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The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems Research Institute for Empirical Research in Economics University of Zurich Functional Imaging Laboratory (FIL) Wellcome Trust Centre for Neuroimaging University College London With many thanks for slides & images to: Meike Grol Tobias Sommer Ralf Deichmann

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Page 1: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

The physiology of the BOLD signal

Methods & models for fMRI data analysis18 February 2009

Klaas Enno Stephan

Laboratory for Social and Neural Systems ResearchInstitute for Empirical Research in EconomicsUniversity of Zurich

Functional Imaging Laboratory (FIL)Wellcome Trust Centre for NeuroimagingUniversity College London

With many thanks for slides & images to:

Meike Grol

Tobias Sommer

Ralf Deichmann

Page 2: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Ultrashort introduction to MRI physics

• Step 1: Place an object/subject in a big magnet

• Step 2: Apply radio waves

• Step 3: Measure emitted radio waves

Page 3: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Step 1: Place subject in a big magnet

Protons have “spins” (like gyroscopes). They have an orientation and a frequency.

When you put any material in an MRI scanner, the protons align with the

direction of the magnetic field.

Images: www.fmri4newbies.com

Page 4: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Images: Ralf Deichmann

Step 2: Apply radio waves

When you apply radio waves (RF pulse) at the appropriate frequency (Larmor frequency), you can change the orientation of the spins as the protons absorb energy.

After you turn off the RF pulse, as the protons return to their original orientations, they emit energy in the form of radio waves.

T2

T1

Page 5: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Step 3: Measure emitted radio waves

T1 = time constant of how quickly the protons realign with the magnetic field

T2 = time constant of how quickly the protons emit energy when recovering to equilibrium

fat has high signal bright

CSF has low signal dark

T1-WEIGHTED ANATOMICAL IMAGE T2-WEIGHTED ANATOMICAL IMAGE

fat has low signal dark

CSF has high signal bright

Images: fmri4newbies.com

Page 6: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

T2* weighted images

• Two factors contribute to the decay of transverse magnetization:1) molecular interactions2) local inhomogeneities of the magnetic field

• The combined time constant is called T2*.

• fMRI uses acquisition techniques (e.g. EPI) that are sensitive to changes in T2*.

The general principle of MRI:– excite spins in static field by RF pulses & detect the emitted RF– use an acquisition technique that is sensitive to local differences in

T1, T2 or T2*– construct a spatial image

Page 7: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Functional MRI (fMRI)

• Uses echo planar imaging (EPI) for fast acquisition of T2*-weighted images.

• Spatial resolution:– 3 mm (standard 1.5 T scanner)– < 200 μm (high-field systems)

• Sampling speed:– 1 slice: 50-100 ms

• Problems:– distortion and signal dropouts in certain regions– sensitive to head motion of subjects during

scanning

• Requires spatial pre-processing and statistical analysis.

EPI(T2*)

T1

dropout

But what is it that makes T2* weighted images “functional”?

Page 8: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

The BOLD contrast

B0

BOLD (Blood Oxygenation Level Dependent) contrast =

measures inhomogeneities in the magnetic field due to changes in the level of O2 in the blood

Oxygenated hemoglobine:

Diamagnetic (non-magnetic)

No signal loss…

Deoxygenated hemoglobine:

Paramagnetic (magnetic)

signal loss !

Images: Huettel, Song & McCarthy 2004, Functional Magnetic Resonance Imaging

Page 9: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

The BOLD contrast

synaptic activity synaptic activity neuronal metabolism neuronal metabolism

neurovascularcoupling

D’Esposito et al. 2003

rCBF rCBF

deoxy-Hb/oxy-Hb deoxy-Hb/oxy-Hb

Due to an over-compensatory increase of rCBF, increased neural activity decreases the relative amount of deoxy-Hb

higher T2* signal intensity

? ?

Page 10: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

The BOLD contrast

Source: Jorge Jovicich, fMRIB Brief Introduction to fMRI

neural activity blood flow oxyhemoglobin T2* MR signal

REST

ACTIVITY

Page 11: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

The temporal properties of the BOLD signal

• sometimes shows initial undershoot

• peaks after 4-6 secs

• back to baseline after approx. 30 secs

• can vary between regions and subjects

BriefStimulus

Undershoot

InitialUndershoot

Peak

Page 12: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

0 2 4 6 8 10 12 14

0

0.2

0.4

0 2 4 6 8 10 12 14

0

0.5

1

0 2 4 6 8 10 12 14

-0.6

-0.4

-0.2

0

0.2

RBMN

, = 0.5

CBMN

, = 0.5

RBMN

, = 1

CBMN

, = 1

RBMN

, = 2

CBMN

, = 2sf

tionflow induc

(rCBF)

s

v

stimulus functions

v

q q/vvEf,EEfqτ /α

dHbchanges in

100 )( /αvfvτ

volumechanges in

1

f

q

)1(

fγsxs

signalryvasodilato

u

s

CuxBuAdt

dx m

j

jj

1

)(

t

neural state equation

1

3.4

111),(

3

002

001

32100

k

TEErk

TEEk

vkv

qkqkV

S

Svq

hemodynamic state equations

f

Balloon model

BOLD signal change equation

BOLD signal is a nonlinear function of

rCBF

Stephan et al. 2007, NeuroImage

Page 13: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Three important questions

1. Is the BOLD signal more strongly related to neuronal action potentials or to local field potentials (LFP)?

2. How does the BOLD signal reflect the energy demands of the brain?

3. What does a negative BOLD signal mean?

Page 14: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Neurophysiological basis of the BOLD signal: soma or synapse?

Page 15: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

In early experiments comparing human BOLD signals and monkey electrophysiological data, BOLD signals were found to be correlated with action potentials.

BOLD & action potentials

Heeger et al. 2000, Nat. Neurosci.Rees et al. 2000, Nat. Neurosci.

Red curve: “average firing rate inmonkey V1, as a function of contrast,estimated from a largedatabase of microelectroderecordings (333 neurons).”

Page 16: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Local Field Potentials (LFP)• reflect summation of post-synaptic

potentials

Multi-Unit Activity (MUA)• reflects action potentials/spiking

Logothetis et al. (2001)• combined BOLD fMRI and

electrophysiological recordings • found that BOLD activity is more closely

related to LFPs than MUA

Logothetis et al., 2001, Nature

Action potentials vs. postsynaptic activity

Page 17: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

BOLD & LFPs

Logothetis & Wandell 2004, Ann. Rev. Physiol.

blue: LFPred: BOLDgrey: predicted BOLD

Page 18: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Thomsen et al. 2004, J. Physiol.

rCBF-increase can be independent from spiking activity, but seems to be always correlated to LFPs

• GABAA antagonist picrotoxine increased spiking activity without increase in rCBF...

• ... and without disturbing neurovascular coupling per se

Lauritzen et al. 2003

Dissociation between action potentials and rCBF

Page 19: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Current conclusion: BOLD signal seems to be more strongly correlated to

postsynaptic activity

Lauritzen 2005, Nat. Neurosci. Rev.

BOLD seems to reflect the input to a neuronal population as well as its intrinsic processing.

Page 20: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Three important questions

1. Is the BOLD signal more strongly related to neuronal action potentials or to local field potentials (LFP)?

2. How does the BOLD signal reflect the energy demands of the brain?

3. What does a negative BOLD signal mean?

Page 21: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Is the BOLD signal driven by energy demands or synaptic processes?

synaptic activity synaptic activity neuronal metabolism neuronal metabolism

neurovascularcoupling

D’Esposito et al. 2003

rCBF rCBF

deoxy-Hb/oxy-Hb deoxy-Hb/oxy-Hb

? ?

Page 22: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Schwartz et al. 1979, Science

Localisation of neuronal energy consumption

Salt loading in rats and 2-deoxyglucose mapping

→ glucose utilization in the posterior pituitary but not in paraventricular and supraoptic nuclei (which

release ADH & oxytocin at their axonal endings in the post. pituitary)

→ neuronal energy consumption takes place at the synapses, not at the cell body

Compatible with findings on BOLD relation to LFPs!

But does not tell us whether BOLD induction is due to energy demands or feedforward synaptic processes...

Page 23: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Lack of energy?

1. Initial dip: possible to get more O2 from the blood without increasing rCBF (which happens later in time).

2. No compensatory increase in blood flow during hypoxia (Mintun et al. 2001).

Friston et al. 2000, NeuroImage

rCBF map during visual stimulation under normal conditions

rCBF map during visual stimulation under hypoxia

Mintun et al. 2001, PNAS

Page 24: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

3. Sustained visual stimulation is associated with an increase in rCBF far in excess of O2 consumption. But over time, O2 consumption begins to increase as blood flow falls (Mintun et al. 2002).

Blood flow seems to be controlled by other factors than a lack of energy.

Lack of energy?

Mintun et al. 2002, NeuroImage

Page 25: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Blood flow might be directly driven by excitatory postsynaptic

processes

Page 26: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Glutamatergic synapses: A feedforward system for eliciting the

BOLD signal?

Lauritzen 2005, Nat. Neurosci. Rev.

Page 27: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Forward control of blood flow

Courtesy: Marieke Scholvinck

Page 28: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

O2 levels determine whether synaptic activity leads to arteriolar vasodilation or vasoconstriction

Gordon et al. 2008, Nature

Page 29: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Energetic consequences of postsynaptic activity

Courtesy: Tobias Sommer

Glutamate reuptake by astrocytes triggers glucose metabolism

ATP needed for restoring ionic gradients, transmitter reuptake etc.

Attwell & Iadecola 2002, TINS.

Page 30: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Three important questions

1. Is the BOLD signal more strongly related to neuronal action potentials or to local field potentials (LFP)?

2. How does the BOLD signal reflect the energy demands of the brain?

3. What does a negative BOLD signal mean?

Page 31: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Shmuel et al. 2006, Nat. Neurosci.

Negative BOLD is correlated with decreases in LFPs

positive BOLD positive BOLD

Page 32: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Impact of inhibitory postsynaptic potentials (IPSPs) on blood flow

Lauritzen 2005, Nat. Neurosci. Rev.

Page 33: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Negative BOLD signals due to IPSPs?

Lauritzen 2005, Nat. Neurosci. Rev.

Page 34: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

BOLDBOLDcontrastcontrast

bloodbloodflowflow

bloodbloodvolumevolume

oxygenoxygenutilizationutilization

structural lesionsstructural lesions(compression)(compression)

autoregulationautoregulation(vasodilation)(vasodilation)

cerebrovascularcerebrovasculardiseasedisease

medicationsmedications

hypoxiahypoxia

anemiaanemiasmokingsmoking

hypercapniahypercapnia

degenerative degenerative diseasedisease

volume statusvolume status

anesthesia/sleepanesthesia/sleep biophysical effectsbiophysical effects

Potential physiological influences on BOLD

Page 35: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Drug effects

Analgetics (NSAIDs)

Coronary heart disease

Page 36: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

Summary

• The BOLD signal seems to be more strongly related to LFPs than to spiking activity.

• The BOLD signal seems to reflect the input to a neuronal population as well as its intrinsic processing, not the outputs from that population.

• Blood flow seems to be controlled in a forward fashion by postsynaptic processes leading to the release of vasodilators.

• Negative BOLD signals may result from IPSPs.

• Various drugs can interfere with the BOLD response.

Page 37: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems
Page 38: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

MRI physics in a nutshell - I

• Inside static magnetic field:Spins of protons align with magnetic field B longitudinal magnetisation (because spins carry an elementary magnetisation)

• Intended manipulation:Make spins rotate (precess) about the direction of B (like a gyroscope).

• Precession (Lamor) frequency is proportional to B, e.g. 64 MHz for 1.5 T

B

Page 39: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

MRI physics in a nutshell - II

• How do we do it?RF pulses (Larmor frequency!) push M away from B transverse magnetization

• During precession, each proton emits an RF signal.

• After the RF pulse, M will re-align to B within 2-3 secs “relaxation”

• Relaxation has a longitudinal (T1) and a transverse (T2) component tissue-dependent time constants! T2

T1

Page 40: The physiology of the BOLD signal Methods & models for fMRI data analysis 18 February 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems

MRI physics in a nutshell - III

• Two factors contribute to the decay of transverse magnetization:1) molecular interactions2) local inhomogeneities of the magnetic field

→ leads to dephasing of the spins• The combined time constant is called T2*.

fMRI uses acquisition techniques (e.g. EPI) that are sensitive to changes in T2*.

The general principle of MRI:–excite spins in static field by RF pulses & detect the emitted RF–use an acquisition technique that is sensitive to local differences in T1, T2 or T2*–construct a spatial image (“how” is the topic of a different talk)