Dear Experts and dear Rik,
Henson (2006) explains Forward Infrence or Reverse Association also called
Function-to-Structure Deduction (Henson, 2005).
[r1, r2 = regions; c1 and c2 = conditions of interest which are different
for one function; c0 = condition of control]
Very briefy there are three criteria for Forward Inference: 1) interaction
R(r1, r2) × C(c1, c2) suggesting a dissociation between r1 ed r2; 2)
positive correlation between r1 and r2 for the contrast c2 and/or c1
compared with c0 suggesting an assocition betwee r1 and r2; 3) negative
correlation between r1 and r2 for the contrast c2 compared with c1.
My questions are:
Are the calculations related to the three criteria done on the % signal
change for c0, c1 and c2?
Is it correct to extract % signal change for c0, c1 e c2 from the same t-map
comparing c2-c1?
Can I use a condition of rest (look a cross) explicitly modeled as c0 or
Forward Inference is invalidated?
Can I derive a Forward Inference when the three criteria are satisfied but
some or all % signal changes for c0, c1, c2 are negative?
Thank you for your clarifications.
Federico.
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