Two-Stage Processing of Sounds during Attention Figure 5. Sustained response amplitudes. Mean evoked activity (+SEM) from (A) 200–300 ms, (B) 300–400 ms, (C) 400–500 ms, and (D) 500– 600 ms time range after the sound onset. We selected (B) as the representative time range for the later analysis (see Materials and Methods). Attentional modulation is strongest in (A)–(C) with some of the narrowest notches (+50–200 Hz maskers), suggesting increase in feature specificity within the classical critical band of approximately 160 Hz at 1,000 Hz. Significant changes between AttAud and AttVis are indicated by asterisks (* pv0:05, ** pv0:01, *** pv0:001). doi:10.1371/journal.pone.0046872.g005 correlations in AttAud task with left middle temporal gyrus (MTG) and right insula. For AttVis data, high correlations with d’ were widespread in posterior frontal and parietal lobes, but no consistent regions were evident for RT. These d’ correlations, however, seem to be driven by a number of outliers with high RT and ROI value (see scatterplots in Fig. 9), so they were most probably caused by some subjects who took abnormally long time to answer in the task, showing strong motor cortex activations especially in vicinity of hand and finger area [29]. Nonetheless, in this respect our data were limited in localization accuracy because of unsuited experimental paradigm for motor cortex mapping. Time course of frequency tuning and attention effect With advances in signal processing and MEG shielding technology, reliable averaged MEG responses can be obtained with a significantly smaller number of epochs than the 100–150 typically used for auditory-evoked M100 (see [30]). Here, this advantage was utilized by selectively offline-averaging subsets of data, with the aim of possibly showing refined time course of the attention effect. The data were averaged to 1) first and second presentation of interleaved attention conditions, and 2) seven 30- second segments (with 15-second overlap) of which only non- overlapping segments (0–0:30, 0:30–1:00, …) were used in statistical analysis. For M100 response, segment analysis of dipole modeling (ECD) data showed a significant MASKERTYPE|SEGMENT interac- PLOS ONE | www.plosone.org 6 October 2012 | Volume 7 | Issue 10 | e46872