Transcript 1A_Louvain_fMRI_Intr.. - Department of Psychology

Jody Culham
Department of Psychology
University of Western Ontario
http://www.fmri4newbies.com/
Introduction to Functional MRI
Last Update: November 29, 2008
fMRI Course, Louvain, Belgium
MRI vs. fMRI
MRI studies brain anatomy.
Functional MRI (fMRI)
studies brain function.
Brain Imaging: Anatomy
CAT
Photography
PET
MRI
Source: modified from Posner & Raichle, Images of Mind
MRI vs. fMRI
high resolution
(1 mm)
MRI
fMRI
low resolution
(~3 mm but can be better)
one image
…
fMRI
Blood Oxygenation Level Dependent (BOLD) signal
indirect measure of neural activity
 neural activity
many images
(e.g., every 2 sec for 5 mins)
  blood oxygen   fMRI signal
The First “Brain Imaging Experiment”
… and probably the cheapest one too!
Angelo Mosso
Italian physiologist
(1846-1910)
E = mc2
???
“[In Mosso’s experiments] the subject to be observed lay on a delicately balanced table
which could tip downward either at the head or at the foot if the weight of either end were
increased. The moment emotional or intellectual activity began in the subject, down went the
balance at the head-end, in consequence of the redistribution of blood in his system.”
-- William James, Principles of Psychology (1890)
The Rise of fMRI
746 papers (2001)
Number of papers (PubMed)
800
700
600
500
400
300
200
100
0
1990
Slide modified from Mel Goodale
1995
Year of Publication
2000
fMRI Activation
Flickering Checkerboard
OFF (60 s) - ON (60 s) -OFF (60 s) - ON (60 s) - OFF (60 s)
Brain
Activity
Source: Kwong et al., 1992
Time 
PET and fMRI Activation
Source: Posner & Raichle, Images of Mind
fMRI Setup
Category-Specific Visual Areas
objects
faces
Malach, 2002, TICS
•
– place-selective
– places > (objects and faces)
– places > scrambled images
places
•
Lateral Occipital (LO)
– object-selective
– objects > (faces & scenes)
– objects > scrambled images
Parahippocampal Place Area (PPA)
•
Fusiform Face Area (FFA) or pFs
–
–
–
–
face-selective
faces > (objects & scenes)
faces > scrambled images
~ posterior fusiform sulcus (pFs)
A Simple Experiment: LO Localizer
Lateral Occipital Complex
• responds when subject
views objects
Intact
Objects
Blank
Screen
TIME
One volume (12 slices) every 2 seconds for 272
seconds (4 minutes, 32 seconds)
Condition changes every 16 seconds (8 volumes)
Scrambled
Objects
fMRI Experiment Stages: Prep
1) Prepare subject
•
Consent form
•
•
Safety screening
Instructions and practice trials if appropriate
2) Shimming
•
putting body in magnetic field makes it non-uniform
•
adjust 3 orthogonal weak magnets to make magnetic field as homogenous as
possible
3) Sagittals
Perhaps the most frequently misspelled word in fMRI: Should have one g, two t’s
Take images along the midline to use to plan slices
In this example, these are the functional
slices we want: 12 slices x 6 mm
fMRI Experiment Stages: Anatomicals
4) Take anatomical (T1) images
•
high-resolution images (e.g., 0.75 x 0.75 x 3.0 mm)
•
•
3D data: 3 spatial dimensions, sampled at one point in time
64 anatomical slices takes ~4 minutes
64 slices
x 3 mm
Slice Terminology
VOXEL
(Volumetric Pixel)
Slice Thickness
e.g., 6 mm
In-plane resolution
e.g., 192 mm / 64
= 3 mm
3 mm
6 mm
IN-PLANE SLICE
SAGITTAL SLICE
Number of Slices
e.g., 10
Matrix Size
e.g., 64 x 64
Field of View (FOV)
e.g., 19.2 cm
3 mm
fMRI Experiment Stages: Functionals
5) Take functional (T2*) images
•
images are indirectly related to neural activity
•
•
•
•
usually low resolution images (3 x 3 x 6 mm)
all slices at one time = a volume (sometimes also called an image)
sample many volumes (time points) (e.g., 1 volume every 2 seconds for 136
volumes = 272 sec = 4:32)
4D data: 3 spatial, 1 temporal
…
Anatomic Slices Corresponding to
Functional Slices
MR SIGNAL
(ARBITRARY UNITS)
Time Courses
Arbitrary signal varies
from coil to coil, voxel to
voxel, day to day, subject
to subject
MR SIGNAL
(% Change)
TIME
To make the y-axis more
meaningful, we usually
convert the signal into units
of % change:
100*(x - baseline)/baseline
Changes are typically in the
order of 0.5-4 %.
Activation Statistics
Functional images
~2s
ROI Time
Course
fMRI
Signal
(% change)
Time
Condition
Statistical Map
superimposed on
anatomical MRI image
Time
Region of interest (ROI)
~ 5 min
Statistical Maps & Time Courses
Use stat maps to pick regions
Then extract the time course
Stats on Anatomical
2D  3D
Design Jargon: Runs
session: all of the scans collected from one subject in one day
run (or scan): one continuous period of fMRI scanning (~5-7 min)
experiment: a set of conditions you want to compare to each other
condition: one set of stimuli or one task
Note: Terminology can vary from one
fMRI site to another (e.g., some places
use “scan” to refer to what we’ve called a
volume).
2 stimulus conditions
+ 1 baseline condition (fixation)
A session consists of one or more experiments.
Each experiment consists of several (e.g., 1-8) runs
More runs/expt are needed when signal:noise is low or the effect is weak.
Thus each session consists of numerous (e.g., 5-20) runs (e.g., 0.5 – 3
hours)
Design Jargon: Paradigm
paradigm (or protocol): the set of conditions and their order used in a
particular run
epoch: one instance of a
run
condition
first “intact objects” epoch
first “scrambled objects” epoch
second “intact objects” epoch
volume #1
(time = 0)
Time
epoch
8 vol x 2 sec/vol = 16 sec
volume #136
(time = 136 vol x 2 sec/vol = 272 sec = 4:32)
Recipe for MRI
1) Put subject in big magnetic field (leave him there)
2) Transmit radio waves into subject [about 3 ms]
3) Turn off radio wave transmitter
4) Receive radio waves re-transmitted by subject
– Manipulate re-transmission with magnetic fields during this readout
interval [10-100 ms: MRI is not a snapshot]
5) Store measured radio wave data vs. time
– Now go back to 2) to get some more data
6) Process raw data to reconstruct images
7) Allow subject to leave scanner (this is optional)
Source: Robert Cox’s web slides
Necessary Equipment
4T magnet
RF Coil
gradient coil
(inside)
Magnet
Source for Photos: Joe Gati
Gradient Coil
RF Coil
The Big Magnet
Very strong
1 Tesla (T) = 10,000 Gauss
Earth’s magnetic field = 0.5 Gauss
4 Tesla = 4 x 10,000  0.5 = 80,000X Earth’s magnetic field
Continuously on
Main field = B0
Robarts Research Institute 4T
x 80,000 =
Source: www.spacedaily.com
B0
Susceptibility Artifacts
T1-weighted image
T2*-weighted image
sinuses
ear
canals
-T2* artifacts occur near junctions between air and tissue
• sinuses, ear canals
The Benefit of Susceptibility
Susceptibility variations can also be seen around blood vessels
where deoxyhemoglobin affects T2* in nearby tissue
Modified from: Robert Cox’s web slides
Deoxygenated Blood  Signal Loss
Oxygenated blood?
No signal loss…
Deoxygenated blood?
Signal loss!!!
Images from Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imaging
Hemoglobin
Figure Source, Huettel, Song & McCarthy, 2004,
Functional Magnetic Resonance Imaging
BOLD Time Course
Stimulus to BOLD
Source: Arthurs & Boniface, 2002, Trends in Neurosciences
Neural Networks
Post-Synaptic Potentials
•
•
The inputs to a neuron (post-synaptic potentials) increase (excitatory PSPs) or
decrease (inhibitory PSPs) the membrane voltage
If the summed PSPs at the axon hillock push the voltage above the threshold, the
neuron will fire an action potential
Even Simple Circuits Aren’t Simple
gray matter
(dendrites, cell bodies
& synapses)
Lower tier area
(e.g., thalamus)
white matter
(axons)
Will BOLD activation from the blue voxel reflect:
Middle tier area
(e.g., V1, primary
visual cortex)
• output of the black neuron (action potentials)?
• excitatory input (green synapses)?
• inhibitory input (red synapses)?
Higher tier area
(e.g., V2, secondary
visual cortex)
• inputs from the same layer (which constitute ~80% of
synapses)?
• feedforward projections (from lower-tier areas)?
…
• feedback projections (from higher-tier areas)?
BOLD Correlations
Local Field Potentials (LFP)
• reflect post-synaptic potentials
• similar to what EEG (ERPs) and MEG
measure
Multi-Unit Activity (MUA)
• reflects action potentials
• similar to what most electrophysiology
measures
Source: Logothetis et al., 2001, Nature
Logothetis et al. (2001)
• combined BOLD fMRI and
electrophysiological recordings
• found that BOLD activity is more closely
related to LFPs than MUA
Comparing Electrophysiolgy and BOLD
Data Source: Disbrow et al., 2000, PNAS
Figure Source, Huettel, Song & McCarthy, Functional Magnetic Resonance Imaging
fMRI Measures the Population Activity
• population activity depends on
– how active the neurons are
– how many neurons are active
• manipulations that change the activity of many neurons a little have
a show bigger activation differences than manipulations that change
the activation of a few neurons a lot
– attention
•  activity
– learning
Verb generation
Verb generation
after 15 min practice
•  activity
• fMRI may not
match single neuron
physiology results
Ideas from: Scannell & Young, 1999,
Proc Biol Sci
Raichle & Posner, Images of Mind cover image
Vasculature
Source: Menon & Kim, TICS
Macro- vs. micro- vasculature
Macrovasculature:
vessels > 25 m radius
(cortical and pial veins)
 linear and oriented
 cause both magnitude and
phase changes
Microvasculature:
vessels < 25 m radius
(venuoles and capillaries)
 randomly oriented
 cause only magnitude
changes
Capillary beds within the cortex.
Why are vessels a problem?
• large vessels produce BOLD activation further from the true site of activation than
small vessels (especially problematic for high-resolution fMRI)
• large vessels line the sulci and make it hard to tell which bank of a sulcus the
activity arises from
• the % signal change in large vessels can be considerably higher than in small
vessels (e.g., 10% vs. 2%)
• activation in large vessels occurs later than in small ones
• vessel artifacts are worse with gradient echo sequences (compared to asymmetric
spin echo for example) and low field strengths
Source: Ono et al., 1990, Atlas of the Cerebral Sulci
Don’t Trust Sinus Activity
•
You will sometimes see bogus “activity” in the sagittal sinus
More Caveats
• “brain vs. vein” debate
– source of signal affects spatial resolution
• scientists haven’t agreed on a single theory to explain
the relationship between oxygen, glucose metabolism
and blood flow
• no one really understands how neurons trigger increased
blood flow
– neural synchrony may be a factor
The Concise Summary
We sort of understand this
(e.g., psychophysics,
neurophysiology)
We’re *&^%$#@ clueless here!
We sort of understand this
(MR Physics)
Bottom Line
• Despite all the caveats, questions and concerns, BOLD
imaging is well-correlated with results from other
methods
• BOLD imaging can resolve activation at a fairly small
scale (e.g., retinotopic mapping)
• PSPs and action potentials are correlated so either way,
it’s getting at something meaningful
• even if BOLD activation doesn’t correlate completely with
electrophysiology, that doesn’t mean it’s wrong
– may be picking up other processing info (e.g., PSPs, synchrony)