The effect of category learning on visual attention and visual representation

Subordinate-level category learning recruits neural resources associated with perceptual expertise, including the N250 component of the ERP, a posterolateral negative wave maximal between 230 and 330 ms. The N250 is a relatively late visual ERP and could plausibly be driven by attention to the features of categorized objects. Indeed, it has a latency and scalp distribution similar to the selection negativity (SN), an ERP component long known to be sensitive to attentional selection of target features. To clarify sensitivity of the N250 to attention and to more generally investigate the effect of category learning on attentional modulation of learned features, we independently manipulated subordinate-level category learning and target detection in a speeded paradigm designed to optimally elicit the SN and accompanying frontal selection positivity (FSP). Participants first practiced categorizing a set of artificial animal stimuli and then performed a speeded target detection task on trained and untrained stimuli while ERPs were recorded. SN and FSP were roughly linearly related to the number of target features in the stimulus. Trained stimuli elicited a significantly larger N250 than untrained stimuli. The SN and N250 effects were additive, with all levels of target similarity equally affected by training, and had different time courses. Training had little effect on the FSP. The results suggest that (a) the N250 and SN have different sources, and (b) at the very least, the learning-induced N250 indexes a different attentional subprocess from the target-induced SN and could be driven by a different cognitive process altogether.