August 2016
Volume 16, Issue 12
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2016
The effect of category learning on attentional feature selection: Selection negativity and N250 likely reflect different processes
Author Affiliations
  • Jonathan Folstein
    Psychology Department, Florida State University
  • Shamsi Monfared
    Psychology Department, Florida State University
  • Trevor Maravel
    Psychology Department, Florida State University
Journal of Vision September 2016, Vol.16, 258. doi:
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      Jonathan Folstein, Shamsi Monfared, Trevor Maravel; The effect of category learning on attentional feature selection: Selection negativity and N250 likely reflect different processes. Journal of Vision 2016;16(12):258. doi:

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      © ARVO (1962-2015); The Authors (2016-present)

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Subordinate level category learning recruits neural resources associated with perceptual expertise, including the N250 component of the ERP, a postero-lateral negative wave maximal between 230 and 330 milliseconds. 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 selection positivity (SP). Participants first practiced categorizing a set of artificial animal stimuli over two training sessions and then performed a speeded target detection task on trained and untrained stimuli while ERPs were recorded. Targets appeared on 20% of the trials and each non-target stimulus shared between 0 and 4 features with the target. The paradigm elicited a robust posterior SN and anterior SP with amplitudes strongly related to the number of target features contained 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 slightly different scalp distributions. Furthermore, frontal electrode cites where the SP was observed showed no sign of a training effect. The results suggest that 1) the N250 and SN have different sources and 2) at the very least, the learning-induced N250 indexes a different attentional subprocess from the target-induced SN and could be unrelated to attention.

Meeting abstract presented at VSS 2016


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