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Summary: SEM Analysis of fMRI Data Donna Rose Addis (adapted from Randy McIntosh) 1
FUNCTIONAL VS. EFFECTIVE CONNECTIVITY
Functional connectivity:
· "temporal" correlation or covariance among measured neural elements
· requires no assumptions about mediation of influences
Effective connectivity:
· influence (effect) that one neural element has on another
· requires some assumptions about mediation of influences
Measures of functional connectivity cannot distinguish between the two networks above,
effective connectivity can.
SOURCES OF VARIANCE
Across-task (within subject or averaged over subjects)
· Variance is introduced through the performance of several tasks. The simplest example
would be the repetition of the same task several times. The variance would be due to the
repetition of the task.
· In fMRI, this would be repetition of a type of event or block. You then compute subject-
specific measures of functional or effective connectivity. The interpretation of the numbers
indicates the degree to which areas within that subject are functionally linked, and may have
a direct physiological translation.
· The difficulty with this source of variance is the generalizability of the subject's measures to
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