1. Functional Magnetic
Resonance Imaging (fMRI): a
quick overview
Matthew Baggott, Ph.D.
Matthew@baggott.net

2. Section Overview
Goal is to understand fMRI well enough to make some sense of studies
We will discuss the basics of fMRI
– Indirect measure of neural activity
– (Actually measures local amount of de-oxygenated blood)
– Slow
– Noisy
– Often analyzed by subtracting different conditions (or by
correlating data)
In the next section, we will use what we learn to evaluate recent work
on the mechanisms of visuals in ayahuasca
Then we will discuss more general theories about psychedelic visuals

3. If you put someone in a very
homogeneous magnetic field…
(image source: Wikipedia)

4. The protons in their body line up
Protons = hydrogen nucleus, abundant in water and fat
(like spinning tops aligned with gravity)

5. …then you can send a RF pulse, and
get the protons to briefly turn 90
degrees away from the magnetic field

6. before they „relax‟ and realign
like spinning tops that pop back up after a push
(Their relaxation and return to equilibrium can be divided into the
components that are parallel and perpendicular to the magnetic field,
which take different times (called T1 and T2) and can be used to make
slightly different images

7. Their movement gives off a
signal that you can pick up
(Head coil for
measuring
signal from
head)
(They emit energy at the same radio frequency they received until they
return to their equilibrium state)

8. If you want to know where the signal
is coming from… Gradient coils let us create magnetic
fields in any direction
Z Coil
Y Coil
X Coil
fnord
transceiver
make the field uneven and use pulses
of different strengths and directions

9. Proton density and uneven magnetic fields
alter the image intensity
Proton density: density of
fat and water (important
for structural scans)
Uneven magnetic fields:
If each proton
experiences a slightly
different magnetic field,
the energy they give off
when they „relax‟ partly
Image from Harvard cancels out
whole brain Atlas

10. Magnetic field irregularities from
hemoglobin
Deoxyhemoglobin is a
significantly more
paramagnetic (with four
unpaired electrons) than
oxygenated hemoglobin
The amount of deoxy-
hemoglobin in each part of the
image alters the image.
Hemoglobin, which carries
oxygen in the blood
(image source: Wikipedia)

11. The magnetic difference between deoxy- and
oxygenated hemoglobin is the basis of the
Blood Oxygen Level Dependent (“BOLD”)
signal, used by almost all fMRI

12. The magnetic difference between deoxy- and
oxygenated hemoglobin is the basis of the
Blood Oxygen Level Dependent (“BOLD”)
signal, used by almost all fMRI
This is what we indirectly measure

13. The Blood Oxygen Level Dependent
(“BOLD”) signal is slow
ON = Checkboard shown
Visual cortex activity changes in response to a flashing checkboard in an early
event-related fMRI study (Blamire et al. 1992)

14. The Blood Oxygen Level Dependent
(“BOLD”) signal is slow
ON = Checkboard shown
Visual cortex activity changes in response to a flashing checkboard in an early
event-related fMRI study (Blamire et al. 1992)

15. The Blood Oxygen Level Dependent
(“BOLD”) signal is slow
ON = Checkboard shown
Response peaks around 6 seconds after stimulus
Visual cortex activity changes in response to a flashing checkboard in an early
event-related fMRI study (Blamire et al. 1992)

16. The Blood Oxygen Level Dependent
(“BOLD”) signal is slow and ‘noisy’
ON = Checkboard shown
Seemingly random fluctuations are ~40% as big as the response to the stimulus
Visual cortex activity changes in response to a flashing checkboard in an early
event-related fMRI study (Blamire et al. 1992)

17. Most fMRI images show statistical maps
rather than raw changes in the BOLD signal
These statistical maps take into account the fact that different parts of the brain
have more variable signals.
(Beauregard & Paquette 2006)

18. Blurry BOLD signal is projected onto high
resolution structural data or an average
brain
Resolution of functional data Voxels with statistically
(volume pixel or voxel initially significant changes
around 2 cm wide)

19. Blurry BOLD signal is projected onto high
resolution structural data or an average
brain
Resolution of functional data Voxels with statistically
(volume pixel or voxel initially significant changes
around 2 cm wide)

20. Blurry BOLD signal is projected onto high
resolution structural data or an average
brain
Resolution of functional data Voxels with statistically
(volume pixel or voxel initially significant changes
around 2 cm wide)

21. Blurry BOLD signal is projected onto high
resolution structural data or an average
brain
Resolution of functional data Voxels with statistically
(volume pixel or voxel initially significant changes
around 2 cm wide)

22. Blurry BOLD signal is projected onto high
resolution structural data or an average
brain
Resolution of functional data Voxels with statistically
(volume pixel or voxel initially significant changes
around 2 cm wide)

23. fMRI analyses are usually based on
subtraction of conditions
Most fMRI studies use a task-activation approach:
– participants do a task
– scientists look for which areas become more active
But “more active” compared to what?
(the brain is always active)
Best comparison is usually another similar task
Early studies compared Tasks vs. “Quiet rest”
– glossing over the fact that “Quiet rest” actually
involves very active minds

24. What was
compared to
what?
(Beauregard & Paquette 2006)

25. What was
compared to
what?
Mystical: Memory of Intense Closeness to God
Baseline: Memory of Intense Closeness to a Person
(This could go wrong in a lot of ways -- though you have to
start somewhere) (Beauregard & Paquette 2006)

26. So much data & so many comparisons, you need to
make sure you aren‟t finding activity due to
chance
Neural correlates of interspecies perspective taking in the post-
mortem Atlantic Salmon: An argument for multiple comparisons
correction (Bennett, Baird, Miller, and Wolford 2009 poster)
See Craig M. Bennett‟s blog post here:
http://prefrontal.org/blog/2009/09/the-story-behind-the-
atlantic-salmon/

27. Visual stimulation is often used to identify visual
maps in an individual‟s brain
(Dougherty et al. 2003)

28. Specialized visual areas
(You can make identical images using WebCaret, online software provided by the
Van Essen lab at Washington University)

29. Really specialized visual areas
Bodies
Faces
Houses
Other objects
(After Op de Beek, Haushofer, & Kanwisher 2008)

30. Specialized areas can be used to study neural
correlates of conscious perception
Face
area
House area
Left: When this image is viewed with red-green glasses, awareness switches
randomly between the face and house.
Right: BOLD signal in face and house sensitive areas change along with
consciousness
(Tong, Nakayama, Vaughn, Kanwisher 1998)

31. The brain is 2% of the
body but uses 20% of the
energy
(Shulman et al. 2004; Raichle and Mintun 2006; Photo by Ben Chenoweth)

32. The brain is 2% of the
body but uses 20% of the
energy
Task-related fluctuations
are a small part (<5%) of
the brain‟s overall activity
(Shulman et al. 2004; Raichle and Mintun 2006; Photo by Ben Chenoweth)

33. The brain is 2% of the
body but uses 20% of the
energy
Task-related fluctuations
are a small part (<5%) of
the brain‟s overall activity
Differences between normal and
pathological populations in task-
related changes are even smaller
(often <1%)
(Shulman et al. 2004; Raichle and Mintun 2006; Photo by Ben Chenoweth)

34. What is the rest of the
activity?
(Shulman et al. 2004; Raichle and Mintun 2006; Photo by Ben Chenoweth)

35. Most of the energy used by the brain
really is used to support ongoing
neuronal signaling
(Atwell & Laughlin 2001; Shulman et al. 2004; Raichle and Mintun 2006)

36. Large decreases in brain activity are
produced by anesthesia
Awake Anesthesia (Isoflurane)
mg/100gm/min
Awake Anesthetized
Cerebral metabolism measured by 18FDG-PET (Hot colors indicate higher glucose use)
(Alkire et al. 1997)

37. Can we find a way to analyze seemingly
random signal fluctuations?
(Blamire et al. 1992)

38. Yes, instead of subtracting activity
between tasks, you can correlate fMRI
signal between voxels
A “Default network” is active when research participants aren‟t told what to do.
Blue shows regions most active in “passive tasks” in a meta-analysis of PET data
(Buckner, Andrews-Hanna, & Schacter 2008)

39. This default network is Default Network
similar to networks
active in internally
focused tasks
Autobiographical Memory Thinking about Others‟ Beliefs
Envisioning the Future Moral Decision Making
(Buckner, Andrews-Hanna, & Schacter 2008)

40. Default network is anticorrelated with an
externally focused network
Regions that negatively correlate with the
default network are shown in cool colors; those
that positively correlate are shown in warm
colors
(Buckner, Andrews-Hanna, & Schacter 2008)

41. Default network is anticorrelated with an
externally focused network
(When one network gets more active, the other gets less active)
% Signal Change
(Buckner, Andrews-Hanna, & Schacter 2008; time course from Fox and Greicius 2010)

42. Looking for correlated activity between brain
areas is a powerful way to identify coordinated
brain networks.
Default
L. FEF
Parietal Attention
Ventral Attention
Frontal-Parietal Task Control
(Power et al. 2011)

43. Correlated activity during movie viewing
Similar colors indicate brain regions that respond similarly
to natural movies (Nishimoto, Huth, Vu, and Gallant 2011)

44. Take home
The BOLD signal is an indirect, slow measure of neural
activity
Miraculously, it works. Results are consistent with direct
electrocortical measurements, studies of brain injury, etc.
Always ask what conditions are being compared and
how/why brain activity might differ between them –the
study may not be measuring what it is trying to measure

45. Some tools and resources
The Whole Brain Atlas at Harvard is just what it sounds like.
http://www.med.harvard.edu/AANLIB/
BodyParts3D is an online tool for browsing (Creative Commons
licensed) gross anatomy diagrams. http://lifesciencedb.jp/bp3d/
NeuroSynth is an online platform for large-scale, automated synthesis
of functional magnetic resonance imaging (fMRI) data extracted from
published articles
brainSCANr is an online engine to search and visualize co-occurrence
of terms in the scientific literature. http://www.brainscanr.com/
WebCaret is an online tool for visualizing a database of surface and
volume fMRI data. http://sumsdb.wustl.edu/sums/