How Neurons Become BOLD Jody Culham Brain and Mind Institute Department of Psychology Western University http://www.fmri4newbies.com/ How Neurons Become BOLD Last Update: September 26, 2016 Last Course: Psychology 9223, F2016, Western University

Section 1 The BOLD Signal

Hemoglobin (Hb)

Deoxygenated Blood  Signal Loss Seiji Ogawa Oxygenated blood? Diamagnetic Doesn’t distort surrounding magnetic field No signal loss… rat breathing pure oxygen 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 At Rest: Active: Blood Oxygen Level Dependent signal neural activity   blood flow   oxyhemoglobin   T2*   MR signal At Rest: Mxy Signal Mo sin T2* task T2* control Stask S Scontrol Active: time TEoptimum http://www.youtube.com/watch?v=VtR--B1oHoU 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 Time Amount of deoxy-Hb “BDLD” idea from Bruce Pike, MNI

Susceptibility A single bobby pin  susceptibility artifacts (drops in signal and distortions nearby)

Hbdeoxy ~= bobby pins Brain at rest T2*-weighted signal Initial Dip Vaso- dilation

BOLD Time Course Blood Oxygenation Level-Dependent Signal Positive BOLD response Initial Dip Overshoot Post-stimulus Undershoot 1 2 3 BOLD Response (% signal change) Time Stimulus

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

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

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

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

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 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 Effect of caffeine Liu et al, 2004, NeuroImage Reviewed in Handwerker et al. 2012, NeuroImage

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

Linearity of BOLD response “Do things add up?” red = 2 - 1 green = 3 - 2 Sync each trial response to start of trial Tzvi Not quite linear but good enough! Source: Dale & Buckner, 1997

Section 2 From Neurons to BOLD

From Neurons to BOLD Voltage (mV) BOLD Signal Change (%) Time (ms) Positive BOLD Response 40 1 Voltage (mV) Depolarization BOLD Signal Change (%) Repolarization -55 -70 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 Local Field Potentials (LFP) 24 s stimulus 12 s stimulus 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 4 s stimulus Source: Logothetis et al., 2001, Nature

Correlations between BOLD and LFP frequencies α (8-12 Hz) β (18-30 Hz) Total LFP (0-100 Hz) γ (40-100 Hz) gamma shares most info with BOLD

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: 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)? Middle tier area (e.g., V1, primary visual cortex) Higher tier area (e.g., V2, secondary visual cortex) …

Stimulation Affects Local Region and Connected Areas Optogenetic stimulation of mouse motor cortex leads to large BOLD response there and smaller BOLD response in thalamus Leopold (2010) comment on Lee et al., 2010, Nature

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

Verb generation after 15 min practice 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 Capillary beds within the cortex Source: Duvernoy, Delon & Vannson, 1981, Brain Research Bulletin Source: Logothetis, 2008, Nature

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

Source: Ono et al., 1990, Atlas of the Cerebral Sulci “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.

Vasodilation vasodilation could be induced by either electrical stimulation or release of Ca2+ stim Time max dilation ~3-6 s after stim two photon microscopy 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 Image from: http://www.colorado.edu/intphys/Class/IPHY3430-200/image/08-5.jpg (see copyright info at bottom of image) Common (i.e., Wrong) Wisdom “Glial cells are probably not essential for processing information” (Kandel, Schwartz & Jessell, Principles of Neural Science 3rd 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: Neurotransmitter uptake and recycling Neurometabolic regulation Cerebrovascular regulation Release of signaling molecules (“gliotransmitters”) Slide modified from talk by Chase Figley Source: Figley & Stroman, 2011, EJN

Glycolysis Source: Raichle, 2001, Nature

Data Source: Howarth et al., 2012 Energy Budget Data Source: Howarth et al., 2012 Figure Source, Huettel, Song & McCarthy, Functional Magnetic Resonance Imaging, 3rd ed.

Neurovascular Mousetrap Hillman et al., 2004, Annual Review of Neuroscience

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 Sirotin & Das, 2009 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 Sirotin & Das, 2009 Leopold, 2009, based on data of Sirotin & Das, 2009, Nature Sirotin & Das, 2009 two components to blood flow in visual cortex (V1) related to neuronal responses to visual stimuli 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 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