threat
to everyone in the room. Credit
cards, bank cards and anything else with magnetic encoding will be erased
by most MRI systems.

that’s pretty bad-ass. and ‘There are no known biological hazards to humans
from being exposed to magnetic fields of the strength used in medical imaging
today.’ I think it’s like Infrared Light, it’s a spectrum of Physics that we
don’t really inhabit. Metal is Artificial and it does inhabit the Magnetic spectrum.

I think Magnetic are cool cause they’re invisible and they pick up stuff. The
Magnetosphere
of Space is fucking fascinating. Plus if you were able to control magnetism
like Magneto (CV),
that would be awesome.

so, the magnet magnetizes the H20 in your brain.

H
= hydrogen. ‘Hydrogen is an ideal atom for MRI because its nucleus has a single
proton and a large magnetic moment. The large magnetic moment means that, when
placed in a magnetic field, the hydrogen atom has a strong tendency to line
up with the direction of the magnetic field. (Gould)

… A short pulse of radiofrequency energy perturbs these tiny magnets from
their preferred alignment. As they subsequently return to their original position
they give off small amounts of energy that can be detected and amplified with
an antenna or “receiver coil” placed directly around the head. The
detected signal allows us to distinguish water molecules and to distinguish
the relative amounts in each part of the head.’ (Understanding
the Technology: Atoms)

3. What are the main steps in obtaining fMRI data?

1.
Stick human in MRI tube

2. Turn on Radio Frequency Pulse:

The MRI machine applies an RF (radio frequency) pulse that is
specific only to hydrogen. The system directs the pulse toward the area of
the body we want to examine. The pulse causes the protons in that area to
absorb the energy required to make them spin, or precess, in a different direction.
This is the "resonance" part of MRI. The RF pulse forces them (only
the one or two extra unmatched protons per million) to spin at a particular
frequency, in a particular direction. The specific frequency of resonance
is called the Larmour frequency and is calculated based on the particular
tissue being imaged and the strength of the main magnetic field.

3. Turn off RF Pulse:

When the RF pulse is turned off, the hydrogen protons begin
to slowly (relatively speaking) return to their natural alignment within the
magnetic field and release their excess stored energy. When they do this,
they give off a signal that the coil now picks up and sends to the computer
system. What the system receives is mathematical data that is converted, through
the use of a Fourier transform, into a picture that we can put on film. That
is the "imaging" part of MRI.

4. Computer converts mathematical differences to visual
gradients (grayscale):

MRI contrast works by altering the local magnetic field in the
tissue being examined. Normal and abnormal tissue will respond differently
to this slight alteration, giving us differing signals. These varied signals
are transferred to the images, allowing us to visualize many different types
of tissue abnormalities and disease processes better than we could without
the contrast.

4. How are fMRI data analyzed?

The rest of the analysis is done using a series of tools which correct for
distortions in the images, remove the effect of the subject moving their head
during the experiment, and compare the low resolution images taken when the
stimulus was off with those taken when it was on. The final statistical image
shows up bright in those parts of the brain which were activated by this experiment.
These activated areas are then shown as coloured blobs on top of the original
high resolution
scan, for interpretation of the experiment. This combined activation image can
be rendered in 3D, and the rendering can be calculated from any angle. (S. Smith,
class reading).

Kanwisher: "faces, places, and bodies may be unusual in
the way they are
processed and represented in the cortex."

1. What are the suspected category-specific region of the ventral visual
pathway and what perceptual categories are they specific to?

‘the
ventral visual pathway extends from the occipital lobe into inferior and lateral
regions of the temporal lobe… This review will focus on the
segment of the human ventral visual pathway that lies anterior to retinotopic
cortex. I will argue that this pathway contains a small number of category-specific
regions, each primarily involved in processing a specific stimulus class, in
addition to a more generalpurpose region that responds to any kind of visually-presented
object…

Kanwisher et al. (1997) scanned subjects with fMRI while they viewed rapid
sequences of faces versus sequences of familiar inanimate objects. We found
a region in the fusiform gyrus in most subjects, and a second
region in the superior temporal sulcus in about half of subjects, that produced
a stronger MR response during face viewing than object viewing (see also McCarthy
et al., 1997).’

2. If you find more activity in a region to faces than to other objects,
does that mean the region is involved in face perception per se?

A greater response to faces than objects could be produced by processes that
have nothing to do with face perception per se, including attentional engagement,
which may be greater for faces than nonfaces, a general response to anything
animate or anything human, or a response to the low-level visual features present
in face stimuli.

// you can measure activation during these processes and see if it accounts
for the activation in the Fucking Fusiform Area (FFA).

3. What are the appropriate control stimuli for demonstrating that
a region is involved in face perception per se?

Measure contrasting conditions…

‘we first identified the candidate face-selective fusiform region individually
in each subject with the comparison of faces to objects, and then measured the
response in this region of interest (ROI) to a number of subsequent contrasting
conditions. After demonstrating that the same region responded at least twice
as strongly to faces as to any of the other control stimuli, we concluded that
this region is indeed selectively involved in face processing, and named it
the fusiform face area, or FFA’

4. Does the FFA respond exclusively to faces?

‘The claim that the FFA responds "selectively" or "specifically"
to faces does not mean that it responds exclusively to faces. Although the FFA
responds much more to faces than to objects, it responds more to objects than
to a baseline condition like a fixation point. The standard criterion for neural
selectivity (Tovee et al. 1993), adopted here, is that the response must be
at least twice as great for the preferred stimulus category as for any other
stimulus category.’

5. Might selective FFA activity to faces result from deeper processing
of faces than other stimuli?

Yes, tho it needs to be tested more. It certainly lights up when we see faces
(and does not light up for other stimuli).

6.
Might selective FFA activity to faces result from low-level feature processing?

No.

These effects are similar when the subject is merely passively viewing the
stimuli, or carrying out a demanding discrimination task on them (Kanwisher
et al.1997), suggesting that the response does not arise from a greater attentional
engagement by faces than other stimuli. Neither can the FFA response to faces
be accounted for in terms of a low-level feature confound, as the response is
higher when a face is perceived versus not perceived even when the stimulus
is unchanged, as in binocular rivalry (Tong et al.1998) and face-vase
reversals (Hasson et al. 2001)

7. Could selective FFA activity be due to domain-general holistic processing?

The most basic question is whether the function of the FFA is truly specific
to faces, or whether it involves a domain-general operation that could in principle
be applied to other stimuli (despite being more commonly carried out on faces).
For example, in our original paper on the FFA, we suggested testing whether
it could be activated by inducing holistic encoding on nonface stimuli . Rossion
et al.(2000) found that although attending to whole faces, rather than
parts of faces, enhanced the right (but not left) FFA response, attending to
whole houses, rather than parts of houses, did not. These data argue
against the domain-general holistic encoding hypothesis, instead implicating
the right FFA in processing holistic/configural aspects of faces.

8. Could selective FFA activity be due to expertise?

No.

Gauthier and her colleagues have argued for a somewhat different domain-general
hypothesis, according to which the right FFA is specialized for discriminating
between any structurally similar exemplars of a given category for which
the subject is expert (Tarr and Gauthier 2000). However, most of her evidence
is based on studies using novel stimuli called "Greebles", a suboptimal
choice for testing this hypothesis because they have the same basic configuration
as a face (i.e., a symmetrical configuration in which two horizontally arranged
parts are above two vertically aligned central parts, as in the configuration
of eyes, nose, and mouth). Nonetheless, in one study, Gauthier et al.(1999)
found that the FFA was activated by cars in car fanatics and birds in bird experts;
this result was replicated by Xu et al.(Xu and Kanwisher 2001 SFN).
However in both studies the effect sizes are small, and the response to faces
remains about twice as high as the response to cars in car experts, a result
that is consistent with both the face-specificity hypothesis and with the subordinate
level categorization of structurally identical exemplars – for-which-the-subject-is-expert
hypothesis. Stronger evidence on this debate comes from a double dissociation
in neurological patients: face recognition impairments can be found in the
absence of impairments in the expert discrimination of category exemplars
(Henke et al., 1998) and vice versa (Moscovitch et al. 1997). These findings
argue that different cortical mechanisms are involved in face perception
and in the expert visual discrimination of structurally similar category exemplars
(Kanwisher, 2000).

9. What does the FFA do with faces?

[The FFA] simply detects the presence of a face. This comes from the findings
that activity in the FFA is strong even for inverted faces (Kanwisher et al.
1998; Aguirre et al. 1999; Haxby et al. 1999) and for line drawings of faces
(Harris and Kanwisher, unpublished; see also Halgren et al. 1999 and Ishai et
al.
1999), both of which support easy face detection but not face recognition. However,
another study (Grill-Spector and Kanwisher, unpublished data) found that activity
in the right FFA is correlated with both successful detection and successful
categorization of faces (versus nonfaces), and in successful discrimination
between individual faces, suggesting that it is involved in both of these abilities.

10. From fMRI evidence, what stimulus information is the parahippocampal
place area (PPA) sensitive to?

determining our location in the environment. A region of cortex called the
parahippocampal place area (or PPA) appears to play an important role in this
ability (Epstein and Kanwisher, 1998). The PPA responds strongly whenever subjects
view images of places, including indoor and outdoor scenes, as well as more
abstract spatial environments such as urban "scenes" made out of Legos,
virtual spaces depicted in video games (Aguirre et al. 1996, Maguire et al.
1998), or close-up photographs of desktop scenes (P. Downing, R. Epstein, &
N. Kanwisher, unpublished data). Remarkably, the visual complexity and number
of objects in the scenes is unimportant; the response is just as high to bare
empty rooms (two walls, a floor, and sometimes a door or window) as it is to
complex photos of the same rooms completely furnished. The PPA also responds
fairly strongly to images of houses cut out from their background (though less
than to full scenes), presumably because spatial surroundings are implicit in
a depiction of a house. Thus it is information about the spatial layout
of the scene that is apparently critical to the PPA response (see Figure
1, middle).

// this is very general spatial info. Doesn’t matter if the input is familiar
or unfamiliar.

11. What are the symptoms of damage to the PPA?

Patients with damage to parahippocampal cortex often suffer from "topographical
disorientation", an impairment in wayfinding (Habib and Sirigu, 1987; Aguirre
et al. 1999a; Epstein et al. 2001). The core deficit in these patients is an
inability to use the appearance of places and buildings for purposes of orientation,
perhaps implicating the PPA in place recognition. However, we tested a neurological
patient with no PPA and largely preserved place perception, but an apparent
deficit in learning new place information, suggesting that the PPA may
be more critical for encoding scenes into memory than for perceiving
them in the first place (Epstein et al. 2001). This possibility is consistent
with evidence from other laboratories suggesting that parahippocampal cortex
is involved in memory encoding of words (Wagner et al., 1998) and scenes (Brewer
et al., 1998).

12. Does the PPA use egocentric or allocentric representations of space?

A recent study found that fMRI adaptation to repeated stimuli in the PPA occurs
only when the same view of a scene is repeated, implicating the PPA in egocentric
rather than allocentric representations of space (Epstein et al. in preparation)…

… physiological recordings in animals indicate that the hippocampus contains
allocentric, or world-centered representations of place, whereas the parietal
lobes contain egocentric (body-centered) representations of spatial locations
(Burgess et al. (1999).

13. What is the extrastriate body area (EBA) region sensitive to?

This region responds about twice as strongly when subjects view images depicting
human bodies or body parts (nothing too interesting!) as when
they view objects or object parts (see Figure 1, bottom).

14. What might be the function of the EBA region?

At present, the function of the EBA is unknown. It may be involved in recognizing
individuals (when their face is hidden or far away), or in perceiving the body
configuration of other people, or even in perceiving the location of one’s own
body parts… the EBA may be part of a broader network of nearby areas involved
in social perception and social cognition.

15. What is the extrastriate body area (EBA) region close to?

The EBA is suggestively close to area MT, perhaps implicating it in integrating
information about body shape and motion, (Grossman et al. 2000). The EBA is
also close to other regions that have been shown to be activated during social
perception, from discriminating the direction of eye gaze, to perceiving or
inferring intentions, to perceiving human voices. Thus the EBA may be part of
a broader network of nearby areas involved in social perception and social cognition.

16. What is the LOC region sensitive to?

human visual cortex contains a region more generally involved in perceiving
the shape of any kind of object. A large region of lateral
and inferior occipital cortex just anterior to retinotopic cortex ("LOC"
for lateral occipital complex) responds more strongly to stimuli
depicting shapes than stimuli with similar low-level features that do not depict
shapes (Malach et al. 1995; Kanwisher et al. 1996; see Grill-Spector et al.
2001 for a review).

17. What might be the function of the LOC region?

Several studies have implicated the LOC in visual object recognition by showing
that activity in this region is correlated with success on a variety of object
recognition tasks (Grill-Spector et al. 2000 ; Bar et al. 2001; James et al.
2000; Lerner et al. 2002). Given the correlation of the MR signal in this region
with successful recognition, representations with these properties are likely
to play an important role in human object recognition.

18. What shape information is the LOC response invariant to? Not invariant
to?

findings suggest that neural populations in the LOC represent the perceived
shape of an object in a fashion invariant to changes in position and size, but
not viewpoint (at least in the right hemisphere).

19. Is there a region sensitive to shape that is viewpoint invariant?

//left hemisphere fusiform gyrus…

another recent study by Vuilleumier et al.(in press) found that the left fusiform
gyrus (but not the right) exhibited invariance to viewpoint.

20. What might apparent partial overlap in the FFA, EBA, and LOC regions
mean?

One account of this situation is that the FFA, EBA, and the LOC are in fact
part of the same functional region, which is composed of a set of category-selective
and/or feature-selective columns (Fujita et al. 1992) at such a fine scale that
they cannot be resolved with fMRI, except for a few very large such regions
such as the FFA. Another possibility is that the FFA and the LOC (and EBA and
LOC) do not in fact overlap anatomically, with the apparent overlap due to limitations
in the spatial resolution of fMRI.

21. How many neurons does a voxel contain? Volumetric pixel. What is the implication
of that for interpreting fMRI data?

each voxel in the fMRI data contains hundreds of thousands of neurons, so it
is possible that discriminative information for nonpreferred categories might
exist in these regions at a finer spatial scale.

22. Might a category-specific region such as FFA also play a role in
perception of nonpreferred stimuli?

it is possible that discriminative information for nonpreferred categories
might exist in these regions at a finer spatial scale.

Many of the studies described in previous sections follow a common strategy
in visual neuroscience, of inferring the function of a cortical area, voxel,
or neuron from the stimulus that drives it most strongly. However, this strategy
is viable only to the extent that maximal responses carry most of the information
in a neural representation.

23. Do category-specific regions imply distinct computational mechanisms?

One might argue that special-purpose mechanisms for processing a particular
stimulus class would be expected only if the recognition of stimuli from that
class poses new computational problems that could not be handled by existing
general-purpose mechanisms. Connectionist researchers have noted the computational
efficiency gained by the decomposition of a complex function into natural parts
(Jacobs, 1997), and cortical specializations for components of visual recognition
are plausible candidates for such task decomposition. If visual cortex is organized
in such a computationally principled fashion then each of the modular components
of the system we discover with functional imaging could be expected to instantiate
a distinct set of computations.

However, an alternative hypothesis is that visual cortex contains a large number
of stimulus-selective regions (like the feature columns in inferotemporal cortex
reported by Tanaka, 1997), but the computations that go on in each of these
regions is very similar. On this view cortical specialization might be found
for virtually any stimulus class, yet these specializations might not imply
qualitative differences in the processing of these stimulus classes. A critical
goal for future research is to determine whether the functional organization
of visual recognition is better characterized by this kind of "shallow
specialization", or whether it reflects a deeper form of functional decomposition
in which each of a small number of functionally specific regions carries out
a qualitatively distinct computation in the service of an evolutionarily or
experientially fundamental visual process.

24. Do category-specific brain regions imply innate modules?

Too soon to tell.

A critical goal for future research is to determine whether the functional
organization of visual recognition is better characterized by this kind of "shallow
specialization", or whether it reflects a deeper form of functional decomposition
in which each of a small number of functionally specific regions carries out
a
qualitatively distinct computation in the service of an evolutionarily or experientially
fundamental visual process.

Notes

pattern vision in the first few months of life is necessary for the development
of normal face processing as an adult; years of subsequent visual experience
with faces is not sufficient.

Evidence that very early experience is also crucial in the development of normal
adult face recognition comes from a remarkable recent study by LeGrand et al.
(2001), who tested people born with dense bilateral cataracts. These people
had no pattern vision until their cataracts were surgically corrected between
2 and 6 months of age. After surgery, pattern vision was excellent, if not quite
normal. Surprisingly, these individuals never developed normal configural processing
of faces. As adults, they are impaired at discriminating between faces that
differ in the relative positions of facial features, despite being unimpaired
at discriminating faces on the basis of individual face parts. (They are also
unimpaired or on either task relative to normal controls when the face stimuli
are presented upside-down.)

… cortical regions that respond to visually-presented words do not show the
kind of selectivity seen in the FFA, PPA, and EBA (Jovicich & Kanwisher,
unpublished data). Thus, for the case of visual recognition in humans, it is
not yet clear whether it is the experience of the individual, or the experience
of the species (or both) that is critical for the construction of functionally
distinct regions in the ventral visual pathway.

Uttal

There is little question that some processes and activities are more or less
localized in the brain. The location of sensory and motor and some emotional
and
appetitive regions have been known for years and newer imaging studies has repeatedly
confirmed the basic facts of this aspect of brain organization. On the other
hand, the idea that high-level cognitive processes such as decisionmaking
or problem solving are uniquely encoded in localized regions of the brain is,
some of us suggest, suspect.

1. What are the difficulties Uttal sees with fMRIs of cognitive functions?

2. Can Uttal and Kanwisher be reconciled?

Posted on Tuesday, November 18th, 2003 in Brain, Cognitive Science, Science.