1. D Y N A M I C C A U S A L M O D E L L I N G
z = (A +  uj Bj)z + Cu
... the (un)practical side . j

2. What to keep in mind if you want to do a DCM analysis
Multifactorial design ( ... is optimal)
at least 1 factor for stimulus input
e.g. low vs. high pain
at least 1 factor for contextual input
e.g. attentional set

3. 2. Defined model to test 3. TR < 2 sec
DCM is not an exploratory technique!
3. TR < 2 sec
1st inaccuracy
2nd inaccuracy

4. How to define a model for DCM:
from hypothesis to model ...
Example:
P A I N u1
low high
T A S K (attention) u2
easy
hard

5. DLPFC
z = (A +  uj Bj)z + Cu . j -
INSULA
low pain
high pain

6. Direct ... DLPFC INSULA easy task hard task low pain high pain

7. currently not possible in DCM!
... or indirect influence?
DLPFC
INSULA
easy task
hard task
hard task
low pain
high pain SI
currently not possible in DCM!

8. DORSOLATERAL PREFRONTAL
one possible model
DORSOLATERAL PREFRONTAL
INSULA
low pain
high pain
easy task
hard task
hard task
ORBITOFRONTAL
easy task
hard task

9. The steps of a DCM analysis
1. set up (new) design matrix
2. define VOIs
3. enter DCM model
4. read output

10. Setting up the (new) design matrix
Regressors in ‚regular‘ SPM analysis:
easy task, low pain
easy task, high pain
hard task, low pain
hard task, high pain
Regressors for DCM analysis:
low pain
high pain
hard task
easy task

11. Define volumes of interest
1. DCM for a single subject analysis (i.e. no 2nd-level analysis intended):
determine representative coordinate for each brain region from the appropriate contrast (e.g. choose coordinate for SI from main effect pain)
Subject specific DCM, but results will eventually be entered into a 2nd-level analysis:
determine group maximum for the area of interest (e.g. from RFX analysis) in the appropriate contrast
in each subject, jump to local maximum nearest to the group maximum, using the same contrast and a liberal threshold (e.g. p<0.05, uncorrected)

12. Setting up the DCM model (1)

13. Setting up the DCM model (2)

14. Read output:
latent (intrinsic) connectivity (A)
insula
OFC
DLPFC

15. Read output: Modulation of connections (B) high pain low pain
hard task
easy task

16. Read output:
Input (C)
high
easy
DLPFC
OFC
insula
low
hard

17. What you really need for a DCM analysis
... not the model
... not a short TR
S O C I A L S U P P O R T

18. ‚hm .... weird ............ but also encouraging, don‘t you think???‘ (Ben)
‚ok, Katja, don‘t worry! That only means that there must be a better model!!‘ (Klaas)