Filtered fMRI signal at the most significant voxel and average priming scores for brain-damaged patients, in a study addressing the extent to which phonological and semantic processes recruit the same brain areas.
A data frame with 35 observations on the following 3 variables.
a factor with levels
irregulars (the morphological condition involving priming using
inflected forms of irregular English verbs, e.g., 'began'-'begin')
semantics (priming with semantically related words such
as 'card' and 'paper').
a numeric vector for the average priming scores.
a numeric vector for the intensity of the filtered fMRI signal at the most significant voxel.
Location of data points reconstructed from the pixel map of Figure 2b of Tyler et al. 2005.
Tyler, L.K., Marslen-Wilson, W.D. and Stamatakis, E.A. (2005) Differentiating lexical form, meaning, and structure in the neural language system, PNAS, 102, 8375-8380.
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## Not run: data(imaging) imaging.lm = lm(FilteredSignal~BehavioralScore*Condition, data=imaging) summary(imaging.lm) plot(imaging$BehavioralScore, imaging$FilteredSignal, type = "n", xlim = c(-30, 40), ylim = c(0, 80)) semantics = imaging[imaging$Condition == "semantics",] irregulars = imaging[imaging$Condition == "irregulars",] points(semantics$BehavioralScore, semantics$FilteredSignal, col = "black") points(irregulars$BehavioralScore, irregulars$FilteredSignal, col = "darkgrey") abline(lm(FilteredSignal ~ BehavioralScore, data = semantics), col = 'black') abline(lm(FilteredSignal ~ BehavioralScore, data = irregulars), col = 'darkgrey') # model criticism plot(imaging.lm) outliers = c(1, 19) # given Cook's distance, or perhaps only outliers = 1 # the outlier in the semantics subset imaging.lm = lm(FilteredSignal ~ BehavioralScore * Condition, data = imaging[-outliers, ]) summary(imaging.lm) ## End(Not run)
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