5 to 11.7 s (timing and stimuli presentation were consistent with previous visual world studies using fMRI; e.g., Righi et al., 2010). See Fig. 1 for a sample trial structure. At the conclusion of the experiment, participants provided names for all competitor and unrelated pictures. Trials in which participants provided this website an alternate name that changed condition assignment (e.g., naming the candle from the candy-candle trial a “flame”) were

removed from analysis (7.4% of trials). Functional neuroimaging data were collected at Baylor College of Medicine’s Human Neuroimaging Laboratory using a 3.0 Tesla head-only Siemens Magnetom Allegra magnetic imager. Anatomical images were acquired using high-resolution T1-weighted anatomical scans with an MPRAGE sequence at a voxel size of 1.0 × 1.0 × 1.0 mm, TR = 1200 ms, TE = 2.93 ms, reconstructed into 192 slices. Functional images were acquired in 34 axial slices parallel to the AC-PC line with an interleaved descending gradient recalled echo-planar (EPI) imaging sequence with a voxel size of 3.4 × 3.4 × 4.0 m, TR = 2700 ms, and TE = 28 ms. Three dependent measures were collected in the current

study: accuracy, response time, and the blood-oxygen-level dependent (BOLD) PFT�� clinical trial response as indexed by fMRI. The dependent variables and the analysis techniques used to evaluate them are described below. For all analyses, trials in which no response was made (1.4% of trials) or in which participants provided an incorrect name for a critical item during post-experimental testing (7.4% of all trials) were removed. Accuracy and response time in the fMRI

task were determined by button-box responses. Trials were considered accurate if the button pressed corresponded to the quadrant in which the target Paclitaxel in vivo was located. Response time was measured from the onset of the search display to the point of the button-press response. Accuracy and response time scores were compared between language groups and across trial types using linear mixed effect (LME) regression models. The LME models included subject and item as random effects, and group (monolingual, bilingual), condition (competitor, unrelated), and item order (to control for potential order effects, as target items appeared on both competitor and unrelated trials) as fixed effects. Functional images for each subject were analyzed using SPM8 software (Wellcome Trust Centre for Neuroimaging, London, UK). During preprocessing, images were realigned for motion correction, resliced, and slice time corrected. The functional images were coregistered to align the mean functional image with the structural image, segmented, and normalized to a standard MNI (Montreal Neurological Institute) template. Functional data were spatially smoothed using an 8 mm full-width half maximum (FWHM) Gaussian kernal to compensate for any additional variability after normalization.