Two-Stage Processing of Sounds during Attention Figure 3. Mean dipole coordinates. Mean (+SEM) dipole coordinates for M100 and sustained responses in both conditions in MEG head coordinate system (N = 14). (A) Coordinates in XY plane. (B) Coordinates in XZ plane. doi:10.1371/journal.pone.0046872.g003 test) in the left hemisphere, which is consistent with earlier findings [24]. There were no statistically significant differences in locations between conditions (AttAud vs. AttVis) in either M100 or sustained response locations. Cortically constrained MNE data analysis for auditory cortex In order to better localize the auditory cortex activity, we explored the MEG data using a cortically constrained MNE [25,26] analysis for the subset of (N = 10) subjects with MRIs. To get an initial assessment of the activity, the whole auditory cortex region of interest (ROI), extending over temporal areas (superior temporal sulcus, including Heschl’s gyrus), was selected and the mean amplitude of vertices was taken as the measure. The results from this analysis were in line with the ECD analysis. When auditory cortex area was divided to roughly equal regions (Fig. 6), the obtained MNE data showed main effects of MASKERTYPE (F6,54~17:29, pv0:0001, e~0:37), ATTENTION (F1,9~9:56, p~0:013) and GRIDPOINT (F14,126~9:21, pv0:0001,e~0:35), with no hemispheric main effect. Importantly, the hemispheric and spatial dependency of the attention effect was evident as both significant ATTENTION|HEMISPHERE interaction (F1,9~13:43, p~0:0052) and ATTENTION|GRIDPOINT interaction term (F14,126~5:21, p~0:00063, e~0:37). Varying frequency tuning at different grid points, which can be seen as variability of curves in Figure 6, resulted a significant MASKER- TYPE|GRIDPOINT interaction (F84,756~7:16, pv0:0001, e~0:23). Sustained response grid analysis (Fig. 7) using MNE did not show spatial changes due to attention, but revealed a hemispheric effect (F1,9~11:46, p~0:0081). Similar to dipole modeling results, the main effect of attention was significant (F1,9~12:55, p~0:0063) and dependent on masker type (MASKERTY- PE|ATTENTION F6,54~2:54, p~0:031, e~1:00). Behavioral results We used sensitivity index d’ [27] to characterize behavioral performance. This index takes into account false alarms in order to reduce possible response bias and is defined as difference of z- transformed hit rate and false alarm rate, z(H){z(FA). Basically a higher d’ value tells that the subjects perform better in the given task, or the signal is more easily detected. Behavioral data showed significant main effects of MASKER- TYPE (F6,78~22:85, pv0:0001, e~0:71; F6,78~14:46, pv0:0001, e~1:00) and ATTENTION (F1,13~8:14, p~0:014; F1,13~189:01, pv0:0001) on performance measure d’ and reaction time (RT), respectively, accompanied with highly significant MASKERTYPE|ATTENTION interaction (F6,78~37:06, pv0:0001, e~0:17; F6,78~22:83, pv0:0001, e~0:64). The significant interaction term stems from differential effects of masker type on performance depending on the focus of attention, as can be seen in Figure 8. Basically for the auditory task (AttAud), d’ and RT change as a monotonic function of notch width, whereas for visual task (AttVis), d’ and RT are more uniform with different noise masker types. With no masker, there was no effect of attention on d’, but subjects responded faster PLOS ONE | www.plosone.org 4 October 2012 | Volume 7 | Issue 10 | e46872