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fMRI Connectivity Models: GCM & DCM

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FMRI Connectivity Models: GCM & DCM
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FUNCTIONAL VS EFFECTIVE CONNECTIVIT Y


Func     l     c
    tiona Conne tivity          Effe tiveConne tivity
           ...

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PSYCHO-PH YSIOLOGICAL INTERACTION (PPI)

             Condition                                    Condition
             ...

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fMRI Connectivity Models: GCM & DCM

  1. 1. FMRI Connectivity Models: GCM & DCM 1
  2. 2. FUNCTIONAL VS EFFECTIVE CONNECTIVIT Y Func l c tiona Conne tivity Effe tiveConne tivity c c x x y y •Temporal correlation •Causal Flow 2 2
  3. 3. PSYCHO-PH YSIOLOGICAL INTERACTION (PPI) Condition Condition Condition Y values A B Y values A B Low 2 4 Low 2 2 High 3 5 High 4 7 6 8 7 5 6 4 5 3 A 4 A B B 3 2 2 1 1 0 0 Low High Low High Main Effect of Condition Main Effect of Condition 3 No Interaction Interaction
  4. 4. G RANG ER CAUSALIT Y M O D EL Time-series t-1 t t+1 t+2 X 1.18 0.20 -0.83 -0.31 Y 2.03 -0.02 0.19 -0.49 Z 0.84 0.08 -0.01 -0.39 Prediction of Xt X,Y < X,Y,Z (less errors) Z contains useful information  “Granger-causes” X Z Num. of lagged observations Coefficients of time Errors contribution 4
  5. 5. D YNAM IC CAUSALIT Y M O D EL DCM: deconvolution of BOLD signal Neural Response HRF BOLD Intrinsic time Connections Inputs to regions Regulation Modulatory •Driving Inputs Regulation connections •Modulatory Inputs 5
  6. 6. G CM VS D CM GCM DCM •BOLD signal •Deconvolved BOLD signal •“Data-driven” •“Hypothesis-driven” •mGCM can differentiate b/w direct and •Connections are predefined. No indirect connections differentiation b/w direct and indirect causal connections 6

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