BOLD fMRI

John VanMeter, Ph.D.

Center for Functional and Molecular ImagingGeorgetown 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 about properties of BOLD

contrast mechanisms

Neuronal Activity and Blood Flow Changes: Initial Hypothesis

• Roy and Sherrington hypothesize 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 the 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

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

• 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)

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Oxy- vs. Deoxy- Hemoglobin

• 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

OxygenatedHemoglobin

DeoxygenatedHemoglobin

Spin GradientEcho (T2) Echo (T2*)

Oxygenation vs Local Field Changes

Bandettini and Wong. Int. J. Imaging Systems and Technology. 6:133 (1995)

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)

Basic Model of Relationship Between BOLD fMRI & Neuronal Activity

WHY DOESMRI SIGNALINCREASE?

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-to-glucose (OGI) for aerobic glycolysis but F&R saw about 1:10

• Implication is anaerobic glycolysis is used

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

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

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)

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 blood flow is to neuronal activity

Initial Dip

• Studies used very short TR (100ms) and visual stimulus for 10s at 4T or higher

• Examined time course of fMRI signal

• 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

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

First fMRI BOLD in Human

• Kwong (1992) demonstrated first BOLD-contrast 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

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

later

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, 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 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

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?

Image Resolution (2D)

• FOV - Field of View, prescribed area that will be covered in the acquisition

• Matrix size - how many voxels will be acquired in each dimension

• Rectangular FOV possible

• Voxel dimension (size) =FOV/matrix

Example

• FOV = 192mm x 192mm• Matrix = 64x64

• What is the voxel size in-plane?

3mm x 3mm

Slice Thickness Defines 3rd Dimension

• Does not have to match size of in-plane resolution

• Voxels are referred to as isotropic when all three sides have the same size

• Gaps between slices can be used to cover more of the brain

• 3D Acquisition has a 2nd phase encode for through plane dimension and effectively 3rd FOV dimension but usually presented on console as slice thickness

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

Signal to Noise Ratio

Spatial Resolution

TemporalResolution

(f)MRI Image Acquisition Constraints

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 547m x 547m resolution

fMRI of Ocular Dominance Columns

Ocular Dominance Columns - Take 2

• Cheng, 2001 used 4T with 470m2 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

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 time to peak between 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 peak) 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 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 does the HRF reflect a sum of the HRF for each stimulus?

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 adding 2 or more 3s stimuli - got smaller than predicted response

• Attributed to adaptation of neurons leading to reduced activity

• Support for linearity & superposition

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 first

• 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 a 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 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 increase in blood flow

• 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

• Definitive linkage of blood flow and neuronal energy metabolism still elusive