cc >> ...Symptoms of autism
and points toward possible, at least diagnostic,
implications. So, Andy, why don't you take it
from here. >> Thank you, Marsha.
It's really a privilege to be here and describe to you some of
our research that we're doing to
people with autism. And try I'm going to give you an in
fairly broad picture and a few
as well as the different types snap shots of both what MRI is
focus specifically on autism. of So just a little bit abouthat
myself. I got my PhD
in 1994. I've been in optical sciences
for about 20 years. And after getting my PhD, I went
to the University of Utah,
there and then joined the sfaculty here at the Universityg
of Wisconsin in 2001. I'm the director of MR Physics
Research at the Waisman Brain Imaging Laboratory here, and
that's really a dream job for me
work with people from all over because I get the opportunity to
projects. My focus campus in a broad range of
neuroimaging with MRI, so we do functional MRI, diffusion tensor
imaging, other methods to try and characterize white matter,
study brain metabolism
But one of my main areas of interest is actually applying
these to autism. So I've
here at the University of Wisconsin as well as the
University of Utah. And I'll present some results
from both of those studies. One of the areas that we've
gotten into recently is to try
networks and brain connectivity, and use MRI to study brain
little bit. So, obviously, and I'll explain that in a
important organ. It's responsible for sensory
integration, thoughts, decision making, really anything that is,
most of our daily functions are caused by the brain.
And we can think of this
tissue, sort of simpllike a computerama.pes of
So the gray matter is like the
and that's basically where, when processing units for the brain,
area of your visual cortex you see a light, you have an
but then we also have what's that's basically being excited,
the connections or the wiring callof our brain computer.at's
And so that's taking the signals
projecting that to other parts from that visual cortex area and
on if the light is picture then ofwe're processing it one way.ng
If it's just a pulse of light,
different way. Most of it might be processed a
using magnetic resonance my studies are done
MRI scanner which looks like a imaging, and that's done in an
a coil of superconducting metal githat essentially induces theof
magnetic field. And the field strength that we
operate at is three Tesla and that's about 10,000 times
stronger than the Earth's magnetic field.
So it's a very strong magnetic field.
To do the superconducting, keep the superconduction going, we
need to keep that magnet cooled with liquid helium and different
than some other imaging technologies, it uses radio
waves instead of x-rays, and so it's a much safer technology
than some of the other imaging
flexibility in terms of the types of images that we can get.
The image on the upper left is a
of an MRI scanner. Around cartothe person's, the blobside
that is their head here, is what's called the RF coil.
And that's what is transmitting these RF radio frequency waves
into the brain. So that excites the protons and
the water molecules in our
becomes reemitted and we detect tissthat also with the coil.tion
And based on the number of these
are basically the density of protons and the water molecules
magnetic tissue environment, we get an image of the brain that
has contrast between
And here's a nice example of the different types of tissue.
with MRI. This is kindwhat's called a coronal get
image. It's basically a cross-section
that goes through the brain like this.
The top of the brain is up here,
the left side of the brain. aThis is the brain stem downnd
here. The black signal in the middle
here are the ventricles. That's where the cerebral spinal
fluid is. We also have
outside of the brain. And then the gray tissue here is
the gray matter. So this is the cortex.
And then we have white matter which is the connections between
the gray matter areas. So you can see how the brain is
essentially integrated. Clinically, how MRI is used is
often, what they're looking for is conspicuous lesions or gross
abnormalities. So here's
of clinical scans in a patient an example of a series
they've done different types of imaging, so T2-weighted imaging,
a FLAIR image here, T1-weighted imaging, and you can see you can
get different types of image
one of the really exciting contrast with MRI, and that's
that you can basically apply things about this technology is
these images to look at didifferent features of theto
tissue. And people
abnormalities, this is what the structural MRI images look like.
On the left we have a T1-weighted image, and then on
the right is a
And you can see the contrast is essentially reversed between the
cerebral spinal fluid, the white
And with this sort of technology, if you compare
people with autism versus people
to look very similar. So without autism, the images tend
signature of autism if you look at structural images that'sk
obvious. There are
have been made. Early in some observations that
an overgrowth of the brain life there tends to be
that's fairly common. Also called macroencephaly, and
appears to be that the corpus callosum appears to be slightly
smaller in people with autism.
There are a lot of people with This is an over generalization.
these features. But autthere are no consistentate
macroscopic abnormalities in people with autism.
One of the more exciting
developed for MRI is called functional magnetic resonance
imaging, or fMRI. And the way that this works is
we essentially apply some sort
showing pictures to the individual, it could be pressing
buttons, playing a game.
in terms of what kind Realof task you could do.dless
But what that does is in the
involved with that task, we get neuronal activation which leads
to increased blood flow to those brain areas.
And one of the important parts
get through the hemoglobin of this blood flow is that we
cells, basically they bring oxygen to the parts of the brain
that are being activated, we get
oxyhemoglobin. And an increase in what's called
oxyhemoglobin has a more similar that's important because
surrounding tissue than deoxyhemoglobin which doesn't
have the oxygen. And that induces a signal change
in that brain area. And so, let's see, so here.
This is an axial slice
This is for a task, and the areas that are colored are the
areas that are activated
The signal in the area where we have activation is increasing
during the task period and then decreasing during what we call
the baseline period, and then areas where there aren't
involved with a specific task,
activation. So this is don't show that same level of
how the fMRI experiments work. a schematic showing
call our paradigm which is a Basically, we do our what we
is alternating, and during that ttime we get a series of MRIat
images, and from these MRI
activation, we see the signal increase, and then areas where
we don't have any activation, it doesn't increase.
And then by modeling the signal,
activated. One of the we caprimary hypothesess are
about the brain and autism right
connectivity. So in now people without autism,mal
it's believed that the
sort of short range local conconnections in the brain of
combined with long range
distant brain areas. This conis an oversimplification,rate
of course, but in autism it's believed that these long range
connections are diminished and
the short range connections. there's an over-connectivity of
diagram is that there still are long range connections in people
with autism, so it's a little bit of an oversimplification.
So, for example, this is the
brain connectivity mapping what we're interested in is how is
this yellow region connected to this red region, for instance,
or maybe this purple region connected to this green region.
And so that's what we're
So just going back to this trying to assess with MRI.
The gray matter is the area of slide I showed earlier.
the cortex, and then the white the processing, so that includes
between the brain areas. So the imaging tools to study
brain connectivity include
at the similarities of the functional MRI, and we can look
regions, diffusion tensor imaging which is a technology we
can use to assess what's called microstructure of the white
matter, and that's important
conducting the signals between because white matter is what's
matter tractography where we different areas, and then white
specific connection cpatterns within the brain.p
So what is functional connectivity.
Like the experiment where I showed before where you have a
specific task, here the task
signal responses are in two different portions of the brain.
And you could do that either
task, like looking at pictures while someone's doing an active
could be just during a resting or listening to sounds, or it
temporal signal correlations period and looking at the
doing anything in the scanner. while someone's supposedly not
active, and so this idea that Ofthere's a true state of rests
isn't true. So the
and the area on the left have very similar signal patterns
here, and so there's a
connectivity. So one high level of functional
the University of Utah has been starting to apply this to people
with autism as well as people without autism to study how
functional connectivity is affected.
And one of the first things that he looked at was how the
interhemispheric connectivity,
studies and I'll come to them in and we've shown also in other
callosum, which is one of the main structures that connects
the two hemispheres,
So that might imply impairments in the interhemispheric
connectivity. And so the
posterior part of the brain in basically what we call
homologous areas of the brain showing very similar signal
patterns, as a function of time now, have a very high degree of
correlation. So those areas are functionally
connected. And so then what he did was
taking the homologous areas on
comparing them with each other, eache compared the functionalen
connectivity in people with autism versus people without
autism and found that there were certain parts of this
interhemispheric connectivity that were stronger in the people
without autism. And these tend to be in areas of
insula and also superior
important, as we'll pariecome to in a minute.hat's
So there does seem to be
interhemispheric connectivity. a slight impairment in
Jeff Anderson at Utah also has So taking this one step further,
use this to classify been looking at whether you can
So is there potentially an individuals with autism.
figure out which brain has image-based measure that could
another. So here is more the results of this than
classifier where basically
a higher classification score, individuals without autism have
lower classification score, and he was able to achieve almost an
80% accuracy rate which is
imaging measures. However, pretty good based on brain
20 years old, the classification for individuals under
So this might imply that there actually goes up almost to 90%.
changes that are going on isthat are unique to autism.l
Where the most important areas
classifier include regions of superior parietal lobe as well
as insula which are areas we
connectivity, and then also sareas of what we call thec
default mode network which
self-reflection and is ithat sort of thing. like
So this is starting to give us
more implicated in a map of areas that seem to be
Another important attribute is the autistic brain.
that long range connections tappeared to be decreased andd
then there was increased
connections. So that was connectivity of short range
hypothesis of abnormal consistent with the
Another technique that my lab has been very active in
developing is called diffusion
noninvasive method for assessing tensor imaging, and it's a
of the tissue, especially white tmatter, and what's importants
about this and how it relates to brain connectivity is that
attributes like myelin and the
basically white matter consists of myelinated axons, changes or
alterations in that also
properties. But with influence the diffusion
imaging, we can try and characterize these
microstructure through a variety
So here we have the main of different types of images.
in areas of cerebral spinal difluid, the direction of theht
white matter using this orientation map, the anisotropy
which is high in areas of white matter and is very sensitive to
microstructural changes, a map
density diffusion, and then a map of the myelin diffusion.
So what we're looking at with diffusion MRI is the diffusion
of water molecules and how they interact with the cellular
membranes of the tissue.
tissue here, the water molecules And so in a tightly packed
bumper car course, they're going are, it's essentially like a
these cells very frequently. to bump into the surface of
the water can go much further Wdistances without running into,
these membranes. And so the diffusion coefficient
for this case is much higher
Another important attribute here than it is for this case.
dependence, so if we think of iwhite matter tracts as being
like parallel fibers, the diffusion in that case is going
to have, it's going to run into less stuff when it's going
parallel to these tracks, the diffusion distribution is going
to be longer in this case, and
it's going to run into these when it's moving perpendicular,
The distribution rotates with the fiber structures as well.
And so we can actually map out
with this technology. So the orientation of these fibers
diffusion tensor, we can using what's called the
properties using a matrix. This is just to illustrate that
both the, essentially the complexity of this sort of
measurement both gives us an
characterize the diffusion but opportunity to more fully
analysis. But with this also prsort of framework,for the
we can characterize the diffusion as being more
isotropic, which means that the diffusion is the same in all
directions, or more anisotropic,
directional dependence, and we which means it has a more
of this anisotropy. So what can do we measure with this?tion
So this sort of ellipsoidal picture here in the shortest
dimension and also in the medium
the plane here, those measures direction which is in and out of
of the tissue or the seem to be related to the myelin
In the direction parallel, it's more sensitive to the axons.
If we take the average of all these, it's related to the
tissue density, and then if we
respect to the three directions lohere, it's a measure of theith
diffusion anisotropy. So
images here, we have our going back to the example
diffusion map, the anisotropy map, our total
Red is indicating fibers are orientation here.
front to back, and then blue is from the bottom to the top of
the brain. Our axonal density diffusion and
our myelin diffusion. So
Lainhart at the University of Utah approached me and said I'd
like to really apply diffusion
autism, can you help me? And tensor imaging in people with
fabulous. So we've I said, wow, that would be
for about 10 years, and we have a longitudinal imaging study.
And I'm just going to present some of the results from that
study. Essentially, most of this comes
from a small study of 43
34 controls that are matched for individuals with autism and then
as head circumference. One age, IQ and handedness as well
we studied was the of the first structures that
So this interhemispheric corpus callosum.
white matter structure that connconnects the two brainmain
hemispheres, and that's shown here in these colored areas.
The different colors are
the corpus callosum reprthat we also looked at.s of
Essentially, this is the results
And what we found is that there was a group of individuals with.
autism that appear to have
decreased anisotropy, and that increased total diffusion and
impaired connectivity through wouthis white matter tract.th
But there is also a lot of
have a high degree of overlap. individuals with autism that
heterogeneity of the disorder. And this fits in with the
reasons why certain people have more autistic features is that
their white matter is abnormal, but in other individuals, maybe
there's another biological mechanism.
We've also applied this diffusion tensor imaging to see
how well we can discriminate the
So here we have a study of 30 individuals with autism and 30
controls using measures of
properties, and with these temporal lobe diffusion tensor
were able to achieve a 92% measurements in this sample, we
is very high. And accuracthen in the smallon which
replication sample, we get
We're in the process of trying similar levels of accuracy.
larger population. The to replicate this across a
going to be about what's called diffusion tensor white matter
tractography where we take the
try to estimate the connection diffusion tensor information and
My lab's been doing this for patterns in the brain.
about 10 years. So from abothe diffusion tensor, weme,
have this orientational information.
So here this anisotropy tensor
Here it's pointing in some other is pointing in the Z direction.
maybe a combination of arbitrary oblique direction,
And that's what's causing the differences in the color map
here. So the red, again in the corpus
callosum appears red. The tracts that go front to back
are green, and then tracts like these cortical spinal tract that
connect the brain stem to the cortex appear blue.
And there's different representations for how we can
map this direction. We can
themselves. We can look at the tensor glyphs
representation of these directions.
But using the vector
and reconstruct the pathways representation we can then try
technology. And we through the brain using this
tractography. And so call this white matter
white matter tract here is an example of
So for instance, here is the reconstructions that we can get.
fronto occipital fasciculus, corpus callosum, the inferior
connects the prefrontal cortex the uncinate fasciculus that
which is part of the limbic tsystem, and also the cingulumix
bundles which are also
And these are just a few of the major white matter fiber tracts
that we see in the human brain. Another application of this that
we have developed is to apply it
undergo brain surgery so we can see, for instance, where are the
white matter tracts of the
to a large brain tumor. coAnd so this is before theive
surgery and then after the
this is that we show the tracts are, indeed, preserved, and this
patient had preserved motor function after the resection of
this brain tumor. So how
brain connectivity? Well, first thing we do is we
basically try and reconstruct all the fibers within the brain,
and then we take the regions of gray matter, so basically the
processing nodes of our brain network, and then define which
tracts are connecting, say, this
back here and then map that into red region with this blue region
this. You can a giabinarize it and then like
basically map where these connections are within the brain
as a network. Moo Chung, one of my
collaborators here in the biostatistics department has
essentially taken this
and developed a technique twhere, at different scales ofr
connectivity, he can define how these tracts are connected
within different brain areas. And applying this technology,
he's looked at comparing people with autism versus people
without autism, and so here is
nodes, so basically the gray a map of the brain connection
to other nodes. And there matteare certain areas, andected
this is an area of what's called
the most highly connected brain areas in the brain, showing very
high connectivity with other
autism. And then in brain the autism group,ithout
the distribution of these nodes is much more distributed.
There is a precuneus cluster
the left side it's not quite as hstrong and there seems to ben
another node structure
So the patterns of these that's more anterior.
different. So, in summary, connections appear to be
study the properties with MRI we can
We found that the functional of brain connections.
autism. So we have connectivity is affected in
connections and slightly decreased long range
connections. We also increased short range
matter microstructure his affected in autism.e
And what seems to be mostly affected are the diffusion
anisotropy and the myelin diffusion measures.
What we don't know yet is what
are there less dense axons this is indicating biologically,
And then also we find that the or is it less myelin.
appear to be more tracvariable and affected.maps
So where do we go from here?
understand how these Well, I think we need to try and
the behavioral connectivity measures relate to
We're currently collecting attributes of autism.
We're in the process of lonanalyzing that data.ta.
We have, now, imaging data that spans over eight years, and so
it should be really exciting to try and understand how these
connectivity measures are modulated as a function of age
in people with autism. And
integrate these different thmodalities together.e
We have functional MRI, diffusion tensor imaging and
tractography. Are these measures
complementary, do they tell us
just relaying the somethisame information.re they
And I couldn't have done this without a really great team of
collaborators. Here's my lab here in front of
the new MRI scanner that
In particular, -- Lee did a lot of the autism DTI work.
Nagesh Adluru worked with Moo Chung on a lot of the
tractography work. Brittany Travers and Chad --
have done a lot of the more recent DTI analyses in the lab.
And then Richie Davidson and Kim
their work today but they've Dalton, I didn't show any of
with functional MRI to also done some very nice work
And then also my collaborators study the brain in autism.
Lainhart who introduced me to research of the brain in people
with autism. Erin Bigler
Young University and is a psychologist and neuroanatomist
and really just a great mentor in terms of helping me
understand what behavioral
Lang who is a biostatistician at measures mean, and then Nick
lot of the Harvard who's been working on a
And I'd like to really thank the classification analyses.
Obviously, we can't partido it without them.udies.
And hopefully this work will
long-term. And also the heNational Institutesthe
of Health for funding. Thank you.
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