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An aspect of the results portrayed in Figure 2 that may appear puzzling at first is that the observed response to the stimuli was generally a deactivation compared to baseline, for both words and nonwords.
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Figure 3, parts B and C show comparisons of left-hemispheric activation patterns elicited by different selections of emotion words against a hash mark baseline: for all emotion words (B) and the group of abstract emotion words only (C).
We found old/new effects for both words and pseudowords.
Error rates were also less than 2% for both words and pictures.
During naming, however, visual input must be linked to speech production for both words and pictures.
That way you score points for both words.
If you can cover a double or triple word bonus square in a way that makes two different words, you would get the bonus (double or triple word) for both words, not just the word that you have made directly.
Contrast images of interest were also produced (letter vs. baseline for the word generation task; bisection vs. control for the landmark task, and faces vs. objects for the faces task), and imported into a 2nd-level or random-effects analysis to obtain group results for each of the tasks.
Valence had a strong positive correlation with dominance (r =.64) for both word groups.
Vocal responses for both word reading and picture naming were recorded during fMRI scanning.
While control subjects showed an amplitude decrease for both word types in the repeat condition, this decrease was only present for LF words in dyslexics.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com