Jody Culham Brain and Mind Institute Department of Psychology Western University http://www.fmri4newbies.com/ How Neurons Become BOLD Last Update: September 23, 2014 Last Course: Psychology 9223, F2014, Western.
Download ReportTranscript Jody Culham Brain and Mind Institute Department of Psychology Western University http://www.fmri4newbies.com/ How Neurons Become BOLD Last Update: September 23, 2014 Last Course: Psychology 9223, F2014, Western.
Jody Culham Brain and Mind Institute Department of Psychology Western University http://www.fmri4newbies.com/
How Neurons Become BOLD
Last Update: September 23, 2014 Last Course: Psychology 9223, F2014, Western University
Section 1 The BOLD Signal
Hemoglobin (Hb)
Deoxygenated Blood Signal Loss rat breathing pure oxygen • • • Oxygenated blood?
Diamagnetic Doesn ’t distort surrounding magnetic field No signal loss… rat breathing normal air (less than pure oxygen) • • • Deoxygenated blood?
Paramagnetic Distorts surrounding magnetic field Signal loss !!!
Images from Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imaging based on two papers from Ogawa et al., 1990, both in Magnetic Resonance in Medicine
BOLD signal B lood O xygen L evel D ependent signal neural activity blood flow oxyhemoglobin T2* MR signal At Rest: Active:
M xy Signal M o sin
S task S control T 2 * task T 2 * control
S TE optimum time
Source: Jorge Jovicich
Figure Source: Huettel, Song & McCarthy,
2004, Functional Magnetic Resonance Imaging
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 fMRI Signal Amount of deoxy-Hb
“BDLD” idea from Bruce Pike, MNI
Susceptibility A single bobby pin susceptibility artifacts (drops in signal and distortions nearby)
Brain at rest Initial Dip Vaso dilation Hb deoxy ~= bobby pins T2*-weighted signal
Evolution of BOLD Response
Hu et al., 1997, MRM
BOLD Time Course Blood Oxygenation Level-Dependent Signal Positive BOLD response 3 2 1 0 Initial Dip Overshoot Post-stimulus Undershoot Time Stimulus
Trial-to-Trial Variability
Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imaging
Variability of HRF Between Subjects Aguirre, Zarahn & D ’Esposito, 1998 • HRF shows considerable variability between subjects
different subjects
• Within subjects, responses are more consistent, although there is still some variability between sessions
same subject, same session same subject, different session
Variability of HRF Between Areas Possible 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
Factors That Affect HRF • drugs: alcohol, caffeine • digestion: fat consumption • aging • disease: dementia
Reviewed in Handwerker et al. 2012, NeuroImage
Effect of caffeine
Liu et al, 2004, NeuroImage
Sampling Rate
Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imaging
Linearity of BOLD response 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!
Source: Dale & Buckner, 1997
Section 2 From Neurons to BOLD
From Neurons to BOLD Positive BOLD Response 1 40 0 -55 -70 0 Refractory period Undershoot Time (ms) Time (s) • Any similarity in the shapes of the curves for action potentials and the BOLD response is purely coincidental (but still kinda cool)
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
What does electrophysiology measure?
Raw microelectrode signal Filter out low frequencies Action Potentials (APs) Filter out high frequencies Local Field Potentials (LFPs) Source: http://www.cin.uni-tuebingen.de/research/methods-in-neuroscience/networks.php
BOLD Correlations 24 s stimulus 12 s stimulus 4 s stimulus
Source: Logothetis et al., 2001, Nature
• • 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
Correlations between BOLD and LFP frequencies α (8-12 Hz) β (18-30 Hz) γ (40-100 Hz) gamma shares most info with BOLD
Even Simple Circuits Aren ’t Simple 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) 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)?
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
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
Bug or feature?
• fMRI adaptation enables us to study the tuning of neurons fMRI for Dummies
Stimulus to BOLD Source: Arthurs & Boniface, 2002,
Trends in Neurosciences
Brain and Blood The brain is ~2% of the body by weight …but it uses about 20% of the body ’s oxygen supply and 20-25% of its glucose supply
Vascular system
Vascular system
Contents of a Voxel
Source: Logothetis, 2008, Nature
Capillary beds within the cortex
Source: Duvernoy, Delon & Vannson, 1981, Brain Research Bulletin
Vasculature: Brain vs. Vein
Source: Menon & Kim, TICS
“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 up to 3 s later than in small ones Source: Ono et al., 1990,
Atlas of the Cerebral Sulci
Vessel Valves Source: Harrison et al. (2002).
Cerebral Cortex
.
stim Vasodilation vasodilation could be induced by either electrical stimulation or release of Ca 2+ max dilation ~3-6 s after stim • 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.
Upstream Effects arteriole veins • 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.
Don ’t Trust Sinus Activity • You will sometimes see bogus “activity” in the sagittal sinus
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 3 rd Ed.)
• Tripartite Synapse 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.
2.
3.
4.
Neurotransmitter uptake and recycling Neurometabolic regulation Cerebrovascular regulation Release of signaling molecules ( “gliotransmitters”)
Source: Figley & Stroman, 2011, EJN
Glycolysis
Source: Raichle, 2001, Nature
Energy Budget
Data Source: Howarth et al., 2012 Figure Source, Huettel, Song & McCarthy, Functional Magnetic Resonance Imaging, 3 rd ed.
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 (Ca 2+ ) – 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
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
Stimulus to BOLD Source: Arthurs & Boniface, 2002,
Trends in Neurosciences
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
We sort of understand this (e.g., psychophysics, neurophysiology) The Concise Summary We ’re *&^%$#@ clueless here!
We sort of understand this (MR Physics)
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 3 Spatial Limits of fMRI
MID-SAGITTAL SCOUT IMAGE
for slice selection Number of Slices e.g., 12 slices 6 mm thick Terminology
ONE VOLUME
one set of all slices
VOXEL (Volumetric Pixel)
In-plane resolution e.g., 192 mm / 64 = 3 mm 3 mm 6 mm
IN-PLANE SLICE
3 mm Matrix Size e.g., 64 x 64 Field of View (FOV) e.g., 19.2 cm
Typically ~36 slice planes
1 2 3 4 5 6 7 8 9 10 11 12 For simplicity… 12 slices
12 slices
12 11 10 4 3 2 1 9 8 7 6 5 Ascending, Non-Interleaved
1 2 3 4 5 6 7 8 9 10 11 12 Descending, Non-Interleaved
1 2 3 4 5 6 7 8 9 10 11 12 How we think slices profiles work
1 2 3 4 5 6 7 8 9 10 11 12 How slice profiles actually work slice sensitivity
Slices without Gap 1 2 3 4 5 6 7 8 9 10 11 12 • ensures brain tissue isn’t missed • but some brain tissue may be sampled on two adjacent slices • exciting one slice may affect adjacent slices • interleaved sequences recommended slice sensitivity
Descending, Interleaved 10 11 12 5 6 7 8 9 1 2 3 4 • interleaving ensures information doesn’t bleed between slices
Slices with Gap e.g., 5-mm slice thickness with 1-mm gap 1 2 3 4 5 6 7 8 9 10 11 12 • allows whole brain coverage with fewer slices • prevents bleeding between sequential slices slice sensitivity
Multiband Imaging 9 10 11 12 1 2 3 4 5 6 7 8 • collect multiple slices (e.g., 3 slices) in the same image and then separate the slices using known coil sensitivities • reduces the time required to sample the whole brain (e.g., to 1/3 for 3 slice multiband) • may reduce vulnerability to artifacts like head motion
4-slice multiband
non-isotropic Voxel Size isotropic
same size in 3 directions
non-isotropic 3 x 3 x 6 = 54 mm 3 e.g., SNR = 100 3 x 3 x 3 = 27 mm 3 e.g., SNR = 71 2.1 x 2.1 x 6 = 27 mm 3 e.g., SNR = 71 In general, larger voxels buy you more SNR.
EXCEPT when the activated region does not fill the voxel (partial voluming)
Partial Voluming 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) 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
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 Spin Echo Functional (activation localized to Layer IV) Gradient Echo Functional (superficial activation includes vessels) Stria of Gennari (Layer IV) Spin Echo Anatomical vein Gradient Echo Anatomical • •
Goenze, Zappe & Logothetis, 2007, Magnetic Resonance Imaging
anaesthetized monkey; 4.7 T; contrast agent (MION) ~0.3 x 0.3 x 2 mm
Can you follow some of this Methods section now?
stuff you should understand stuff your MR physicist or MR tech can explain
Gallivan et al., 2011, J. Neurosci.