fmri overview

Functional Magnetic Resonance Imaging (fMRI): a

quick overview

Matthew Baggott, Ph.D.Matthew@baggott.net

Section OverviewGoal 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

If you put someone in a very homogeneous magnetic field…

(image source: Wikipedia)

The protons in their body line up

(like spinning tops aligned with gravity)

Spin

Protons = hydrogen nucleus, abundant in water and fat

…then you can send a RF pulse, and get the protons to briefly

turn 90 degrees away from the magnetic field

before they ‘relax’ and realignlike 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

Their movement gives off a signal that you can pick up

(Head coil for measuringsignal from head)

(They emit energy at the same radio frequency they received until they return to their equilibrium state)

If you want to know where the signal is coming from…

Gradient coils let us create magnetic fields in any direction

make the field uneven and use pulses of different strengths and

directions

X CoilZ CoilY Coil

fnordtransceiver

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 cancels out

Image from Harvard whole brain Atlas

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)

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

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

The Blood Oxygen Level Dependent (“BOLD”) signal is slow

Visual cortex activity changes in response to a flashing checkboard in an early event-related fMRI study (Blamire et al. 1992)

ON = Checkboard shown

The Blood Oxygen Level Dependent (“BOLD”) signal is slow

Visual cortex activity changes in response to a flashing checkboard in an early event-related fMRI study (Blamire et al. 1992)

ON = Checkboard shown

The Blood Oxygen Level Dependent (“BOLD”) signal is slow

Visual cortex activity changes in response to a flashing checkboard in an early event-related fMRI study (Blamire et al. 1992)

ON = Checkboard shown

Response peaks around 6 seconds after stimulus

The Blood Oxygen Level Dependent (“BOLD”) signal is slow and ‘noisy’

Visual cortex activity changes in response to a flashing checkboard in an early event-related fMRI study (Blamire et al. 1992)

ON = Checkboard shown

Seemingly random fluctuations are ~40% as big as the response to the stimulus

Most fMRI images show statistical maps rather than raw changes in the BOLD signalThese statistical maps take into account the fact that different parts of the brain have more variable signals.

(Beauregard & Paquette 2006)

Blurry BOLD signal is projected onto high resolution structural data or an average brainResolution of functional data(volume pixel or voxel initially around 2 cm wide)

Voxels with statistically significant changes

Voxels with statistically significant changes

Blurry BOLD signal is projected onto high resolution structural data or an average brainResolution of functional data(volume pixel or voxel initially around 2 cm wide)

Voxels with statistically significant changes

Blurry BOLD signal is projected onto high resolution structural data or an average brainResolution of functional data(volume pixel or voxel initially around 2 cm wide)

Voxels with statistically significant changes

Blurry BOLD signal is projected onto high resolution structural data or an average brainResolution of functional data(volume pixel or voxel initially around 2 cm wide)

Voxels with statistically significant changes

Blurry BOLD signal is projected onto high resolution structural data or an average brainResolution of functional data(volume pixel or voxel initially around 2 cm wide)

fMRI analyses are usually based on subtraction of conditionsMost 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

What was compared to what?

(Beauregard & Paquette 2006)

What was compared to what?

(Beauregard & Paquette 2006)

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)

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/

Visual stimulation is often used to identify visual maps in an individual’s brain

(Dougherty et al. 2003)

Specialized visual areas

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

Really specialized visual areas

(After Op de Beek, Haushofer, & Kanwisher 2008)

BodiesFacesHousesOther objects

Specialized areas can be used to study neural correlates of conscious perception

(Tong, Nakayama, Vaughn, Kanwisher 1998)

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

Face area

House area

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)

The brain is 2% of the body but uses 20% of the energyTask-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)

The brain is 2% of the body but uses 20% of the energyTask-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)

(Shulman et al. 2004; Raichle and Mintun 2006; Photo by Ben Chenoweth)

What is the rest of the activity?

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)

Large decreases in brain activity are produced by anesthesia

(Alkire et al. 1997)

Awake Anesthetized

Cerebral metabolism measured by 18FDG-PET (Hot colors indicate higher glucose use)

Awake Anesthesia (Isoflurane)

mg/100gm/min

Can we find a way to analyze seemingly random signal fluctuations?

(Blamire et al. 1992)

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)

This default network is similar to networks active in internally focused tasks

(Buckner, Andrews-Hanna, & Schacter 2008)

Autobiographical Memory Thinking about Others’ Beliefs

Moral Decision MakingEnvisioning the Future

Default Network

Default network is anticorrelated with an externally focused network

(Buckner, Andrews-Hanna, & Schacter 2008)

Regions that negatively correlate with the default network are shown in cool colors; those that positively correlate are shown in warm colors

Default network is anticorrelated with an externally focused network

(Buckner, Andrews-Hanna, & Schacter 2008; time course from Fox and Greicius 2010)

(When one network gets more active, the other gets less active)

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Looking for correlated activity between brain areas is a powerful way to identify coordinated brain networks.

(Power et al. 2011)

Default

L. FEF

Parietal Attention

Ventral Attention

Frontal-Parietal Task Control

Correlated activity during movie viewing

Similar colors indicate brain regions that respond similarly to natural movies (Nishimoto, Huth, Vu, and Gallant 2011)

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

Some tools and resourcesThe 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/