Neurophysiology of Human Perceptual Learning Figure 4. Effect of training over mean N2pc amplitude. A) Grand average ERPs contralateral-to-target and difference -waves (contra minus ipsilateral) obtained from sessions 1, 3 and 5 and from electrode: A) LO2 left occipital; B) Average topographic distribution of scalp potential peakin the N2pc time window for the corresponding sessions and for targets appearing at the right side of the array; C) RO2, right occipital; D) Same as in B but for targets appearing at the left side of the array. doi:10.1371/journal.pone.0019221.g004 [39,40] and recent models of guided search comprising not only selective, but also non-selective pathways for target identification depending on its context [41]. The present results show for the first time that sustained practice in a visual search task leads to amplitude increments in the N2pc wave that are strongly correlated with psychophysical performance and highly specific for trained stimulus orientation. N2pc is involved in selective processing of targets embedded in complex visual arrays [29,30]. Accordingly, training-dependent amplitude increments of this component could represent a neurophysiolog- ical correlate of an improvement in this capability. The specificity level exhibited by this activity modification, however, argues against a purely attentional-related effect and suggests that performance improvements should be at least partially dependent upon visual cortices capable of responding to specific stimuli features (e.g. orientation, shape). Changes in N2pc amplitude could therefore be the result of the dynamical interaction between sensory cortices and upstream attentional networks, accounting both for specificity and for classical N2pc results in visual search tasks. Indeed, Ahissar and Hochstein [4,5] have proposed a mechanism for such interaction in which attention constrains the stimuli attributes upon which learning takes place. Furthermore, to account for performance improvements outside the focus of attention [42], the original model was extended by proposing that perceptual learning occurs thanks to the coincidence of diffusive reinforcement signals related to task execution (also in agreement with our P3 results) and signals induced by target presentation [43]. In this context, attention would work as a gate mechanism, selecting which aspects of the task will be learned with a lower or higher degree of generalization [37]. Our ERP results fit well in the framework provided by Ahissar and Hochstein’s model, but suggest several relevant lines of development. We propose that unspecific, context-related effects of practice can be seen through a P3 amplitude increment, while both unspecific and specific attention-related effects are associated with changes in the N2pc profile. Indeed, Hopf and collaborators have shown that the N2pc component has its origins in both parietal and occipito-temporal cortices [44]. This would be compatible with an interaction between fronto-parietal attentional networks [45] and sensory cortices resulting in attentional re-weighting that encompasses an increase in the amount of attention paid to perceptual dimensions and important features, and/or a withdrawal of attention from irrelevant aspects of the stimulus [46]. In addition to behavioral and ERP results, we found novel evidence of the effects of sustained training on posterior oscillatory brain activity for both gamma and alpha frequency bands. Interestingly, their temporal profiles were not monotonic but showed complex amplitude patterns better described as bell- and U-shaped respectively. Previous investigations regarding human perceptual learning and GBA have found a decrease in the case of priming [47], and an increase in the case of associative [48] and rapid perceptual learning [49]. However, these studies compared GBA either pre- vs post-training or trained vs non-trained, without assessing the entire course of learning acquisition. Moreover, such studies did not focus on perceptual learning as the result of extensive practice in a sensory task. Figure 5. Effect of training on mean GBA amplitude over ROI-2 or right hemisphere sites. The left side of the figure depicts TF charts obtained for each of the five training sessions. The right side of the figure depicts, from top to bottom, the TF chart obtained for the control session, head plot showing the approximate position of electrodes identified for ROI-2 and quantification of the amplitude profile along training (1-5) and during control (6) session. doi:10.1371/journal.pone.0019221.g005 PLoS ONE | www.plosone.org 9 April 2011 | Volume 6 | Issue 4 | e19221