The locations of these artifacts can be estimated in each subject and they are summarized MLN8237 order in Figure S4. These artifacts limit our ability to measure a portion of the VWFA in some subjects. The main experiment consisted of separate sessions (on separate days) for each feature type (line contours, motion-dot, luminance-dot, and mixture). Each subject completed six runs (312 s per run) for each feature type. The order of feature types was counterbalanced across subjects. Subjects were asked to keep fixation on a central fixation dot while reading the stimuli and to indicate by button press whether each stimulus was a word or

pseudoword (i.e., lexical decision task). Eye movements were monitored (see above). We measured the BOLD response to words and pseudowords at four different visibility levels for each feature type. In analyzing the data, we grouped words and pseudowords together because they showed similar responses in all regions of interest that we examined. All stimuli used for the main experimental runs were four-letter words or pseudowords (Medler and Binder, 2005). Words were nouns with a frequency of at least four per million (median: 28 per million). All words (n = 480) and pseudowords (n = 480) were unique within each subject, with five words and five pseudowords (× 4 visibility SKI-606 purchase levels × 6 runs/feature × 4 feature types) being assigned randomly to each of four visibility levels within each run (40 stimuli per run). All stimuli

were shown for 2 s. Stimulus presentation and response collection, both for fMRI and TMS (see below), were created using custom Matlab (The MathWorks, Inc.) scripts and controlled using the Psychtoolbox (Brainard, 1997). The stimuli were created as follows: The procedure used for rendering standard words at different visibility not levels was similar to that used by Ben-Shachar and colleagues (2007b). We rendered words in black using the Monospaced (Sans Serif) font within a gray rectangular frame (24 degrees horizontal, 7 degrees vertical). The horizontal and

vertical spans of the word within the frame were approximately 7.5 and 2.5 degrees, respectively (height of an x character was approximately 2°). To obtain different degrees of visibility, we computed the 2D Fourier transform of the word image, randomized the phase, and then applied the inverse Fourier transform. Visibility could be controlled by the degree of offset between the old and new phase. Resulting images ranged from noise (fully phase-scrambled) that contained the same amplitude spectrum as the original images, to highly visible words. To create words defined by dots of spatially varying luminance, we replaced the word image with a field of dots (dot density = 0.3; dot size = 1 pixel, total image size = 600 × 180 pixels), keeping the background color a uniform gray. The luminance of the dots was set separately for dots that fall inside (black) or outside (white) the nominal borders of the word form.