fMRI Journal Club September 28, 2004 Andy James and Jason Craggs Evaluation of mixed effects in event-related fMRI studies: Impact of first-level design and filtering M. Bianciardi, A. Cerasa, F. Patria, and G.E. Hagberg Neuroimage 22 (2004)

Problem: What is the best design and analysis approach for event-related fMRI (er-FMRI) studies? Designs Block Bimodal Geometric Latin square Bimodal Fixed Analysis SPM99 SPM2 FSL3.0 We are primarily interested in fixed effects (factors we control) and not random effects (factors varying by subject). We want results that are sensitive and specific.

What is an event related design? An fMRI experiment where stimuli are presented as individual discrete trials, which can vary both time and sequence of stimuli In contrast, block design experiments typically have groups or “blocks” of trials EventBlock

Binomial Hayberg 2001 Different event related fMRI designs

Fixed, Random, and Mixed Fixed effects: factors and levels that the experimenter is “arbitrarily and systematically” choosing to analyze Random effects: factors the experimenter is not attempting to control, but will use to test external validity Mixed effects: analyses that incorporate fixed and random effects

Random effects analysis In performing a standard GLM analysis, the resulting significant results are strictly speaking only valid for the group(s) of subjects or patients included in the analysis because subjects are treated as a fixed effect in a standard GLM. In order to generalize the obtained fMRI results to the population level, a random effects analysis has to be performed. This means that the studied sample of subjects are treated as a random selection from the population of all people. Note, that for generalization to the population level, many subjects should be included, i.e. 50 or more (per experimental group!). With a few subjects, it is simply impossible to estimate general population effects. The recommended minimum for random effects analysis are 10 subjects per experimental group.

Other Key concepts Sphericity –Is an extension of homogeniety of variance, but with a repeated measures twist That is, we expect the covariances between groups/regions/whatever to be roughly equal across multiple measurements

Sensitivity How well can the hardware detect an fMRI signal elicited from the paradigm

Precision How well can you specify the origin of the detected signal. –How much is it really related to the experimental manipulation

Anatomic ROI masks Red: M1 (Active) Green: S1 (not active) Used for 2nd level (random effects) analyses Also depict ROIs for comparing designs and programs

Sensitivity vs Specificity/Precision