1 neuroimaging: from image to inference chris rorden –fmri limitations: relative to other tools...
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Neuroimaging: from image to Inference
Chris Rorden– fMRI limitations: relative to other tools used to infer
brain function.– fMRI signal: tiny, slow, hidden in noise.– fMRI processing: a sample experiment.– fMRI anatomy: stereotaxic space.
– See also:– http://www.biac.duke.edu/education/courses/fall05/fmri/
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Modern neuroscience
Different tools exist for inferring brain function.
No single tool dominates, as each has limitations.
This course focuses on fMRI.
Temporal resolution
good (millisecond) poor (months)
good(neuron)
poor(whole brain)
scr
erp
fmri
pettmsnirs
lesionseegiap
Sp
ati
al re
solu
tion
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Single Cell Recording
Directly measure neural activity.Exquisite timing informationPrecise spatial informationOften, no statistics required!
•Each line is one trial.•Each stripe is neuron firing.•Note: firing increases whenever monkey reaches or watches reaching.
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Single Cell Recording
With SCR, we are very close to the data.We can clearly see big effects without
processing.Unfortunately, there are limitations:
– Invasive (needle in brain)Typically constrained to animals, so difficult to directly
infer human brain function.
– Limited field of view: just a few neurons at a time.
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fMRI Processing
Unlike SCR, we must heavily process fMRI data to extract a signal.
The signal in the raw fMRI data is influenced by many factors other than brain activity.
We need to filter the data to remove these artifacts.
We will examine why each of these steps is used.
Processing Steps1. Motion Correct
1. Spatial
2. Intensity
2. Physiological Noise Removal
3. Temporal Filtering
4. Temporal Slice Time Correct
5. Spatial Smoothing
6. Normalize
7. Statistics
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fMRI signal sluggish
Unlike SCR, huge delay between activity and signal change.
Visual cortex shows peak response ~5s after visual stimuli.
Indirect measure of brain activity
0 6 12 18 24
2
1
0
Time (seconds)
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What is the fMRI signal
fMRI is ‘Blood Oxygenation Level Dependent’ measure (BOLD).
Brain regions become oxygen rich after activity. Very indirect measure.
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Lets conduct a study
Anatomical Hypothesis: lesion studies suggest location for motor-hand areas.
Ask person to tap finger while in MRI scanner – predict contralateral activity in motor hand area..
M1: movement
S1: sensation
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Task
Task has three conditions:1. Up arrows: do nothing
2. Left arrows: press left button each time arrow flashes.
3. Right arrows: press right button every time arrow flashes.
Block design: each condition repeats rapidly for 11.2 sec.
No sequential repeats: block of left arrows always followed by block of either up or right arrows.
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Data Collection
Participant Lies in scanner watching computer screen.
Taps left/right finger after seeing left/right arrows.
Collect 120 3D volumes of data, one every 3s (total time = 6min).
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Raw Data
The scanner reconstructs 120 3D volumes.– Each volume = 64x64x36
voxels– Each voxel is 3x3x3mm.
We need to process this raw data to detect task-related changes.
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Motion Correction
Unfortunately, people move their heads a little during scanning. We need to process the data to create motion-stabilized
images. Otherwise, we will not be looking at the same brain area over
time.
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Spatial smoothing
Each voxel is noisy By blurring the image, we can get a more stable signal
(neighbors show similar effects, noise spikes attenuated).
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Predicted fMRI signal
We need to generate a statistical model. We convolve expected brain activity with
hemodynamic response to get predicted signal.
Predicted fMRI signal
=
Neural Signal HRF
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Predicted fMRI signal
We generate predictions for neural responses for the left and right arrows across our dataset.
Statistics will identify which areas show this pattern of activity. Several possible statistical contrasts (crucial to inference):
1. Activity correlated with left arrows: visual cortex, bilateral motor.2. More activity for left than right arrows: contralateral motor.
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Voxelwise statistics
We compute the probability for every voxel in the brain.
We observe that right arrows precede activation in the left motor cortex and right cerebellum.
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fMRI signal change is tiny, noise is high
Right motor cortex becomes brighter following movement of left hand. Note signal increases from ~12950 to ~13100, only about 1.2% And this is after all of our complicated processing to reduce noise.
0 100 200 300
L_Tap right
12900
13000
13100
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Coordinates - normalization
Different people’s brains look different ‘Normalizing’ adjusts overall size and orientation
Raw Images Normalized Images
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Why normalize?
Stereotaxic coordinates analogous to longitude– Universal description for anatomical location– Allows other to replicate findings– Allows between-subject analysis: crucial for inference that
effects generalize across humanity.
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Goals for this course
fMRI is notoriously difficult technique– Sluggish signal– Poor signal/noise– Must find meaningful statistical contrasts
This seminar reveals how to– Devise meaningful contrasts– Maximize signal, minimize noise– Control for statistical errors.
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Safety
MRI uses very strong magnet and radiofrequencies– 3T= ~x60,000 field that aligns compass– Metal and electronic devices are not compatible.
MRI scanning makes loud sounds– Rapid gradient switching creates auditory noise.– Auditory protection crucial.
MRI scanning is confined– Claustrophobia is a concern.
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Summary of Lectures
1. Introduction2. Physics I: Hardware and Acquisition3. Physics II: Contrasts and Protocols4. fMRI Paradigm Design5. fMRI Statistics and Thresholding6. fMRI Spatial Processing7. fMRI Temporal Processing8. VBM & DTI: subtle structural changes9. Lesion Mapping: overt structural changes10. Advanced and Alternative Techniques
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Which tools
There are many tools available for analysis.
Different strengths.We predominantly focus
on SPM and FSL.These are both free,
popular and have good user support.
Tool SFN04
SPM 78.5%
AFNI 9.1%
FSL 7.4%
BrainVoyager 4.1%
https://cirl.berkeley.edu/view/Grants/BrainPyMotivation
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Reporting findings
How do we describe anatomy to others?
We could use anatomical names, but often hard to identify.
We could use Brodmann’s Areas, but this requires histology – not suitable for invivo research.
Both show large between-subject variability.
Requires anatomical coordinate system.
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Relative Coordinates
On the globe we talk about North, South, East and West.
Lets explore the coordinates for the brain.
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Orientation - animals
Cranialhead
Rostralbeak Caudal
tail
Dorsalback
Ventralbelly
Rostral Caudal
Ventral
Dorsal
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Coordinates – Dorsal Ventral
Human dorsal/ventral differ for brain and spine.– Head/Foot, Superior/Inferior, Anterior/Posterior not ambiguous.
DorsalVentral
Dorsal
Ventral
DorsalVentral
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Coordinates – Human
CR CR
C
R
Human rostral/caudal differ for brain and spine.– Head/Foot, Superior/Inferior, Anterior/Posterior not ambiguous.
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Orientation
Human anatomy described as if person is standing
If person is lying down, we would still say the head is superior to feet.
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Anatomy – Relative Directions
Posterior <> Anterior
Pos
teri
or <
> A
nte
rior
Ven
tral
<>
Dor
sal
lateral < medial > lateral
Anterior/Posterioraka Rostral/Caudal
Ventral/Dorsalaka Inferior/Superioraka Foot/Head
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Coordinates - Anatomy
3 Common Views of Brain:– Coronal (head on)– Axial (bird’s eye), aka
Transverse. – Sagittal (profile)
sagittalcoronal
axial
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Coronal
Corona: a coronal plane is parallel to crown that passes from ear to ear
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Transverse
Transverse/Axial: perpendicular to the long axis
Example: cucumber slices are transverse to long axis.
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Sagittal
Sagittal – ‘arrow like’– Sagittal cut divides object into left
and right– sagittal suture looks like an arrow.
top view
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Sagittal and Midsagittal
A Sagittal slice down the midline is called the ‘midsagittal’ view.
midsagittal sagittal
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Oblique Slices
Slices that are not cut parallel to an orthogonal plane are called ‘oblique’.
The oblique blue slice is neither Coronal nor Axial.
Ax
Cor
Oblique