Functional MRI: techniques and applications
Susan Bookheimer, Ph.D.
UCLA Center for Cognitive Neurosciences
Outline
• Basis of fMRI signal; how it works, what it
measures
• fMRI experimental design
• New techniques
• Clinical applications
• Research applications
Introduction to Functional
Imaging
• Neurovascular Coupling: Increased local
brain activity leads to:
– Increased glucose utilization
– Increased cerebral blood flow
– Increased cerebral blood volume
– Minimal increase in oxygen utilization
– Increased deoxyhemoglobin concentration
Functional Magnetic Resonance
Imaging (FMRI)
• MRI scanning of brain function (vs. structure)
• An indirect measure of increased regional
cerebral blood flow during neural activity
• During increased brain activity, MRI signal
intensity (“brightness”) increases with the
increase in oxyhemoglobin concentration
• Tells us which brain regions are “working”
during task performance
Principles of fMRI
• Indirect measure of blood flow
– Measures changes in magnetic susceptibility due
to change in ratio of oxygenated vs. deoxygenated
blood that accompanies increased neural activity
• Relative measure
– change across states (rest, activity) of arbitrary
units of signal intensity
Assumptions in fMRI
• Assumes relatively intact blood flow
response
• Permits relative, activation based
measurements only
• Requires adequate task performance
fMRI techniques
• Fast- scanning: Echoplanar (EPI) imaging
– Gradient echo EPI: susceptibility weighted
– Spin echo or asymmetric spin echo EPI
– Spiral
– Arterial spin labeling
Image processing
• Image reconstruction into a time series of
volumes
• Test the extent to which the MR signal
intensity conforms to the predicted
hemodynamic response
• Present results in an accessible format
Practical issues
• Getting people in the scanner
• Stimulus presentation
• Head motion
– restraint
– Mathematical correction (eg AIR)
Conceptual and methodogical
aspects of experimental design • There are two aspects of fMRI design that are important to
distinguish
• Conceptual design
– How do we design tasks to properly measure the processes of interest?
– The issues here are very similar to those in cognitive psychology
• Methodological design
– How can we construct a task paradigm to optimize our ability to measure the effects of interest, within the specific constraints of the fMRI scanning environment?
fMRI experimental design: A basic plan
Define mental process
to examine
Define tasks to manipulate
that process
Measure fMRI data
during tasks
Compare fMRI data
between tasks
Control
Ex B
Ex A - }
- }
Hierarchical Common
baseline
Ex B Ex A
Control
Parallel
Ex B Ex A
Ex A Ex B >
>
Parametric
A< A < A < A
Tailored Baseline
Ex A > Ctl A
Ex B > Ctl B >}
Selective
attention
A B C
A B C
A B C
Factorial Designs
Ex A Ex B
AxB
Mixed, Nested Designs
Conjunction Designs
Priming/Adaptation Designs
The subtraction method
• Acquire data under two
conditions
– These conditions
putatively differ only in
the cognitive process of
interest
• Compare brain images
acquired during those
conditions
• Regions of difference
reflect activation due to the
“subtracted” process of
interest
Petersen et al., 1988
Hierarchical subtraction example from Petersen, 1991
• Rest Control
• Auditory words vs. rest: A1, word recognition centers
• Visual words vs rest: visual areas, word form areas
• Reading or repeating words vs passive words: motor areas
• Generating words vs. repeating: semantic (language) areas
- }
- }
- } Semantic
Motor
Sensory
Experimental design models • Hierarchical designs
– Eg: Peterson et al language study
– Sensory control (see words)
– Output control (read words aloud)
– Language task (generate associates)
• Use a cognitive subtraction model
– Equate demands on all factors except one
• Rely on theory of additive factors
– active areas remain the same throughout the hierarchy
– One level of hierarchy
– Test for violation of additivity assumption
– Allows you to see common areas active for A
and B
– Assumes A and B have similar psychometric
properties (ie, level of difficulty, variation, and
distribution in the population)
– Need additional approach to see unique areas
Ex B Ex A
Control
Common Baseline
Directed Attention Models
• All stimuli identical in all conditions
• Direct attention towards different features
• Implicit or explicit
• Assumes process is modified by directed attention
• Assumes passive processing does not capture your variable of interest
Example: implicit selective
attention with parallel comparisons
• Subjects hear pairs of sentences.
• Task: judge if the sentences mean the same thing
• Implicit Manipulation: sentences differ on semantic or syntactic basis
– “The boy went to the store- The boy went to the market”
– “The city is east of the lake. East of the city is the lake”
• Comparisons:
– Common baseline: each vs. rest
– Parallel comparisons: semantic vs syntax and reverse
Implicit Directed attenion
• EG Dapretto et al
• Instructions are the same; process required to
reach a response differs
• Syntax vs semantics: sentence comprehension
task.
– Do the sentences mean the same thing (Y N)
– The boy has gone to the market. The boy has gone to
the store
– The city is east of the lake. East of the lake is the city.
Parametric designs
• Employs continuous variation in a stimulus/task parameter
– E.g., working memory load, stimulus contrast
• Inference:
– Modulation of activity reflects sensitivity to the modulated parameter
Priming/adaptation designs
• Presentation of an item multiple times leads to changes in
activity
– Usually decreased activity upon repetition
• Inference:
– Regions showing decreased activity are sensitive to (i.e. represent)
whatever stimulus features were repeated
• Requires version of pure modulation assumption
– Assumes that processing of specific features is reduced but that the
task is otherwise qualitatively the same
Can adaptation fMRI characterize
neural representations?
• A voxel containing neurons that respond to all
politicians, irrespective of party
• A voxel containing some specifically
Democratic neurons, and other specifically
Republican neurons.
Two stimuli: can neurons tell the
difference?
From R. Raizada
Neural adaptation to repeated stimuli does show the difference:
What counts as repetition for neurons in a voxel?
It’s a politician Same neurons, adapting:
It’s a politician again
It’s a
Republican
Different, fresh neurons:
It’s a Democrat From R. Raizada
Blocked vs. Event-Related fMRI
BLOCKED:
SPACED MIXED TRIAL:
RAPID MIXED TRIAL:
From R. Buckner, HBM2001
Event-Related Designs
• Event-related or single trial experiments
– Have stimuli presented 1 at a time rather than in
blocks
– Adjust for the hemodynamic response function
– Bin like stimuli, obtain averaged HRF
– Compare HRFs across stimulus types
– Long ISI studies (15 seconds) allow for complete
relaxation of HRF (implicit resting control)
– Short ISI studies model additive response of like
stimuli and adjust
Event-Related fMRI Design
Optimized Random Sequence
(Wager & Nichols 2003)
ISI = 500-1500 ms
Jitter = 0-500 ms
2 s
2 s
2 s
+
+
+
TR = 3 s
TR = 3 s
Episodic Retrieval:
R-K Distinction (Eldridge,
Knowlton et al 2000)
• Remember (R) - recognition with conscious
recollection
– Episodic memory
• Know (K) - recognition without recollection
– Non-episodic memory
Two-Group Designs
• Two-group designs
– Hypothesis: groups differ in activation vs
control comparisons
– Different from resting state differences ala
FDG
– Performance confounds
% c
orr
ect
Match Label Control0
20
40
60
80
100
High-Functioning
Autistic Boys
Normal Adults
Accuracy
TD: Directed vs Averted Gaze
(negative emotions)
Amygdala,
hippocampus,
Medial PFC,
lateral PFC
Visual and HC
Imaging Genetics
• Growing Field
• Examines differences in brain structure/function/connectivity as a result of possessing different genetic polymorphisms
• Usually chosen for conferring risk for a disorder
• Imaging differences seen in normal populations with different, common polymorphisms in the absence of obvious behavioral or phenotypic differences
fMRI in normal subjects with
genetic risk for AD Bookheimer, Small, et al, NEJM 2000
• Purpose: use fMRI to identify changes in brain function
prior to significant cognitive decline; predict outcome
• APOE-3 vs E-4 extremely healthy older volunteers
(X=63.5; N=30)
• Memory “stress-test” in cognitively normal elderly
– Memorize unrelated word pairs “justice-club”
– Scans compare learning/retrieval vs. control
Applications
• Mapping normal functions: within group
• Clinical applications: between group designs
– Surgical planning
– AD/AD risk
– Drug interventions
– Psychiatric disorders
Clinical Applications:
Neurosurgical planning
• Goal: Identify critical areas
• Task specificity issues
• Disruption by the lesion
• Language performance
Language Tasks • Object Naming
– Finding a name; expression
– Used in OR; alternate forms; reveals Broca’s area and
Basal temporal language area
• Auditory Naming
Smell with this “nose”
Color of grass “green”
– Finding a name; comprehension, expression
Conjunction Analysis
• Within task, repeat conditions (3 times)
• Across tasks, find areas of overlap
• Perform separately for receptive, expressive
tasks
• Allows low magnitude activations that are
consistent to show.
Pharmaco- fMRI
• Use fMRI to identify brain changes
associated with treatment
• Eg, Acetylcholine agonist treatment may
improve memory in AD
• fMRI Pre- and post-treatment with Aricept
Pre-Treatment
Post-Treatment
Donepezil Treatment- Mild AD
Related Paired-Associate Learning vs. Rest
Social Anxiety and amygdala
arousal Guyer et al, Arch Gen Psychiatry. 2008 65(11): 1303–1312.
Simulated online “chat” in social anxiety and control adolescents
Susan Y. Bookheimer, Ph.D.
Disgust and Threat Responses in
OCD (Shapira et al, Biol Psychiatry. 2003)
Threat
Disgust
Control OCD