Each trial began with an ocular fixation cross at the center of the monitor that appeared 300 ms before the beginning of the sentence and disappeared 800 ms after the response. The inter- stimulus interval was set at 150 ms. Sentences were recorded by a female native Spanish speaker. Auditory stimuli were recorded and set using Audacity 1.2.6 software. Experimental presentation and data collection were performed with Python software. The 156 trials were uniformly distributed over the three conditions of sentences in a counterbalanced list, ensuring that the same condition was not appearing more than twice consecutively (see Table 2). ERP Data Acquisition and Processing Electroencephalographic (EEG) data were acquired with a 128 channel Electrical Geodesics Inc. (EGI) system, GES300, consist- ing of Hydrocel Geodesic Sensor Net, Net Amps and Net Station software (Electrical Geodesics Inc.). EEG data were sampled at 500 Hz and 0.1–100 Hz analog filtered. Impedances were kept under 50 kV. EEG data were continuously recorded by default to vertex and offline re-referenced to linked mastoids (motor responses) and average electrodes (N400-like component). A band pass digital filter between 0.5 and 30 Hz was applied to remove unwanted frequency components. EEG data were segmented offline into 1 s epochs spanning from 200 ms pre-stimulus to 800 ms post-stimulus for stimulus-locked segments and 1500 ms epochs from 2500 ms to 1000 ms for hand response-locked segments. EEG channels with visually detectable artifacts (e.g., eye blink, channel drift and gross movement) were isolated using the Net Station Waveform Tools (NSWT) and discarded from the analysis. In addition, automatic ICA and adaptive autoregressive modeling was performed to discard further artifacts. Data analysis Reaction times (RTs) were calculated for each subject in each condition (compatible, incompatible and neutral). Outliers with RTs outside +2.5 SD were deleted. For ERPs, a strategy for channel location reported previously was used (e.g., [71–72]). A time-course analysis for 9 representative electrodes (11(Fz), 24(F3), 36(C3), 52(P3), 62(Pz), 92(P4), 104(C4), 124(F4) and 129(Cz)) in the compatible, incompatible and neutral condition for OHG and CHG was implemented. After an electrode6category analysis of all ERPs (see Methods S2), the vertex site was selected based on bigger amplitudes and differences between categories. The Cz region has been reported previously as the main site for N400 [73] and motor responses [66]. Although ERP figures show single electrodes, a region of interest (ROI) of those 6 electrodes around the maxima of MRCP and N400-like (vertex) effects were chosen to analyze the ERPs. This analysis is consistent with previous reports for maxima location of motor responses [66] and the N400-like component [74]. ERP figures shows those selected channel locations. ERPs were analyzed by considering mean amplitude values. The MRCP consisted of two Table 2. Conditions of the experiment. OHS CHS NS OHG CHG Compatible condition Incompatible condition Neutral condition Incompatible condition Compatible condition Neutral condition Interaction of the type of response (OHG or CHG) and content of the sentences (OHS, CHS, NS) in three categories (compatible, incompatible and neutral). doi:10.1371/journal.pone.0011751.t002 Neural Signatures of ACE components (similar to those reported in [66]), an MP peaking between 290 and 50 ms immediately following the onset of the movement followed by a clear positive deflection, resembling the RAP, peaking from 200 to 300 ms after movement onset was considered. Both MRCPs were triggered by the zero time response automatically detected by the computer when the button was activated. The N400-like component was analyzed 350–650 ms after stimulus onset (final target word). Because of the observed early differences at 0–150 ms and 150–300 ms windows, we performed a preliminary analysis over those windows. Those comparisons yielded no statistical effect. Consequently, we did not include them in this report. By including the N400 and the MRCPs triggered by semantic stimuli and motor response respectively, we were able to measure the possible bidirectional effects on action and language processing. Statistical analysis Repeated measures of Analysis of Variance (ANOVA), with group as the between-subject factor (OHG and CHG) and category as the within-subject factor (compatible, incompatible and neutral), were performed for behavioral and ERP measures. For example, CHS in the OHG and OHS in the CHG were considered incompatible categories (see Table 2). An additional factor, stimulus content (NS, OHS and CHS), was introduced when necessary. Matlab software was used for offline processing and analysis of ERP data. ANOVA degrees of freedom were corrected using the Greenhouse-Geisser method to adjust the unvaried output of the repeated measures ANOVA for violations of the compound symmetry assumption. When the covariances are not equal and all the variances are not equal, this method adjusts the degrees of freedom in the ANOVA test in order to produce a more accurate significance (p) value. Tukey’s HSD method was used for the calculation of post-hoc contrasts. Results Behavioral measures Content effects. Regardless of ACE, an effect of stimulus content was significant (F(2, 48) = 8.07; p,0.001). Post hoc comparisons (MS = 776.34; df = 48.00) showed that NS elicited a shorter response (M = 611 ms, SD = 50) compared with OHS (M = 920 ms, SD = 70; p,0.001) and CHS (M = 793, SD = 60; trend: p = 0.58). No differences between OHS and CHS were obtained (p = 0.23). A group effect elicited a trend (F (1, 24) = 3.48, p = 0.07), suggesting a faster processing of the CHG (M = 698 ms, SD = 58) compared to OHG (M = 852 ms, SD = 58). ACE. A strong ACE of category was found (F (2, 48) = 8.07, p,0.001). The incompatible category presented longer RTs (M = 1034 ms, SD = 102) compared with the compatible (M = 679 ms, SD = 92) and neutral categories (M = 611 ms, SD = 70). Regarding groups results (Figure 2), a group6category interaction was significant (F (2, 48) = 10.57, p,0.001). Both groups seemed to elicit an ACE, although this was more accentuated in the CHG. Post hoc comparisons performed over this last interaction (MS = 96.21, df = 67.00), showed that in the CHG, incompatible responses (M = 1015 ms, SD = 99) elicited longer RTs compared with compatible (M = 533 ms, SD = 85; p,0.001) and neutral stimuli (M = 545 ms, SD = 70; p,0.005). No differences between compatible and neutral stimuli were observed (p = 0.99). In the OHG, responses from compatible stimuli (M = 826 ms, SD = 99) were shorter than responses from incompatible stimuli (M = 1053 ms, SD = 85; p,0.05). Neutral stimuli (M = 677 ms; SD = 70) elicited shorter responses than incompatible ones (p,0.05). PLoS ONE | www.plosone.org 5 July 2010 | Volume 5 | Issue 7 | e11751