Introduction: fMRI for Newbies

MRI vs. fMRI Functional MRI (fMRI) studies brain function. MRI studies brain anatomy.

Brain Imaging: Anatomy CAT Photography PET MRI Source: modified from Posner & Raichle, Images of Mind

 neural activity   blood oxygen   fMRI signal MRI vs. fMRI MRI fMRI high resolution (1 mm) low resolution (~3 mm but can be better) one image … fMRI Blood Oxygenation Level Dependent (BOLD) signal indirect measure of neural activity many images (e.g., every 2 sec for 5 mins)  neural activity   blood oxygen   fMRI signal

The First “Brain Imaging Experiment” … and probably the cheapest one too! E = mc2 ??? Angelo Mosso Italian physiologist (1846-1910) “[In Mosso’s experiments] the subject to be observed lay on a delicately balanced table which could tip downward either at the head or at the foot if the weight of either end were increased. The moment emotional or intellectual activity began in the subject, down went the balance at the head-end, in consequence of the redistribution of blood in his system.” -- William James, Principles of Psychology (1890)

The Rise of fMRI Number of papers (PubMed) Year of Publication 800 700 600 500 Number of papers (PubMed) 400 300 200 100 1990 1995 2000 Year of Publication Slide modified from Mel Goodale

fMRI Activation Flickering Checkerboard Brain Activity Time  OFF (60 s) - ON (60 s) -OFF (60 s) - ON (60 s) - OFF (60 s) Brain Activity Time  Source: Kwong et al., 1992

PET and fMRI Activation Source: Posner & Raichle, Images of Mind

fMRI Setup

Category-Specific Visual Areas objects faces Malach, 2002, TICS Parahippocampal Place Area (PPA) place-selective places > (objects and faces) places > scrambled images places Fusiform Face Area (FFA) or pFs face-selective faces > (objects & scenes) faces > scrambled images ~ posterior fusiform sulcus (pFs) Lateral Occipital (LO) object-selective objects > (faces & scenes) objects > scrambled images

A Simple Experiment: LO Localizer Lateral Occipital Complex responds when subject views objects Blank Screen Intact Objects Scrambled Objects TIME One volume (12 slices) every 2 seconds for 272 seconds (4 minutes, 32 seconds) Condition changes every 16 seconds (8 volumes)

fMRI Experiment Stages: Prep 1) Prepare subject Consent form Safety screening Instructions and practice trials if appropriate 2) Shimming putting body in magnetic field makes it non-uniform adjust 3 orthogonal weak magnets to make magnetic field as homogenous as possible 3) Sagittals Take images along the midline to use to plan slices Note: That’s one g, two t’s In this example, these are the functional slices we want: 12 slices x 6 mm

fMRI Experiment Stages: Anatomicals 4) Take anatomical (T1) images high-resolution images (e.g., 0.75 x 0.75 x 3.0 mm) 3D data: 3 spatial dimensions, sampled at one point in time 64 anatomical slices takes ~4 minutes 64 slices x 3 mm

Slice Terminology VOXEL (Volumetric Pixel) IN-PLANE SLICE Slice Thickness e.g., 6 mm Number of Slices e.g., 10 SAGITTAL SLICE VOXEL (Volumetric Pixel) 3 mm 6 mm Matrix Size e.g., 64 x 64 In-plane resolution e.g., 192 mm / 64 = 3 mm IN-PLANE SLICE Field of View (FOV) e.g., 19.2 cm

fMRI Experiment Stages: Functionals 5) Take functional (T2*) images images are indirectly related to neural activity usually low resolution images (3 x 3 x 6 mm) all slices at one time = a volume (sometimes also called an image) sample many volumes (time points) (e.g., 1 volume every 2 seconds for 136 volumes = 272 sec = 4:32) 4D data: 3 spatial, 1 temporal …

Anatomic Slices Corresponding to Functional Slices

Time Courses Arbitrary signal varies from voxel to voxel, day to day, subject to subject (ARBITRARY UNITS) MR SIGNAL TIME To make the y-axis more meaningful, we usually convert the signal into units of % change: 100*(x - baseline)/baseline Changes are typically in the order of 0.5-4 %. MR SIGNAL (% Change)

Activation Statistics Functional images Time fMRI Signal (% change) ROI Time Course Condition ~2s Region of interest (ROI) Condition 1 Statistical Map superimposed on anatomical MRI image Condition 2 Time ... ~ 5 min

Statistical Maps & Time Courses Use stat maps to pick regions Then extract the time course

2D  3D

Design Jargon: Runs session: all of the scans collected from one subject in one day run (or scan): one continuous period of fMRI scanning (~5-7 min) experiment: a set of conditions you want to compare to each other condition: one set of stimuli or one task 4 stimulus conditions + 1 baseline condition (fixation) Note: Terminology can vary from one fMRI site to another (e.g., some places use “scan” to refer to what we’ve called a volume). A session consists of one or more experiments. Each experiment consists of several (e.g., 1-8) runs More runs/expt are needed when signal:noise is low or the effect is weak. Thus each session consists of numerous (e.g., 5-20) runs (e.g., 0.5 – 3 hours)

Design Jargon: Paradigm paradigm (or protocol): the set of conditions and their order used in a particular run volume #1 (time = 0) volume #105 (time = 105 vol x 2 sec/vol = 210 sec = 3:30) run epoch: one instance of a condition first “objects right” epoch second “objects right” epoch epoch 8 vol x 2 sec/vol = 16 sec Time

fMRI Equipment Magnet (4T) Gradient Coil Head Coil Surface Coil RF Coil gradient coil (inside) Head Coil Surface Coil Source: Joe Gati, photos

What Does fMRI Measure? Big magnetic field RF (radio frequency) coil protons (hydrogen molecules) in body become aligned to field RF (radio frequency) coil radio frequency pulse knocks protons over as protons realign with field, they emit energy that coil receives (like an antenna) Gradient coils make it possible to encode spatial information MR signal differs depending on concentration of hydrogen in an area (anatomical MRI) amount of oxy- vs. deoxyhemoglobin in an area (functional MRI)

BOLD signal Blood Oxygen Level Dependent signal neural activity   blood flow   oxyhemoglobin   T2*   MR signal Source: fMRIB Brief Introduction to fMRI

JODY – THE FOLLOWING SLIDES ARE FROM THE NORWAY PAGE

Statistical Maps & Time Courses Use stat maps to pick regions Then extract the time course

Percent Signal Change 505 1% 500 205 200 Slide from Duke course

Stats on Anatomical

2D  3D

Design Jargon: Runs session: all of the scans collected from one subject in one day run (or scan): one continuous period of fMRI scanning (~5-7 min) experiment: a set of conditions you want to compare to each other condition: one set of stimuli or one task 2 stimulus conditions + 1 baseline condition (fixation) Note: Terminology can vary from one fMRI site to another (e.g., some places use “scan” to refer to what we’ve called a volume). A session consists of one or more experiments. Each experiment consists of several (e.g., 1-8) runs More runs/expt are needed when signal:noise is low or the effect is weak. Thus each session consists of numerous (e.g., 5-20) runs (e.g., 0.5 – 3 hours)

Design Jargon: Paradigm paradigm (or protocol): the set of conditions and their order used in a particular run epoch: one instance of a condition epoch 8 vol x 2 sec/vol = 16 sec volume #1 (time = 0) volume #136 (time = 136 vol x 2 sec/vol = 272 sec = 4:32) run first “intact objects” epoch first “scrambled objects” epoch second “intact objects” epoch Time

Recipe for MRI 1) Put subject in big magnetic field (leave him there) 2) Transmit radio waves into subject [about 3 ms] 3) Turn off radio wave transmitter 4) Receive radio waves re-transmitted by subject Manipulate re-transmission with magnetic fields during this readout interval [10-100 ms: MRI is not a snapshot] 5) Store measured radio wave data vs. time Now go back to 2) to get some more data 6) Process raw data to reconstruct images 7) Allow subject to leave scanner (this is optional) Source: Robert Cox’s web slides

Necessary Equipment Magnet Gradient Coil RF Coil 4T magnet RF Coil (inside) Magnet Gradient Coil RF Coil Source for Photos: Joe Gati

Susceptibility Artifacts T1-weighted image T2*-weighted image sinuses ear canals -artifacts occur near junctions between air and tissue sinuses, ear canals

The Benefit of Susceptibility Susceptibility variations can also be seen around blood vessels where deoxyhemoglobin affects T2* in nearby tissue Aha! Modified from: Robert Cox’s web slides

BOLD Correlations Local Field Potentials (LFP) reflect post-synaptic potentials similar to what EEG (ERPs) and MEG measure Multi-Unit Activity (MUA) reflects action potentials similar to what most electrophysiology measures Logothetis et al. (2001) combined BOLD fMRI and electrophysiological recordings found that BOLD activity is more closely related to LFPs than MUA Source: Logothetis et al., 2001, Nature

Comparing Electrophysiolgy and BOLD Data Source: Disbrow et al., 2000, PNAS Figure Source, Huettel, Song & McCarthy, Functional Magnetic Resonance Imaging

fMRI Measures the Population Activity population activity depends on how active the neurons are how many neurons are active manipulations that change the activity of many neurons a little have a show bigger activation differences than manipulations that change the activation of a few neurons a lot attention  activity learning  activity fMRI may not match single neuron physiology results Verb generation Verb generation after 15 min practice Ideas from: Scannell & Young, 1999, Proc Biol Sci Raichle & Posner, Images of Mind cover image

Why are vessels a problem? large vessels produce BOLD activation further from the true site of activation than small vessels (especially problematic for high-resolution fMRI) large vessels line the sulci and make it hard to tell which bank of a sulcus the activity arises from the % signal change in large vessels can be considerably higher than in small vessels (e.g., 10% vs. 2%) activation in large vessels occurs later than in small ones vessel artifacts are worse with gradient echo sequences (compared to asymmetric spin echo for example) and low field strengths Source: Ono et al., 1990, Atlas of the Cerebral Sulci

Don’t Trust Sinus Activity You will sometimes see bogus “activity” in the sagittal sinus

More Caveats “brain vs. vein” debate source of signal affects spatial resolution scientists haven’t agreed on a single theory to explain the relationship between oxygen, glucose metabolism and blood flow no one really understands how neurons trigger increased blood flow neural synchrony may be a factor

Bottom Line Despite all the caveats, questions and concerns, BOLD imaging is well-correlated with results from other methods BOLD imaging can resolve activation at a fairly small scale (e.g., retinotopic mapping) PSPs and action potentials are correlated so either way, it’s getting at something meaningful even if BOLD activation doesn’t correlate completely with electrophysiology, that doesn’t mean it’s wrong may be picking up other processing info (e.g., PSPs, synchrony)