1. Basis of the BOLD Signal
Christoph Korn
Andrea Dantas

2. Outline fMRI Physics BOLD Signal fMRI - Magnetic fields & spins
fMRI - Radio pulse & relaxation times
fMRI - Tissue contrasts
fMRI - BOLD & T2*
BOLD Signal
Brain Metabolism
Neural Basis of BOLD signal
Technique & Protocols
Advantages & Disadvantages
Areas for future research

3. What do we want to understand?
Singer et al., 2006

4. Which magnetic fields do we know?
1 Tesla = 20,000x Earth’s magnetic field

5. Where is the magnetic field in the scanner?
B0 = constant magnetic field
Along z-axis
For fMRI 1.5T or 3T Z

6. Where are our compass needles?
Protons have a spin and therefore a magnetic dipole moment MDM
They can align to external magnetic fields in two ways: parallel or anti-parallel

7. What happens in the scanner?
Outside scanner

8. What happens in the scanner?
Inside scanner (B0)
The protons of the H2O molecules in our body align along B0

9. Are there more up-spins than down-spins?
Yes and the excess spins create a new magnetic field M which we can measure
[T]

10. Do the spinning tops tumble?
Precession and Larmor frequency
ω = γ · B0
ω Larmor frequency
γ gyromagnetic constant
B0 static magnetic field
e.g. 1.5 T  ω = 64 MHz
z-axis

11. How do we measure spins? We have to disturb them How?
With a radiofrequency pulse with Larmor frequency

12. What happens if spins fall down?
z axis
x-y plane

13. What happens if spins fall down?
90° High frequency pulse
before
after
z axis
x-y plane
z axis
x-y plane

14. What is the T1 relaxation?
Recovery in z-axis = longitudinal relaxation = spin-lattice relaxation
Supplied energy lost
Spins re-align with B0 T1

15. What is the T2 relaxation?
Dephasing in x-y plane = horizontal relaxation = spin-spin relaxation
90° pulse
T2 relaxation

16. Why does this happen and what is T2*?
Two reasons for dephasing in x-y plane
Spin-spin interaction  T2
Local magnetic field inhomogeneities  T2*
Magnetic field inhomogeneities
T2(*) time constant

17. And? How can we use this for imaging?
Different tissues have different relaxation times
Let’s look at T1
Fat
White matter
Grey matter
CSF

18. And T2? Different tissues have different relaxation times CSF
Grey matter
White matter
Fat

19. How do the T1 & T2 contrasts look like?
Fat
White matter
Grey matter
CSF

20. How do we get these contrasts? How do we get a 3D-image?
Too much to explain here
Different times between high frequency pulses
Different gradients along magnetic field

21. Finally, what is BOLD? Blood Oxygen Level Dependent signal
O2 is transported by haemoglobin (Hb)

22. What is the difference between deoxyHb and oxyHb?
Remember T2* and field inhomogeneities?
DeoxyHb paramagnetic
strong field inhomogeneities
Fast dephasing
Fast T2*
OxyHb diamagnetic
weak field inhomogeneities
Slower dephasing
slower T2*

23. Better?
Singer et al., 2006

24. Outline fMRI Physics BOLD Signal fMRI - Magnetic fields & spins
fMRI - Radio pulse & relaxation times
fMRI - Tissue contrasts
fMRI - BOLD & T2*
BOLD Signal
Brain Metabolism
Neural Basis of BOLD signal
Technique & Protocols
Advantages & Disadvantages
Areas for future research

25. Brain Metabolism Review
Basic Facts
54ml of blood / 100g of brain tissue
Brain:
2-3% of body weight
20% of O2 consumption
For imaging purposes, the main vasculature concerned are the capillaries networks – where glucose and O2 exchanges happen

26. Principles of BOLD
BOLD contrast depends on the balance between O2 supply and consumption by the neural tissues
DeoxyHb is paramagnetic – as its proportion decreases, the MR signal increases and generates what is referred to as the BOLD signal

27. Neural Basis of BOLD – Energy Consumption Theory
Initial thoughts were that increase of blood flow was due to the increase in energy requirements of the active tissue
Most of the energy is spent maintaining action potentials and in post-synaptic signalling
Inhibitory synapses use less energy than excitatory ones – controversy around whether these generate a BOLD signal at all!!
Attwell, D. , Iadecola, C “The neural basis of functional brain imaging signals”. Trends in Neuroscience. 25 (12)

28. Neural Basis of BOLD – Blood Flow Increase
Energy use does not directly increase blood flow…so how does the brain cope with the increase in glucose and O2 demands?
Glutamate-generated Calcium influx at post-synaptic level releases potent vasodilators:
Nitric Oxide
Adenosine
Arachidonic Acid metabolites
Blood flow is increased over an area larger than the one with neuronal activity
Global blood flow changes also associated with dopamine, noradrenaline and serotonin
Not related with regional energy utilisation at all!!
Energy utilisation and increase in blood flow are processes that occur in parallel and are not causally related
Attwell, D. , Iadecola, C “The neural basis of functional brain imaging signals”. Trends in Neuroscience. 25 (12)

29. How can we (can we?) predict neural activity from fMRI signals?
to neurons per 1mm3 of brain tissue
109 synapses, depending on cortical thickness

30. What is in a Voxel? Volume of 55mm3
Using a 9-16 mm2 plane resolution and slice thickness of 5-7 mm
Only 3% of vessels and the rest are….(be prepared!!)
5.5 million neurons
x 1010 synapses
22km of dendrites
220km of axons

31. What are we actually measuring?
Inputs or Outputs?
BOLD responses correspond to intra-cortical processing and inputs, not outputs
Aligned with previous findings related to high activity and energy expenditure in processing and modulation
Excitation or inhibition circuits?
Excitation increases blood flow, but inhibition might too – ambiguous data
Neuronal deactivation is associated with vasoconstriction and reduction in blood flow (hence reduction in BOLD signal)
And what about the awake, but resting brain?
Challenges in interpreting BOLD signal
Presence of the signal without neuronal spiking
Logothetis, N. K. 2008, "What we can and cannot do with fMRI", Nature, vol. 453, pp

32. fMRI Study Designs Main types of study design:
Block design
Consecutive tasks in pre-defined time intervals (also referred to as “epochs”)
Event-related
Stimuli (events or trials) are presented
Higher image acquisition rates (1/sec)
5 minutes of scanning can result in over 80 MB of data!

33. Example of fMRI Protocol
Delay between the stimulus and the vascular changes – might take up to 6 secs
Initial “Dip” – decrease in BOLD signal due to O2 consumption

34. fMRI Image Processing Stages
Images are re-aligned
Spatial normalisation of images to a standard brain space
Smooth and normalise the data
Combine statistical maps with anatomical information
Result is a superposition of a statistical map on a raw image

35. Sample fMRI Images

36. Advantages of BOLD Advantages over other methods:
EEG / MEG – Poor spatial localisation, high number of electrodes needed
PET – Invasive and need to use potentially toxic contrast
Non-invasive
Increasing availability
High spatial and temporal resolution
Enables demonstration of entire network brain areas engaged in specific activities
Logothetis, N. K. 2008, "What we can and cannot do with fMRI", Nature, vol. 453, pp

37. Disadvantages of BOLD
Surrogate signal of haemodynamic activity – which has physical and biological constraints
Neuronal mass activity and not activity of specific neuronal units
Circuitry and functional organisation of the brain not fully understood
Difficult to differentiate between excitation/inhibition and neuromodulation
Signal intensity does not accurately differentiate between:
Different brain regions
Different tasks within the same region
Logothetis, N. K. 2008, "What we can and cannot do with fMRI", Nature, vol. 453, pp

38. Future Development Areas
Multimodal approach is the way forward!!!
Coupling of electrophysiological studies with BOLD
Further improvements to fMRI technology
Expansion of human and animal experimentation, enhancing the comprehension of the neural basis of haemodynamic responses
New smart contrast agents that do not rely on haemoglobin

39. References
Logothetis, N. K. 2008, "What we can and cannot do with fMRI", Nature, vol. 453, pp
Attwell, D. , Iadecola, C “The neural basis of functional brain imaging signals” Trends in Neuroscience. 25 (12)
Huettel, S. C., A. W. Song, and G. McCarthy. Functional Magnetic Resonance Imaging. 2nd ed. Sinauer Associates Inc., 2004
McRobbie, D.W., Moore, E.A., Graves, M.J., and Prince, M.R. MRI – From Picture to Proton. 2nd ed. Cambridge University Press, 2007
SIEMENS. Magnets, Spins and Resonance Ref Type: Report