what neuroscientists can and cannot learn from fmri last update: january 18, 2012 last course:...
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What Neuroscientists Can and Cannot Learn from fMRI
http://www.fmri4newbies.com/
Last Update: January 18, 2012Last Course: Psychology 9223, W2010, University of Western Ontario
Jody CulhamBrain and Mind Institute
Department of PsychologyUniversity of Western Ontario
Section 1The BOLD Signal
Deoxygenated Blood Signal Loss
Oxygenated blood?• Diamagnetic• Doesn’t distort surrounding
magnetic field• No signal loss…
Deoxygenated blood?
• Paramagnetic
• Distorts surrounding magnetic field
• Signal loss !!!
Images from Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imagingbased on two papers from Ogawa et al., 1990, both in Magnetic Resonance in Medicine
rat breathing pure oxygen
rat breathing normal air (less oxygen than pure oxygen)
Hemoglobin (Hb)
Figure Source, Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imaging
BOLD Time CourseBlood Oxygenation Level-Dependent Signal
Positive BOLD response
InitialDip
OvershootPost-stimulusUndershoot
0
1
2
3
BO
LD R
espo
nse
(% s
igna
l cha
nge)
Time
Stimulus
Perhaps it should be BDLD?Blood DE-oxygenation level-dependent signal?
• Technically, “BOLD” is a misnomer• The fMRI signal is dependent on deoxygenation
rather than oxygenation per se• The more deoxy-Hb there is the lower the signal
fMRISignal
Amount of deoxy-Hb
“BDLD” idea from Bruce Pike, MNI
Initial Dip (Hypo-oxic Phase)• Transient increase in oxygen consumption, before
change in blood flow – Menon et al., 1995; Hu, et al., 1997
• Smaller amplitude than main BOLD signal– 10% of peak amplitude (e.g., 0.1% signal change)
• Potentially more spatially specific– Oxygen utilization may be more closely associated with
neuronal activity than positive response
Slide modified from Duke course
Rise (Hyperoxic Phase)
• Results from vasodilation of arterioles, resulting in a large increase in cerebral blood flow
• Inflection point can be used to index onset of processing
Slide modified from Duke course
Peak – Overshoot
• Over-compensatory response– More pronounced in BOLD signal measures than flow
measures
• Overshoot found in blocked designs with extended intervals– Signal saturates after ~10s of stimulation
Slide modified from Duke course
Sustained Response
• Blocked design analyses rest upon presence of sustained response– Comparison of sustained activity vs. baseline– Statistically simple, powerful
• Problems– Difficulty in identifying magnitude of activation– Little ability to describe form of hemodynamic response
Slide modified from Duke course
Undershoot
• Cerebral blood flow more locked to stimuli than cerebral blood volume– Increased blood volume with baseline flow leads to
decrease in MR signal
• More frequently observed for longer-duration stimuli (>10s)– Short duration stimuli may not evidence– May remain for 10s of seconds
Slide modified from Duke course
Trial to Trial Variability
Huettel, Song & McCarthy, 2004,Functional Magnetic Resonance Imaging
Variability of HRF Between SubjectsAguirre, Zarahn & D’Esposito, 1998• HRF shows considerable variability between subjects
• Within subjects, responses are more consistent, although there is still some variability between sessions
different subjects
same subject, same session same subject, different session
Variability of HRF Between AreasPossible caveat: HRF may also vary between areas, not just subjects
• Buckner et al., 1996: • noted a delay of .5-1 sec between visual and prefrontal regions• vasculature difference?• processing latency?
• Bug or feature? • Menon & Kim – mental chronometry
Buckner et al., 1996
Variability Between Subjects/Areas
• greater variability between subjects than between regions
• deviations from canonical HRF cause false negatives (Type II errors)
• Consider including a run to establish subject-specific HRFs from robust area like M1
Handwerker et al., 2004, Neuroimage
Sampling Rate
Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imaging
Linearity of BOLD response
Source: Dale & Buckner, 1997
Linearity:“Do things add up?”
red = 2 - 1
green = 3 - 2
Sync each trial response to start of trial
Not quite linear but good enough!
Section 2From Neurons to BOLD
From Neurons to BOLD
• Any similarity in the shapes of the curves for action potentials and the BOLD response is purely coincidental (but still kinda cool)
-70
-55
0
40
Refractory period
Dep
olar
izat
ion R
epolarization
Vo
ltage
(m
V)
Time (ms)
0
1
UndershootBO
LD
Sig
na
l Ch
ang
e (
%)
Time (s)
Positive BOLD Response
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
What does electrophysiology measure?
Source: http://www.cin.uni-tuebingen.de/research/methods-in-neuroscience/networks.php
Raw microelectrode signal
Filter out low frequencies Action Potentials (APs)
Filter out high frequencies Local Field Potentials (LFPs)
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
Logothetis et al. (2001)• combined BOLD fMRI and
electrophysiological recordings • found that BOLD activity is more closely
related to LFPs than MUA
Source: Logothetis et al., 2001, Nature
4 s stimulus
12 s stimulus
24 s stimulus
Even Simple Circuits Aren’t Simple
Will BOLD activation from the blue voxel reflect:
• output of the black neuron (action potentials)?
• excitatory input (green synapses)?
• inhibitory input (red synapses)?
• inputs from the same layer (which constitute ~80% of synapses)?
• feedforward projections (from lower-tier areas)?
• feedback projections (from higher-tier areas)?
Lower tier area (e.g., thalamus)
Middle tier area (e.g., V1, primary
visual cortex)
Higher tier area (e.g., V2, secondary
visual cortex)
…
gray matter(dendrites, cell bodies
& synapses)
white matter(axons)
Comparing Electrophysiolgy and BOLD
Data Source: Disbrow et al., 2000, PNASFigure Source, Huettel, Song & McCarthy, Functional Magnetic Resonance Imaging
fMRI Measures the Population Activity
Ideas from: Scannell & Young, 1999, Proc Biol Sci fMRI for Dummies
Effects of Practice
Verb generation Verb generation after 15 min practice
Raichle & Posner, Images of Mind cover image
fMRI for Dummies
Bug or feature?• fMRI adaptation enables us to study the tuning of
neurons
Contents of a Voxel
Source: Logothetis, 2008, Nature
Capillary beds within the cortex
Source: Duvernoy, Delon & Vannson, 1981, Brain
Research Bulletin
“Brain vs. Vein”• 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
Source: Ono et al., 1990, Atlas of the Cerebral Sulci
Dilation of Arterioles
• biggest changes in arteriole dilation occurred near stimulation; however, effects could also be observed several mm upstream
Source: Adapted from Takano et al., 2006, Nat Neurosci, by Huettel, et al., 2nd ed.
Tim
e
stim
max dilation ~3-6 s after stim
vasodilation could be induced by either electrical stimulation or release of Ca2+
Upstream Effects
• biggest changes in arteriole dilation occurred near stimulation; however, effects could also be observed several mm upstream
Source: Adapted from Iadecola et al., 1997, J Neurophysiol, by Huettel, et al., 2nd ed.
arteriole
veins
Don’t Trust Sinus Activity
• You will sometimes see bogus “activity” in the sagittal sinus
Energy Budget
Data Source: Atwell & Laughlin, 2001, J. Cereb. Blood Flow Metab.Figure Source, Huettel, Song & McCarthy, Functional Magnetic Resonance Imaging
The Forgotten Brain Cells
Common (i.e., Wrong) Wisdom
“Glial cells are probably not essential for processing information”(Kandel, Schwartz & Jessell, Principles of Neural Science 3rd Ed.)
• Astrocytes are adjacent to both synapses and blood vessels– well poised to adjust vascular response to neural activity
• Astrocytes outnumber neurons by at least 10:1 and comprise ~50% of the total CNS volume
Astrocytes perform a number of critically important functions:
1. Neurotransmitter uptake and recycling2. Neurometabolic regulation3. Cerebrovascular regulation4. Release of signaling molecules
(“gliotransmitters”)
Tripartite Synapse
Source: Figley & Stroman, 2011, EJN
Vasoactive Substances
• substances that cause the vessels to dilate• potassium ions (K+)
– move from intra- to extra-cellular space during synaptic activity
• adenosine– increases with high metabolic activity
• nitric oxide– released by local and distant activation
• gap junctions• calcium (Ca2+)
– triggered by neuronal activation
• dopamine
Information Source: Huettel, Song & McCarthy, 2nd ed.
What about inhibitory synapses?
• GABA = inhibitory neurotransmitter hyperpolarization (IPSP)
• less metabolically demanding than excitatory (glutamatergic) activity
• GABA can be taken up presynaptically rather than recycled through astrocytes
• Therefore, neurotransmission at inhibitory synapses likely influences the BOLD signal less than at excitatory synapses
Not Just Neurons
Leopold, 2009, based on data of Sirotin & Das, 2009, NatureSirotin & Das, 2009• awake macaque monkey sees tiny light in dark room
– red: keep tight fixation; green: relax– timing of red-green is periodic
• measure blood flow in area of peripheral visual cortex – away from foveal representation of fixation point– on some trials visual stimuli were presented to activate the measured area
Non-Neuronal Effects
Leopold, 2009, based on data of Sirotin & Das, 2009, Nature
Sirotin & Das, 2009• two components to blood flow in visual cortex (V1)
1. related to neuronal responses to visual stimuli
2. related anticipation of neural events
Properties of Predictive Response
• response follows expected trial timing– when trial timing is changed, monkey performs correctly but
this response persists for a few trials
• occurs even without stimulation• correlated with pupil diameter
– is it just general arousal?
• visual cortex response does not occur with predictive sequence of auditory events – suggests it’s more regionally specific than general arousal
• occurs in arterial signal
Gradient Echo vs. Spin Echo
Gradient Echo• high SNR• strong contribution of vessels
Spin Echo• lower SNR• weaker contribution of vessels
Source: Logothetis, 2008, Nature
The Concise SummaryWe sort of understand this
(e.g., psychophysics, neurophysiology)
We sort of understand this (MR Physics)We’re *&^%$#@ clueless here!
Is the fMRI Sky Falling?
Don’t Panic
• 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)– maybe anticipatory changes in blood flow are interesting too
Section 3Spatial Limits of fMRI
fMRI in the Big Picture
What Limits Spatial Resolution
• noise– smaller voxels have lower SNR
• head motion– the smaller your voxels, the more contamination head motion
induces
• temporal resolution– the smaller your voxels, the longer it takes to acquire the same
volume• 4 mm x 4 mm at 16 slices/sec• OR 1 mm x 1 mm at 1 slice/sec
• vasculature– depends on pulse sequences
• e.g., spin echo sequences reduce contributions from large vessels
– some preprocessing techniques may reduce contribution of large vessels (Menon, 2002, MRM)
Ocular Dominance Columns
• Columns on the order of ~0.5 mm have been observed with fMRI
Submillimeter Resolution
Goenze, Zappe & Logothetis, 2007, Magnetic Resonance Imaging• anaesthetized monkey; 4.7 T; contrast agent (MION)• ~0.3 x 0.3 x 2 mm
Gradient EchoFunctional
(superficial activationincludes vessels)
Spin EchoFunctional(activation
localized to Layer IV)
Spin EchoAnatomical
Gradient EchoAnatomical
vein
Stria of Gennari(Layer IV)
EXCEPT when the activated region does not fill the voxel (partial voluming)
Voxel Size
3 x 3 x 6= 54 mm3
e.g., SNR = 100
3 x 3 x 3= 27 mm3
e.g., SNR = 71
2.1 x 2.1 x 6= 27 mm3
e.g., SNR = 71
isotropic
non-isotropic
non-isotropic
In general, larger voxels buy you more SNR.
Partial Voluming
• The fMRI signal occurs in gray matter (where the synapses and dendrites are)
• If your voxel includes white matter (where the axons are), fluid, or space outside the brain, you effectively water down your signal
fMRI for Dummies
Partial Voluming
This voxel contains mostly gray matter
This voxel contains mostly white matter
This voxel contains both gray and white matter. Even if neurons within the voxel are strongly activated, the signal may be washed out by the absence of activation in white matter.
Partial voluming becomes more of a problem with larger voxel sizes
Worst case scenario: A 22 cm x 22 cm x 22 cm voxel would contain the whole brain
Partial volume effects: The combination, within a single voxel, of signal contributions from two or more distinct tissue types or functional regions (Huettel, Song & McCarthy, 2004)
The Initial Dip
• The initial dip seems to have better spatial specificity• However, it’s often called the “elusive initial dip” for a reason