The…. U. M. D. S’. GUIDE to. M. I. E. DCM. Velia Cardin. Functional Specialization is a question of Where ?. Where in the brain is a certain cognitive/perceptual attribute processed? What are the Regionally specific effects. your normal SPM analysis (GLM).
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How does the system work?
What are the inter-regional effects?
How do the components of the system interact with each other?
Experimentally designed input
The aim of DCM is to estimate parameters at the neuronal level so that the modelled BOLD signals are most similar to the experimentally measured BOLD signals.
Statistical test on parameters of optimal model
Definition of DCMs as systemmodels
Bayesian modelselection of optimal DCM
Design a study thatallows to investigatethat system
Parameter estimationfor all DCMs considered
Extraction of time seriesfrom SPMs
attention modulates V5 directly
When attending to motion…….
Attention modulates effective connectivity between PPC to V5
DCM cannot distinguish between direct and indirect!
Hypotheses of this nature cannot be tested
In case of
Stimuli 250 radially moving dots at 4.7 degrees/s
5 x 30s trials with 5 speed changes (reducing to 1%)
Task - detect change in radial velocity
Scanning(no speed changes)
6 normal subjects, 4 x 100 scan sessions;
each session comprising 10 scans of 4 different conditions
F A F N F A F N S .................
F - fixation point only
A - motion stimuli with attention (detect changes)
N - motion stimuli without attention
S - no motion
Attention – No attention
Büchel & Friston 1997, Cereb. Cortex
Büchel et al.1998, Brain
NB: in order!
Latent (intrinsic) connectivity (A)
Modulation of connections (B)
A simple DCM of the visual system
Re-analysis of data fromFriston et al., NeuroImage 2003
Comparison of three simple models
Model 1:attentional modulationof V1→V5
Model 2:attentional modulationof SPC→V5
Model 3:attentional modulationof V1→V5 and SPC→V5
Bayesian model selection: Model 1 better than model 2,
model 1 and model 3 equal
→ Decision for model 1: in this experiment, attention primarily modulates V1→V5
Bayes Information Criterion (BIC) and Akaike’s Information Criterion (AIC)
BIC is biased towards simple models
AIC is biased towards complex ones
Make a decision if both factors are in agreement, in particular if
Both provide factors of at least e (2.7183)
Penny et al. 2004, NeuroImage
The read-out in MatLab indicates which model is most likely
Thanks to Klaas, Ollie and Barrie