acquisition. This would mean that while GBA is reflecting the degree in which cells are spiking in a more packed way (thus forming neural ensembles), ABA may be indicative of a similar, but sparser organization of neural activity in time. There is probably more than one mechanism [52,53] by which different brain networks [27,33] reorganize their activity in order to produce the characteristic psychophysical improvements of percep- tual learning. The present results suggest that neural reorganization due to perceptual learning is a multi-layered phenomenon involving different mechanisms at different stages of acquisition. Figure 8 depicts a simplified model that aims at integrating previous accounts of perceptual learning and the present results. In our model, both specific and unspecific learning take place along the entire course of training. The unspecific aspects are reflected in P3 amplitude, and comprise the development of a cognitive configuration relative to the task and its context, enhancing performance by facilitating non- selective context updating processes [36,37,41]. Specific processes are reflected in the N2pc amplitude, favoring detection and identification of the trained target by means of a differential weighting and re-weighting mechanism [46]. This would take place at a mid-level stage of perceptual processing [52] where an interaction between attentional neural networks and sensory cortices can facilitate the selective treatment of the target among distractors. Finally, oscillatory brain activity over posterior sites would reflect underlying changes at an early-local network stage [61]. This would enhance performance by augmenting the number and/or strength of connections in a given cell ensemble during a first phase and by selecting only the most strong and selective neurons during the second one. Importantly, and in agreement with our results, previous fMRI reports [52,53] also show that the second phase starts around the same time that perceptual improvement becomes asymptotic. Although the proposed orchestration of neurophysiological processes is still probably an incomplete scheme of experience-dependent changes in brain activity, we expect that highlighting the dynamical modifications that take place during training will suggest and open possible directions for future research. Supporting Information Figure S1 Single subject psychophysical profiles along training. A) Hit rate, B) False alarm rate, C) Sensitivity or d’ D) Response criterion or c. (TIF) References 1. Gibson E (1963) Perceptual learning. Ann Rev Psychol 14: 29–56. 2. Skrandies W, Jedynak A, Fahle M (2001) Perceptual learning: psychophysical thresholds and electrical brain topography. Int J Psychophysiol 41: 119–129. 3. Song Y, Ding Y, Fan S, Qu Z, Xu L, et al. 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