Contrasting effects of word length and visual contrast in fusiform and lingual gyri during reading

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DCM - the practical bits
Manuel Carreiras and Helmut Laufs
Thanks to previous former dummies,Andrea
Mechelli, Stefan Kiebel and Lee Harrison, Klaas
E. Stephan
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Structure

• 1. Quick recap on what DCM can do for you.
• 2. What to keep in mind when designing a DCM
  analysis
• 3. How to do DCM. What buttons to press etc.

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Functional Specialization Functional
Integration

• The organization of the primate brain is based
  upon two complementary principles
• 1) Functional Specialization (each area performs
  unique operations Joseph Gall, 1810)
• 2) Functional Integration (functions are emergent
  properties of interacting brain areas Pierre
  Flourens, 1823)
• Until recently, neuropsychological and functional
  imaging
• studies have focused on functional specialization

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Functional Effective Connectivity
Studies of functional connectivity investigate
the temporal correlations between neuronal
activity in different areas
Inferior Temporal
Inferior Frontal
Studies of effective connectivity investigate the
influence that one brain region exerts over
another and how this varies with the experimental
context
Inferior Temporal
Inferior Frontal
Inferior Temporal
Inferior Frontal
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Functional Connectivity
D
M
INPUT
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Effective Connectivity
(on a region)
D
M
INPUT
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Effective Connectivity
(on a region)
D
M
INPUT
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Effective Connectivity
(on a region)
D
M
INPUT
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Effective Connectivity
(on a region)
D
M
INPUT
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Effective Connectivity
(on a region and a connection)
D
M
INPUT
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Effective Connectivity
(on a connection only)
D
M
INPUT
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Methods for the study of Functional Effective
Connectivity
Functional Correlation Analysis Psychophysiologic
al Interaction (PPI)
Effective Auto-regressive (AR) models Volterra
Kernels Structural Equation Modelling Dynamic
Causal Modelling
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What to keep in mind if you want to do a DCM
analysis

1. Multifactorial design ( ... is optimal)

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3. TR lt 2 sec
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Planning a DCM-compatible study

• Experimental design
• preferably multi-factorial (e.g. at least 2 x 2)

1.Sensory input factor At least one factor that
varies the sensory input changing the stimulus
a perturbation to the system
2. Contextual factor At least one factor that
varies the context in which the perturbation
occurs. Often attentional factor, or change in
cognitive set etc.
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• Hypothesis and model
• define specific a priori hypotheses.
• DCM is not exploratory!

Specify your hypotheses as precisely as possible.
This requires neurobiological expertise (the fun
part) read lots of papers! Look for convergent
evidence from multiple methodologies and
disciplines. Anatomy is your friend.
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Defining your hypothesis
Hypothesis A attention modulates V5 directly
When attending to motion.

Parietal areas
V5

Hypothesis B Attention modulates effective
connectivity between PPC to V5
V1
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4.Evaluate whether DCM can answer your
question Can DCM distinguish between your
hypotheses?
Parietal areas
V5
Direct influence
V1
DCM cannot distinguish between direct and
indirect! Hypotheses of this nature cannot be
tested
In case of
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1.Specify your main hypothesis and its competing
hypotheses as precisely as possible using
convergent evidence from the empirical and
theoretical literature 2.Think specifically about
how your experiment will test the hypothesis and
whether the hypothesis is suitable for DCM to
test. 3. DCM is tricky, ask the experts during
the design stage. They are very helpful.
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A DCM in 5 easy steps

1. Specify the design matrix
2. Define the VOIs
3. Enter your chosen model
4. Look at the results
5. Compare models

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Specify design matrix

• Normal SPM regressors
• -no motion, no attention
• -motion, no attention
• -no motion, attention
• -motion, attention
• DCM analysis regressors(main effects)
• -no motion (photic)
• -motion
• -attention

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Defining VOIs

• Single subject choose co-ordinates from
  appropriate contrast.
• e.g. V5 from motion vs. no motion
• RFX DCM performed at 1st level, but define
  group maximum for area of interest, then in
  single subject find nearest local maximum to this
  using the same contrast and a liberal threshold
  (e.g. Plt0.05, uncorrected).

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PPC
PFC
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specify
NB in order!
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• Can select
• Effects of each condition
• Intrinsic connections
• Contrast of connections

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Bilinear state equation in DCM
state changes
intrinsic connectivity
m externalinputs
systemstate
direct inputs
modulation of connectivity
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Output
Latent (intrinsic) connectivity (A)
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Modulation of connections (B)
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Input (C)
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Comparing models
See what model best explains the data, e.g.
Original Model Attention modulates V1 to V5
Alternative Model Attention modulates V5
?
Penny WD, Stephan KE, Mechelli A, Friston KJ.
Comparing dynamic causal models. Neuroimage. 2004
Jul22(3)1157-72.
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PRACTICAL EXERCISE
PPC
PFC