The effect of category learning on attentional modulation of visual cortex

Search flavor labels in beverages: An electrophysiological investigation of color-flavor congruency and association strength in visual search

Individuals are apt to link various characteristics of an object or event through different sensory experiences. We conducted two electrophysiological experiments to investigate the effects of color-flavor congruency and association strength on visual search efficiency and the in-depth cognitive mechanisms underlying multisensory processes. Participants were prompted with a flavor label and asked to identify the primed flavor from four beverage bottle images. Experiment 1 focused on color-flavor congruency and noted faster searches for congruent targets than incongruent ones. EEG data exhibited smaller N2, larger P3 and LPC, and increased parietal-occipital midline (POM) alpha power for incongruent targets than congruent ones. Experiment 2 manipulated color-flavor association strength within each flavor. Behavioral findings showed that searches for targets with weak association strength took longer than those with strong association strength. Moreover, time-frequency analysis displayed that the former evoked greater frontal midline (FM) theta power and higher alpha power than the latter. Altogether, our research indicated that (1) color expectations based on prior experience can automatically guide people's attentional selection, (2) the color-flavor congruency and association strength impact the visual search efficiency via distinct pathways, and (3) theta and alpha activities make a pivotal role in unraveling multisensory information processing. These findings shed some light on the intricate cognitive processes involved in crossmodal visual search and the underlying neurocognitive dynamics.

Category learning can alter perception and its neural correlates

Learned Categorical Perception (CP) occurs when the members of different categories come to look more dissimilar ("between-category separation") and/or members of the same category come to look more similar ("within-category compression") after a new category has been learned. To measure learned CP and its physiological correlates we compared dissimilarity judgments and Event Related Potentials (ERPs) before and after learning to sort multi-featured visual textures into two categories by trial and error with corrective feedback. With the same number of training trials and feedback, about half the subjects succeeded in learning the categories ("Learners": criterion 80% accuracy) and the rest did not ("Non-Learners"). At both lower and higher levels of difficulty, successful Learners showed significant between-category separation-and, to a lesser extent, within-category compression-in pairwise dissimilarity judgments after learning, compared to before; their late parietal ERP positivity (LPC, usually interpreted as decisional) also increased and their occipital N1 amplitude (usually interpreted as perceptual) decreased. LPC amplitude increased with response accuracy and N1 amplitude decreased with between-category separation for the Learners. Non-Learners showed no significant changes in dissimilarity judgments, LPC or N1, within or between categories. This is behavioral and physiological evidence that category learning can alter perception. We sketch a neural net model predictive of this effect.

Extended categorization of conjunction object stimuli decreases the latency of attentional feature selection and recruits orthography-linked ERPs

The role of attention in driving perceptual expertise effects is controversial. The current study addressed the effect of training on ERP components related to and independent of attentional feature selection. Participants learned to categorize cartoon animals over six training sessions (8,800 trials) after which ERPs were recorded during a target detection task performed on trained and untrained stimulus sets. The onset of the selection negativity, an ERP component indexing attentional modulation, was about 60 msec earlier for trained than untrained stimuli. Trained stimuli also elicited centro-parietal N200 and N320 components that were insensitive to attentional feature selection. The scalp distribution and timecourse of these components were better matched by studies of orthography than object expertise. Source localization using eLORETA suggested that the strongest neural sources of the selection negativity were in right ventral temporal cortex whereas the strongest sources of the N200/N320 components were in left ventral temporal cortex, again consistent with the hypothesis that training recruited orthography related areas. Overall, training altered neural processes related to attentional selection, but also affected neural processes that were independent of feature selection.