Transcript Document

BOLD fMRI
John VanMeter, Ph.D.
Center for Functional and Molecular Imaging
Georgetown University Medical Center
Outline
• BOLD contrast fMRI conceptually
• Relationship between BOLD contrast
and hemodynamics
• History of BOLD contrast
• Relationship between neuronal glucose
metabolism and blood flow
• Theories and properties of BOLD
contrast mechanisms
Neuronal Activity and Blood Flow
Changes: Initial Hypothesis
• Roy and Sherrington hypothesized that
local neuronal activity is related to
regional changes in both cerebral blood
flow and metabolism (1890).
• “There are, then, two more or less
distinct mechanisms for controlling the
cerebral circulation, viz. - firstly, an
intrinsic one by which the blood supply
of the various parts of the brain can
be varied locally in accordance with
local requirements, and secondly, an
extrinsic, viz. - the vasomotor nervous
system…”
Roy and Sherrington’s
Experiments
“… the increase in the volume of the brain which results
from stimulation of the sensory nerves is mainly if not
entirely due to passive or elastic distension of its
vessels as a result of the blood-pressure in the systemic
arteries.”
History of BOLD fMRI
• Initial discovery of magnetic properties
of blood by Linus Pauling and graduate
student Charles Coryell (1936):
– Magnetic properties of a blood cell
(hemoglobin) depends on whether it has an
oxygen molecule
– With oxygen  zero magnetic moment
– Without oxygen  sizeable magnetic
moment
Initial In Vivo Measurement of
Neuronal Activity
• Initial techniques used PET (positron
emission tomography)
• PET uses injection of a radiotracers
which are variants of physiological
molecules that include a radio isotope
• FDG (2-fluoro-2deoxy-D-glucose) for
glucose metabolism
• H2015 for blood flow
Functional Imaging - PET
• Sokoloff demonstrated that rCBF (blood flow)
increases in visual cortex in proportion to
photic stimulation using PET (1961).
• Demonstrated “coupling” between blood flow
and metabolism (1981).
Relationship Between Glucose
Metabolism and Blood Flow
• Sokoloff (1981) used
autoradiography
• Measured both
glucose metabolism
and blood flow
• 39 brain regions in
rat brain
• Correlation r=0.95
• Slope m=2.6
First MRI-based Measurement of
Neuronal Activity
• Belliveau (1990)
used MRI contrast
agent Gadolinium as
an exogenous tracer
• Gadolinium locally
disrupts MRI signal
• Perfusion weighted
imaging (PWI)
Oxy- vs. DeoxyHemoglobin
• Oxygenated hemoglobin (Hb) is
diamagnetic (zero magnetic moment)
• Deoxygenated hemoglobin (dHb) is
paramagnetic (magnetic moment)
• Magnetic susceptibility of dHb is about
20% greater than Hb
• Magnetic susceptibility affects rate of
dephasing - T2 and T2* contrast!
T1 & T2 Contrast Versus
Oxygenated Hemoglobin
Demonstration of BOLD
Contrast
• Seiji Ogawa (1990) manipulates
oxygen content of air breathed by
rats
• Results in variation of oxygenated
state of blood
• Demonstrates effect on T2*
contrast to make images of blood
vessels
Ogawa’s Images of Blood Vessels
Based on Oxygen Content
Pure oxygen
Normal Air
Magnetic Susceptibility Greater
on T2* than T2 Images
Spin
Echo (T2)
Gradient
Echo (T2*)
Oxygenated
Hemoglobin
Deoxygenated
Hemoglobin
Oxygenation vs Local Field
Changes
Bandettini and Wong. Int. J. Imaging Systems and Technology. 6:133 (1995)
First fMRI BOLD in Human
• Kwong (1992)
demonstrated
first BOLDcontrast fMRI in
human visual
cortex
Blood Flow vs BOLD
Changes
• Kwong also
showed how
changes in BOLD
corresponded to
changes in blood
flow
• Important to
show that BOLD
and blood are
related
Build Up to BOLD Contrast
• Hypothesis of relationship between blood flow and
activity (Roy & Sherrington, 1890)
• Discovery of differential magnetic properties of
oxygenated and deoxygenated hemoglobin (Pauling,
1936)
• Blood flow increases with activity (Sokoloff, 1961)
• Blood flow correlated with glucose metabolism
(Sokoloff, 1981)
• Demonstration of blood flow measured using MRI with
an exogenous tracer (Belliveau, 1990)
• Demonstration of effect of dHb on T2* contrast (Ogawa,
1990) use of blood as an endogenous tracer
• Generation of first BOLD images (Ogawa, 1990)
• First BOLD images in humans (Kwong, 1992)
Basic Model of Relationship Between
BOLD fMRI & Neuronal Activity
WHY DOES
MRI SIGNAL
INCREASE?
Disparity Between Blood Flow &
Oxygen Consumption
• Fox & Raichle conducted PET
experiments to measure glucose
metabolism (CMRglu), blood flow (CBF),
and rate of oxygen metabolism
(CMRO2)
• Measured percent change between
visual stimulation and rest
• Increase in CBF=50%, CMRglu=51%
• But increase in CMRO2 is only 5%!!
• Implies anaerobic metabolism of
glucose
Disparity & MRI Signal
Increase
• Upshot of Fox & Raichle: much more oxygen
(CBF) is supplied than is used (CMRO2)
• While neuronal activity results in more
deoxygenated hemoglobin much more
oxygenated hemoglobin flows in flushing out
deoxygenated hemoglobin
• Result is a decrease in dHB and thus an
increase in MRI signal
• But there’s uncoupling of glucose metabolism
and oxygen metabolism - WHY?
Uncoupling Problematic
• Fox & Raichle data nicely explains why
MRI signal increases with neuronal
activity
• But a new problem is presented:
uncoupling of glucose and oxygen
metabolism
• We expect a 6:1 ratio of oxygen-toglucose (OGI) for aerobic glycolysis but
F&R saw about 1:10
• Implication is anaerobic glycolysis is
used
Theories to Explain Uncoupling
Found by Fox & Raichle
1. Watering the Garden for the Sake
of One Thirsty Flower
2. Astrocyte-Neuron Lactate Shuttle
Model
3. Transit Time and Oxygen
Extraction
Separate Measurement of
Oxy & Deoxy Hemoglobin
• Malonek & Grinvald
used optical imaging
to measure Hb and
dHb separately
during visual
stimulation
 dHb spatially focal
and co-located to
neuronal activity
 Hb more widely
distributed
Implications of Differences in
Concentration of Hb & dHb
• Rapid increase in
dHb implies
oxidative metabolism
initially
• High spatial
correspondence
between initial dHb
increase and
neuronal activity
• Coarse spatial
correspondence and
greater extent of
delivery of Hb
Theories to Explain Uncoupling
Found by Fox & Raichle
1. Watering the Garden for the Sake of
One Thirsty Flower
2. Astrocyte-Neuron Lactate Shuttle
Model
3. Transit Time and Oxygen Extraction
(extended to Balloon Model)
4. Aerobic glycolysis already near max at
rest thus activity requires quick
increase in energy via anaerobic
glycolysis (Prichard, 1991)
Watering the Garden
• According to this model uncoupling
observed by Fox & Raichle does not
imply anaerobic glycolysis
• Instead Malonek & Grinvald’s data
shows huge excess of freshly
oxygenated hemoglobin spread over a
wide area displacing deoxygenated
hemoglobin
• But CMRglu wasn’t measured; still
haven’t explained why Fox & Raichle
gets a 1:10 versus expected 6:1 OGI
Astrocyte-Neuron Lactate
Shuttle Model
• Initially anaerobic glycolysis occurs producing
excess glutamate (consistent with Fox &
Raichle)
• Glutamate taken up by astrocyte to prevent
toxicity and converted to glutamine which
neuron can reuse
• Delicate balance is achieved by astrocyte
through intake of Na+ produced by sodiumpotassium pump of neuron
• Astrocyte uses 2 ATP molecules
• Great because that’s all the ATP available!
• But where’s the ATP for the neuron?
ANLS Model (cont’d)
• Astrocyte dumps resulting lactate, which
diffuses into neuron that turns into pyruvate
and into TCA cycle to give neuron 36 ATP
molecules for neuron’s energy
• Thus, we’re back to aerobic glycolysis, which
requires 6 molecules of oxygen
• Model hypothesizes early anaerobic followed
by aerobic glycolysis
• Support for this comes from Mintun (2002)
who showed uncoupling only occurs with initial
onset of stimulus then coupling is
reestablished with continued stimulation
Astrocyte-Neuron Lactate
Shuttle Model
Transit Time and Oxygen
Extraction
• Disputes that uncoupling implies
anaerobic glycolysis as does
Watering the Garden
• Model is based on limited time for
extraction of oxygen due to
increase in velocity of blood flow
with neuronal activity
Transit Time and Oxygen
Extraction
•
Model proposed by Buxton (1998)
rests on four assumptions:
1. Increased blood flow accomplished by
increase in velocity as opposed pumping
more blood through more capillaries
2. Virtually all oxygen is metabolized
3. But not all of the glucose is metabolized
4. Extraction of oxygen from blood by
neurons is limited and proportional to
transit time
Transit time - how long it takes for blood to
pass through a given area
Transit Time and Oxygen
Extraction
• Wouldn’t limited time for extraction of
oxygen due to increase in velocity of
blood also limit glucose availability?
• Buxton - well actually glucose
availability is even more limited than
oxygen but less than half that is
extracted is actually used…
• Data from Gjedde (2002) supports
glucose part
Balloon Model
• No uncoupling of CBF and CMRO2; difference between CBF
and CMRO2 lowers oxygen extraction fraction (E) [Fick
Principle]
• Initial increase in blood flow increases blood volume
(ballooning of venous capillary to accommodate)
• Predicts an initial dip in BOLD signal
Buxton et al. Neuroimage 2004
Uncoupling Problem
• Debate continues to this day
• Uncoupling problem important to
understanding the fundamental basis of fMRI
signal
• fMRI is an indirect measure of blood flow and
is not directly tied to glucose metabolism or
even oxygen metabolism
• Relationship between mechanisms of
metabolism and blood flow is important to
understanding how closely related BOLD and
blood flow are to neuronal activity
Implications of Theories
for Uncoupling
• “Watering the Garden” model posits
widespread distribution of CBF increase 
poor fMRI spatial resolution
• “Transit Time” model implies excess oxygen
rich blood passing over area of activity getting
into venous system  poor fMRI spatial
resolution
• Both imply a “Draining Vein” problem with dHb
flowing downstream of area of activity
• Frahm (1994) asked “Brain or Vein?”
• Uncoupling issue remains unresolved
Physiological Mechanisms for
Regulation of Blood Flow
• How is blood flow controlled?
• Arterioles well upstream need to respond to
produce local changes in blood flow
• Mechanism for accomplishing this is largely
unknown
• Possible candidates include nitrous oxide
synthesis, potassium accumulation, generation
of lactate, or acetylcholine activity
Initial Dip
• Studies used very
short TR (100ms)
and visual stimulus
for 10s at 4T or
higher
• Menon (1995) found
Initial Dip in fMRI
signal before
expected increase
• There’s also a post
stimulus undershoot
Spatial Extent of Initial Dip
• Voxels with initial dip were more
spatially restricted and localized to gray
matter around calcarine sulcus
Implications of Initial Dip
• Menon suggested dip is directly related to
oxygen extraction and thus more closely
related to neuronal activity
• But dip could also result from temporary
decrease in blood flow or increase in blood
volume
• Initial dip if it occurs is contradictory with
anaerobic glycolysis - Why?
• Balloon model predicts increase in blood
volume and thus consistent with initial dip but
for a different reason than Menon posits
HDR (Hemodynamic Response)
HRF (Hemodynamic Response Function)
• Change in MR signal
related to neuronal
activity (HRF)
• Has multiple components
– Changes delayed by 1-2
sec (lags activity)
– Initial dip (not always
seen)
– Influx of Hb greater than
needed for activity
– 5-6 sec time to peak
– Undershoot follows ~6s
after peak
Typical HDR for Long
Stimulus (Block)
• Peak is sustained with
prolonged stimulation
• Block is also referred to
as an epoch
• Brief stimulus is referred
to as an event
Undershoot
• Arises from rapid
return to baseline
of CBF but
delayed return of
CBV
• Delay in CBV
return to baseline
results in an
accumulation of
dHb
BOLD vs Neuronal Activity
• Logothetis, et al., 2001
recorded LFP, MUA, SUA,
and BOLD simultaneously
• BOLD response best
explained by changes in
LFP
• Suggests BOLD reflects
“incoming input and local
processing rather than
spiking activity”
• ”The BOLD contrast
mechanism directly
directly reflects the neural
responses elicited by a
stimulus.”
Open Questions about
Basis of BOLD fMRI
• Uncoupling problem - Why does it
occur? To what extent?
• Is there an Initial Dip? What causes the
dip? Is it more localized than the
expected signal increase?
• What about “Draining Veins”?
• How does the arterial system upstream
know when and by how much to
increase blood flow?
Factors Affecting BOLD
Signal
• Physiology
– Cerebral blood flow (baseline and change)
– Metabolic oxygen consumption
– Cerebral blood volume
• Equipment
– Static field strength
– Field homogeneity (e.g. shim dependent T2*)
• Pulse sequence
– Gradient vs spin echo
– Echo time, repeat time, flip angle
– Resolution
Physiological Baseline
• Baseline CBF changes (up for hypercapnia, down for
hypocapnia)
• But CBF CMRO2 unchanged (probably)
(Brown et al JCBFM 2003)
• BOLD response  (probably)
Cohen et al JCBFM 2002
Spatial & Temporal
Properties of BOLD
• Spatial resolution - ability to distinguish
unique changes in activity from one location to
the next
• Temporal resolution - ability to distinguish
changes across time
• Linearity vs Nonlinearity - does combined
response to 2 or more events with short ISI
(inter-stimulus interval) lead to sum in BOLD
response?
Problems With Increasing
Spatial Resolution
• Increased spatial resolution results in
smaller voxels
– Fewer protons so less MRI signal
– Less dHb thus more noise in BOLD fMRI
signal
– Degree of activation varies by brain region
with greater activation in sensorimotor
areas and less in frontal and association
cortices
• Smaller voxels ultimately make
detecting changes harder
Spatial vs Temporal
Resolution
• Acquisition time per slice goes up
as voxel size goes down
– Number of phase encode lines
increases thus more time required to
cover k-space
• Decreasing slice thickness will
require increasing number of slices
to maintain same coverage again
increasing acquisition time
Designing an fMRI
Protocol
• Tradeoffs
– Increased spatial resolution requires
• Increased TR (scan time)
• Less coverage (fewer slices)
– Increased temporal resolution requires
• Decreased spatial resolution (larger voxels)
• Less coverage (fewer slices)
• Reducing amount of k-space acquired (less SNR)
– Increased SNR (signal-to-noise ration) requires
• Decreased spatial resolution and/or
• Increased scan time via averaging
(f)MRI Image
Acquisition Constraints
Signal to Noise Ratio
Spatial
Resolution
Temporal
Resolution
Partial Volume Effects
• Any given voxel will be a
mix of tissue types
• Boundaries with sulci will
include CSF
• Both can lead to a
reduction in overall fMRI
BOLD signal
Spatial Correspondence
Theoretical Lower Bound
on Spatial Resolution
• Ultimately determined by the size
of capillaries
– 1mm in length
– ~100 microns between capillaries
– Theoretical lower bound for any
hemodynamic based measurement is
100 microns
Mapping Ocular
Dominance Columns
• Menon, 1997 presented visual
stimulus to alternating eyes
• Expect to see side-by-side
alternating areas of activation in
V1 corresponding to columns first
shown by Hubel & Wiesel
• Acquired at 4T using a single slice
with 547m x 547m resolution
fMRI of Ocular Dominance
Columns
Ocular Dominance
Columns - Take 2
• Cheng, 2001 used 4T with 470m2
resolution, single slice
• Each slice required 32-RF pulses to
get enough SNR (averaging), scan
time for 1 slice was 10s!
• Stimulus was 2min monocular
presentation of light interspersed
with 1min darkness
Replication Within Subject
Ocular Dominance
Columns - Take 3
fMRI Data Processing &
Spatial Resolution
• Typical processing includes
– Motion correction which will reslice
the data (reslicing of data requires
averaging of voxels to reformat data)
– Spatial Normalization (transforming
into atlas space) again reslices data
– Spatial smoothing (blurring)
• Net result is reduction in effective
spatial resolution
Temporal Resolution
• TR in fMRI refers to time needed to collect one
volume of data
• Long TR (>3s) good for detecting differences
in activation but not differences in HRF
(hemodynamic response function)
characteristics
– Where is activity occurring?
• Shorter TR (<2s) gives better estimate of
differences in HRF characteristics
– What are the differences in activity between two
stimuli activating in the same area?
“Jitter”
Interleaved Stimulus Presentation
• Instead of locking
stimulus presentation
to the TR jitter it
• Effectively gives more
data on HRF curve than
locked to the TR
• Thus, effective
temporal resolution is
increased
BOLD as a Psychophysical
Measure
Duration of Cognitive
Processing & BOLD Response
• Psychophysical experiments looking at mental
rotation have shown that the greater the
differences in angle between two figures the
longer the response time
• What happens to BOLD response?
BOLD Response Duration
Increases
Timing Between Brain
Regions
• Move joystick from one
target to another
• Measured reaction time and
difference in onset time of
BOLD response different
brain regions
 V1-SMA differences
suggests decision pathway
 SMA-M1 flatness suggests
simple execution
Latency of BOLD Response
• Examination of the
latency (time to onset) in
voxels with significant
activation
– Blue shortest
– Yellow longest
• Output from V1 (slices a
& c) feeds fusiform gyrus
(slices b & d)
• As hoped response
delayed in fusiform
relative to V1
Linearity of Hemodynamic
Response?
• Linearity would imply
– there is an additive effect of two
stimuli presented close enough in
time
– HRF scales with stimulus intensity
– HRF response to two or more stimuli
equal summation of response to
individual stimuli
• Under what conditions is HRF
linear?
Linearity of HRF Theoretical
• Give two stimuli
close in time
• Is the HRF for the
second equal to
the first?
Nonlinearity Via
Attenuation - Theoretical
• Or is there some
attenuation
(reduction) in the
response to the 2nd
stimulus?
• Refractory effects change in response
to 2nd stimulus based
on presence of first?
Does HRF Scale with
Stimulus Magnitude?
Superposition of HRF ?
Evidence for Linearity
• Boynton, 1996
• Presented
several short
stimuli for
various
durations
• Found response
scaled with
contrast
• Found good
correspondence
between actual
response and
predicted thus
linearity held
Superposition
• Boynton found good correspondence
between predicted and actual measured
response
• However, when 2 or more 3s stimuli
presented - got smaller than predicted
response
• Attributed to adaptation of neurons
leading to reduced activity
• Support for linearity & superposition
when stimuli >3s
Response to Multiple Trials
• Dale & Buckner,
1997
• Three identical
trials presented
• ISI was either 2s
or 5s
• Each trial gives
additive effect
Separation of Response to
Multiple Trials
• Recovered HRF
for 2nd and 3rd
trials quite
closely match
that of the 1st
for 5s ISI
• Again at
shorter ISI’s of
2s results were
reduced
amplitude and
greater latency
• Evidence of
nonlinearity at
short ISI’s
HRF as a Function of
Interstimulus Interval
• Huettel, 2000
used visual
stimuli separated
by a variable
amount of time
• Found reduction
in amplitude of
response and
increase in
latency as ISI
decreased
Linearity of HRF and
Refractory Period
• Linearity seems to hold for
combinations of stimuli with ISI’s 5-6s
or longer
• Much evidence of a refractory period
during which additional presentation of
stimuli produces smaller and delayed
response
• Is this bad? Can we take advantage of
this?
fMRI Adaptation (fMRI-A)
• Grill-Spector & Mallach, 2001
• Presented same face with different sizes,
positions, shading, and angles
• Response in fusiform was reduced during
conditions where size and position was varied
• Signal recovered when shading or angle was
varied!
• Conclusion - fusiform recognizes identity
regardless of size or position but treats
shading and angle changes as ‘different’ face
fMRI Adaptation
• Top graph - release of
response to attributes
other than color thus this
area preferentially
responds to changes in
physical characteristics
• Bottom graph - release
of response only to
vehicle type thus this
area preferentially
responds to complex
object categories
Summary
• fMRI BOLD signal arises from changes in
oxygenated state of blood
• Blood flow is primary means for delivering
oxygen and glucose to neurons for production
of energy
• Aerobic and anaerobic glycolysis implies
different amounts of ATP (energy) production
and oxygen requirements; important for
understanding how well BOLD relates to
neuronal activity
• Definitive linkage of BOLD, blood flow and
neuronal energy metabolism still elusive
• Properties of BOLD signal