Despite the fact that we did not find an effect of training on response criterion (F4,45 = 0.615, P = 0.655; Figure 2D), we did find a drop in c when comparing first and last training session (t9 = 3.832, P,0.005). Nevertheless, no changes were observed in false alarms (F4,45 = 0.794, P = 0.537; Figure S1) suggesting that the improvement in perceptual performance is most likely not related to extra-perceptual factors (e.g. decision-making or response strategy). Moreover, in contrast with sensitivity and RT, we did not find a clear trend among subjects for this index (Figure S1). Electrophysiological data: ERP waves Visual ERPs to search array presentation were obtained for each subject and condition (hit, correct-rejection, miss). Because perceptual learning without transfer to novel stimuli has traditionally been interpreted as involving changes in early visual areas [1,5,16], we initially studied the effect of training on early components of the visual evoked response during hits. P1 and N1 waves were therefore identified over occipital electrodes peaking between 75–135 and 80–180 ms after stimulus presentation respectively. However, we did not find significant effect of training either over P1 (F4,45 = 1.821, P = 0.141) or N1 (F4,45 = 1.118, P = 0.36) amplitude. Late ERP waves P3 and N2pc were processed in a slightly different fashion due to the high sensitivity they show to target presence: A P3b-like (from now on P3 for simplicity) component was identified by a rather distributed scalp topography, which appeared more clearly over central and parietal sites, showing no significant differences between target and no-target trials (supplementary Figure S2). We analyzed the absolute value of P3 amplitude throughout the perceptual learning process, and found a significant effect of training as measured over left (F4,45 = 123.42, P,0.001; Figure 3A), right (F4,45 = 39.631, P,0.001; Figure 3B) and central (F4,45 = 105.841, P,0.001; Figure 3C) posterior electrodes. Planned pair-wise comparisons revealed that this main effect could be described as a tendency of P3 amplitude to increase over the course of learning. More specifically, in left electrodes, the amplitude increment was significant between first-second (t9 = 26.74, P,0.001) and fourth-fifth (t9 = 213.185, P,0.001) training sessions. In right-hemisphere electrodes, significant differences were found between sessions second-third (t9 = 28.068, P,0.001), third-fourth (t9 = 24.893, P,0.001) and fourth-fifth (t9 = 24.519, P,0.01). Finally, in the case of central electrodes, significant differences were found between sessions first-second (t9 = 20.2638, P,0.05) and fourth-fifth (t9 = 210.392, P,0.001). In contrast to behavioral indexes, however, the increment in P3 amplitude was not specific for target orientation as revealed by the absence of significant differences between the last and control sessions, where target orientation had been modified (left: t9 = 20.321, P = 0.756; right: t9 = 0.369, P = 0.721; and central: t9 = 1.985, P = 0.078). The N2pc component has been widely involved in visual search tasks such as the one used in the present study, and has been targeted as a neurophysiological marker for selective processing of stimuli that are embedded in sets of distractors [29,30]. However, despite the fact that visual search tasks have been frequently used to explore visual perceptual learning [4,5,17–27], there have not been, to our knowledge, any reports analyzing the relationship between N2pc and this process. In order to isolate the N2pc component, we obtained the difference wave between ipsi and contralateral-to-target potentials (see Methods). We found a significant difference waveform in the 200 to 350 ms post-stimulus Neurophysiology of Human Perceptual Learning time-window, for all sessions in both left and right posterior electrodes (lower P value,0.05; supplementary Figure S3). There was a clear effect of training on N2pc amplitude spanning left (F4,45 = 107.629, P,0.001; Figure 4A) and right hemisphere (F4,45 = 68.98, P,0.001; Figure 4C) electrodes. Planned pair-wise comparisons showed a progressive amplitude increment of this component. In the case of the left hemisphere, significant differences were found between first-second (t9 = 22.72, P,0.05), second-third (t9 = 24.427, P,0.005), third-fourth (t9 = 25.995, P,0.001), but not fourth-fifth (t9 = 0.92, P = 0.381) training sessions, while for right sites the significant differences were found between second-third (t9 = 28.319, P,0.001), third- fourth (t9 = 26.085, P,0.001), but not for first-second (t9 = 20.667, P = 0.522), nor forth-fifth (t9 = 20.452, P = 0.662) sessions. Importantly, N2pc amplitude increase was found to be highly specific for the trained target orientation as evidenced by the significant drop in amplitude during the control session (t9 = 16.036, P,0.001; t9 = 9.45, P,0.001, for left and right sites respectively). Electrophysiological data: Time-frequency analysis TF-representations were obtained trial-by-trial for each condi- tion, normalized by subject and then averaged across epochs to construct theta (4–6 Hz), alpha (8–14 Hz), beta (20–30 Hz) and gamma (30–60 Hz) profiles of band-limited power variations. From a subject-level statistics point of view, there were significant changes in power relative to baseline activity in the alpha and gamma, but not in the theta or beta frequency bands for all subjects and training sessions in all the regions of interest (ROIs, See Methods). Accordingly, in the following we limit our analysis to the former frequency ranges only. At the group-level, we found a significant effect of training on amplitude of gamma band activity (GBA, Figure 5) over posterior left (F4,45 = 515.851, P,0.01), central (F4,45 = 248.533, P,0.01) and right (F4,45 = 612.081, P,0.01) electrodes. Planned pair-wise comparisons showed a significant amplitude increment between first-second and second-third training sessions, and a significant drop between third-fourth and fourth-fifth sessions over all analyzed regions (all P,0.01), revealing a complex bell-shaped amplitude profile of GBA throughout the learning process. We did not find significant GBA amplitude differences between the last and control sessions for any of the ROIs (lowest P value .0,08). The second main group-level result concerning oscillatory brain activity was the significant effect of training on the amplitude of alpha band activity (ABA; Figure 6) over posterior left (F4,45 = 40174.531, P,0.01), central (F4,45 = 60133.456, P,0.01) and right (F4,45 = 38796.946, P,0.01) electrodes. Planned pair- wise comparisons showed a significant amplitude decrement between first-second (P,0.005) and second-third (P,0.01) train- ing sessions, and a significant increment between third-fourth (P,0.01) and fourth-fifth (P,0.001) sessions in all the analyzed regions (P,0.05). Compared to the case of GBA, ABA also showed a complex amplitude modulation pattern along training, although this time as a mirror U-shaped profile. We did not observe significant amplitude differences between the last and control sessions for none of the assessed ROIs for ABA either. Interestingly, we found a strong inverse correlation (e.g. ROI-2: R = 20.993, P,0.001) between GBA and ABA amplitudes (supplementary Figure S4). Relationship between neural activity reorganizations and perceptual learning In order to analyze the level of dependency between perceptual learning and observed changes in brain activity, we calculated the PLoS ONE | www.plosone.org 5 April 2011 | Volume 6 | Issue 4 | e19221