What Neuroscientists Can and Cannot Learn from fMRI Last Update: January 18, 2012 Last Course: Psychology 9223, W2010, University of Western Ontario Jody Culham Brain and Mind Institute Department of Psychology University of Western Ontario

Section 1 The 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 Imaging based 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 Course Blood Oxygenation Level-Dependent Signal Positive BOLD response Initial Dip Overshoot Post-stimulus Undershoot BOLD Response (% signal change) 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 fMRI Signal Amount of deoxy-Hb Time “BDLD” idea from Bruce Pike, MNI

Deoxy-Hb Deoxy-Hb Concentration Time Stimulus

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

Hu et al., 1997, MRM Evolution of BOLD Response

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 Within subjects, responses are more consistent, although there is still some variability between sessions different subjects same subject, same sessionsame 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

Sampling Rate Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imaging

Linearity of BOLD response Source: Dale & Buckner, 1997 Linearity: “Do things add up?” red = green = Sync each trial response to start of trial Not quite linear but good enough!

Section 2 From 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) Refractory period Depolarization Repolarization Voltage (mV) Time (ms) 0 1 Undershoot BOLD Signal Change (%) Time (s) Positive BOLD Response

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? Source: 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, 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 fMRI for Dummies Bug or feature? fMRI adaptation enables us to study the tuning of neurons

Stimulus to BOLD Source: Arthurs & Boniface, 2002, Trends in Neurosciences

Vasculature: Brain vs. Vein Source: Menon & Kim, TICS

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

Vessel Valves Source: Harrison et al. (2002). Cerebral Cortex.

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. Time stim max dilation ~3-6 s after stim vasodilation could be induced by either electrical stimulation or release of Ca 2+

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 3 rd 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 recycling 2. Neurometabolic regulation 3. Cerebrovascular regulation 4. Release of signaling molecules (“gliotransmitters”) Tripartite Synapse Source: Figley & Stroman, 2011, EJN

Glycolysis Source: Raichle, 2001, Nature

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

Not Just Neurons Leopold, 2009, based on data of Sirotin & Das, 2009, Nature Sirotin & 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

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

The Concise Summary We 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 3 Spatial 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 Echo Functional (superficial activation includes vessels) Spin Echo Functional (activation localized to Layer IV) Spin Echo Anatomical Gradient Echo Anatomical 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 mm 3 e.g., SNR = x 3 x 3 = 27 mm 3 e.g., SNR = x 2.1 x 6 = 27 mm 3 e.g., SNR = 71 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