Functional Magnetic Resonance Imaging

1
Functional Magnetic Resonance Imaging

• Carol A. Seger
• Psychology
• Molecular, Cellular, and Integrative Neuroscience
• Michael Thaut
• Music, Theater, and Dance and MCIN

2
Outline

• Overview of fMRI
• Our labs research questions
• Open imaging issues in fMRI
• Spatial normalization and interindividual
  comparisons
• Functional connectivity analyses

3
(No Transcript)
4
fMRI what are we measuring?

• BOLD imaging
• Blood oxygenation level dependent contrast.
• Ratio of deoxyhemoglobin to oxyhemoglobin
• Essentially reflects blood flow (hemodynamic
  response)
• Hemodynamic response characteristics
• Tightly coupled to neural activity.
• Slow
• Additive
• Inherently comparative method

5
Steps in fMRI

• Design
• Image acquisition
• Anatomical images
• Functional images
• Across multiple tasks
• Preprocessing
• Slice timing correction
• Temporal smoothing
• Motion correction
• Spatial smoothing
• Normalization to template brain

• Statistical analyses
• Deconvolution of BOLD signal
• Voxel wise statistical analyses comparing BOLD
  signal to task
• Correction for multiple comparisons
• Functional connectivity analyses
• Data visualization
• False color overlay onto anatomical images
• Cortex inflation

6
Introduction to my research questions

• The roles of corticostriatal loops in human
  learning and cognition
• Corticostriatal loops and the basal ganglia
• Human stimulus-outcome learning
• Michael Thaut, Music Therapy.
• Rhythm and tempo processing, and its interactions
  with human motor performance.

7
Basal Ganglia A Striatum 1. Caudate
a. head b. body/tail 2.
Putamen 3. Ventral striatum / nucleus
accumbens B Output nuclei SNc, GPi
8
Motor Loop
Executive Loop
Visual Loop
Motivational Loop
9
Parallel Corticostriatal Loops
Temporal Cortex / Ventrolateral Prefrontal
Orbito- Frontal / Anterior Cingulate
Dorsolateral Prefrontal / Posterior Parietal
Premotor / SMA / Somato- sensory
Caudate Body/Tail
Ventral Striatum
Caudate Head
Putamen
GPi / SNr
GPi / SNr
GPi / SNr
GPi / SNr
Thalamus
Thalamus
Thalamus
Thalamus
Motivational Executive
Visual Motor
Associative
Modificed from Lawrence et al, 1998
10
Stimulus-outcome learning
Learn to respond to a particular stimulus or
situation with An appropriate response that will
result in an appropriate Outcome Many different
tasks Instrumental conditioning Arbitrary
motor response learning Categorization Example
study Visual categorization task Focus on the
visual loop
11
Method Typical Learning Task
Trial

• View stimulus
• Make response
• Button press indicating category
• Receive feedback
• Right or Wrong

Right
0
2500

3000
3500 ms
8 faces, 8 houses. Event related
analyses deconvolve BOLD on each trial. compare
different types of trials face trials vs house
trials correctly categorized vs error
12
Activation within the visual corticostriatal Loop
during categorization of faces.
Basal Ganglia Activity in the body of the
caudate associated with correct categorization
Visual Cortex Activity in the fusiform Gyrus
associated with Processing faces. FFA - Fusiform
face area
13
Thaut lab
14
Spatial normalization and Interindividual
comparisons

• Variability in brain size and shape across people
• Special issues in normalizing the basal ganglia.

15
(No Transcript)
16

• SPM
• 1. 12 parameter affine registration
• Registration using a spatial transformation model
  consisting of a linear combination of low-spatial
  frequency discrete cosine transform functions
• --gt 1176 df

17
Functional Connectivity

• Anatomical Connectivity measurements
• Diffusion Tensor Imaging
• Functional Connectivity measurements
• Model free approaches
• Model based approaches

18
Diffusion Tensor Imaging
White matter myelinated axons connecting brain
regions. Basal ganglia Verifying
corticostriatal loop anatomy in humans Examine
individual differences in anatomical connectivity
19
Principles of Functional Brain Organisation
Functional Connectivity Overview

• Functional specialisation (Localism)
• Assumption of functionally specialised brain
  regions

20
Step 1 Postulation of Model
- postulation of a hypothetical model of
inter-regional interactions
- should be based on known anatomical connections
Slide 10
y B x
21
Model freeFunctional connectivity

• Generally start with a seed region, then identify
  other regions using various methods
• Correlation
• Principal component analysis
• Partial least squares analysis
• Granger causality mapping
• Vector Autoregressive modeling
• Coherence analysis
• Spectral methods
• Fourier analysis or wavelets

22
Example connectivity maps
Granger Causal Modeling Red seed region Green
preceeds / predicts seed Blue follows /
predicted by seed
Coherence analysis Circle Seed in motor cortex
23
Corticostriatal interaction during categorization
RH
Granger Causality analysis Seed region Fusiform
Face Area predicted body/tail of the
caudate activity 8 / 8 subjects
LH
24
Model Bases Analyses Structural Equation Modeling
y B x
25
Summary - Future Directions

• Continue our work on corticostriatal loops in
  human learning and cognition.
• Anatomical Spatial Normalization
• Functional Connectivity
• Other imaging issues
• Comparisons across patient groups
• Better ways to deconvolve blood flow measures
• Funded by NIMH

26
Blocked Design
20-60 sec
20-60 sec fixation
trials
HRF

• Consecutive, rapid presentation for long
  duration.
• Use overlap to build a larger signal.
• Advantages
• Simple analysis.
• Optimal for detection.

27
Additivity of the hemodynamic response
1
2
3
28
11-41

• What does the basal ganglia do?
• Modulatory system
• Selection or gating of responses
• --- extending to strategies, etc.
• Accounts for symptoms of Parkinsons
• and Huntingtons diseases

W. W. Norton