1. Declaration of Conflict of Interest or Relationship
Speaker Name: Thomas Liu
I have no conflicts of interest to disclose with regard to the subject matter of
this presentation.

2. Thomas Liu University of California, San Diego May 4, 2008
Functional MRI Signal Interpretation and Calibration
Thomas Liu University of California, San Diego May 4, 2008

3. Topics BOLD signal model Sources of Variability and Confounds
Normalization Methods
Calibration Methods

4. BOLD Contrast
Source: Ogawa et al., 1992

5. BOLD Signal Change
Baseline Signal TE
Activation Signal

6. Hemoglobin and Field Inhomogeneities
Oxygen binds to the iron atoms to form oxyhemoglobin HbO2
Release of O2 to tissue results in deoxyhemoglobin dHBO2 B0
Field Maps
More dHB
Less dHB

7. Signal Decay Some dHB, Some dephasing TE
time TE
Some dHB, Some dephasing
More dHB, More dephasing, Decrease in MR signal

8. BOLD Signal Equation Cerebral Blood Volume Large vessels Linear =1
Ogawa et al, 1993
Large vessels
Linear =1
Cerebral Blood Volume
Diffusion around small vessels
Quadratic =2
Simulations suggest  1.5 is a reasonable value
Ogawa et al, 1993; Boxerman et al 1995, Hoge et al. 1999

9. Blood Flow and Oxygen Metabolism
Cerebral Blood Flow (CBF) measures delivery of blood to brain tissue (units of ml/(g-min))
Cerebral Metabolic Rate of (CMRO2) is the rate of oxygen consumption (units of mol/(g-min))
CBF [O2]arterial
Oxygen extraction fraction (E)
CMRO2
CMRO2= E CBF [O2]arterial

10. Deoxyhemoglobin O2 [dHB]venous  E [O2]arterial / 4 = CMRO2 / 4CBF

11. fMRI: Spatial Temporal Dynamics
arteriole
capillary bed
venule
CBF
oxyHb
deoxyHb
Neural activity
CMRO2
CMRO2
CBV
CBF
dHb
Positive BOLD
Post-stimulus Response
Initial dip
CMRO2
CBV
CBF
dHb
CMRO2
CBV
CBF
dHb

12. BOLD Signal Equation (Davis Model)
Grubb’s Relation;  0.38
Maximal BOLD signal

13. Davis Model
Hoge et al. 1999

14. BOLD Signal Path Cerebral Blood Volume deoxyHb Neural Activity
Blood Flow
Metabolism
(CMRO2)
BOLD
Signal

15. Interpreting BOLD
Most fMRI studies assume that the BOLD signal is is proportional to brain activity.
This is a reasonable assumption for basic studies of healthy young unmedicated subjects.
However, the assumption is less valid for studies where disease, medication, and age may be a factor.
Boynton et al, 1996

16. Variability in BOLD amplitude
Data courtesy of J. Liau

17. BOLD Signal Chain
Ianetti and Wise, MRI, 2007

18. Effect of Age
D’Esposito et al 2003

19. Effects of Vascular Disease
D’Esposito et al 2003
Iadecola et al 2003

20. Carbon Dioxide
Lower CBF
Higher CBF
Cohen et al 2002

21. Caffeine
Lower CBF
Liu et al 2004

22. Interpreting BOLD
Ianetti and Wise, MRI, 2007

23. ASL measures of regional baseline CBF
Response to Breathhold or CO2; Resting-state Fluctuations
Cerebral
Blood Volume
deoxyHb
Neural
Activity
Cerebral
Blood Flow
Metabolism
(CMRO2)
BOLD
Signal
Trust MRI Measures of whole brain venous oxygenation

24. BOLD and Venous Oxygenation
Inter-subject Differences in M can lead to inter-subject differences in BOLD
TRUST MRI (Lu et al 2007): Measures of whole brain venous oxygenation saturation. Yv
[dHB]venous
BOLD

25. Venous Oxygenation (TRUST MRI)
Lu, ISMRM 2007

26. TRUST MRI
Lu et al, Abstract 855, ISMRM 2008

27. BOLD and Baseline CBF
CBF0 M
BOLD
dHb
BOLD ?
CBF
BOLD

28. BOLD variability and Baseline CBF
M appears to be independent of CBF -- effects of increased CBF and decreased [dHb] appear to cancel out
Variability in the BOLD response across subjects appears to be driven by inter-subject differences in the CBF response.
Liau et al, Abstract 854, ISMRM 2008

29. Breathold/Hypercapnic Normalization1

30. Breathhold Calibration
Breathhold Signal
Thomason et al, 2007

31. Breathhold Calibration
Thomason et al, 2007

32. Hypercapnic Calibration
Cohen et al, 2004

33. Scaling with Resting-State Fluctuations
Wise et al 2004;

34. Scaling with Resting-State Fluctuations
Birn et al 2006;

35. Scaling with Resting-State Fluctuations
Kannapurti and Biswal 2008; also Abstract 750

36. Summary of Normalization Approaches
Additional measures can account for BOLD variability due to variations in baseline blood flow, volume, oxygenation, field strength, etc.
Measures of venous oxygenation, cerebral blood flow, and resting fluctuations have the advantage of not requiring the subject to perform additional tasks.
These approaches offer some insight into the factors that can affect the BOLD response between subjects, groups, and conditions.

37. ASL
Signal
Cerebral
Blood Volume
deoxyHb
Neural
Activity
Cerebral
Blood Flow
Metabolism
(CMRO2)
BOLD
Signal

38. Calibrated fMRI (Davis et al 1998)

39. Experimental Protocol
2x Block design visual stimulus
20s
60s
2x 5% CO2 Scans
2min
air
3min
CO2
%∆CBF
%∆BOLD M
%∆CMRO2

40. Calibrated fMRI
Ances et al, NIMG 2007

41. Calibrated fMRI of HIV
Ances et al, in preparation

42. Effect of age on CBF and BOLD
Young Old
Normalized CMRO2
Young Old
%CMRO2
Restom et al, NIMG 2007

43. Calibrated fMRI
Can provide insights that BOLD measures alone cannot provide.
Can be difficult to apply to cognitive tasks and special populations, due to low sensitivity of ASL.
The need for breathhold or hypercapnia can also be an issue. Hyperoxia-based method may be an alternative.

44. Conclusions
The BOLD signal is a complex function of the baseline state and changes in blood flow, volume, and metabolism.
Differences in the BOLD signal do NOT always reflect differences in neural activity.
Instead they may reflect differences in the baseline vascular or metabolic state.
Normalization methods can help to reduce inter-subject variability.
Calibrated fMRI can provide additional insights into differences in brain activity, especially in the presence of disease, medication, and age.

45. Acknowledgements Beau Ances Yashar Behzadi Rick Buxton David Dubowitz
Joy Liau
Oleg Leontiev
Joanna Perthen
Khaled Restom
Eric Wong