Recent years have seen an explosion of research on the N2 component of the event-related potential, a negative wave peaking between 200 and 350 ms after stimulus onset. This research has focused on the influence of ''cognitive control,'' a concept that covers strategic monitoring and control of motor responses. However, rich research traditions focus on attention and novelty or mismatch as determinants of N2 amplitude. We focus on paradigms that elicit N2 components with an anterior scalp distribution, namely, cognitive control, novelty, and sequential matching, and argue that the anterior N2 should be divided into separate control-and mismatch-related subcomponents. We also argue that the oddball N2 belongs in the family of attention-related N2 components that, in the visual modality, have a posterior scalp distribution. We focus on the visual modality for which components with frontocentral and more posterior scalp distributions can be readily distinguished.Descriptors: N2, N200, Cognitive control, Error-related negativity, Feedback-related negativity, NoveltyThe P300 may be the most studied component of the event-related potential (ERP). Its amplitude is sensitive to stimulus probability and task relevance of the eliciting stimulus, and its latency reflects stimulus evaluation time (Johnson & Donchin, 1980, Chapter 12;Verleger, 1997). The P300 is commonly divided into two subcomponents with different scalp distributions and different functional correlates: a frontally maximal P3a that reflects the orienting of attention to unexpected or significant events in the environment and a parietally maximal P3b that indexes the updating of working memory (Courchesne, Hillyard, & Galambos, 1975;Debener, Makeig, Delorme, & Engel, 2005;Dien, Spencer, & Donchin, 2004;Donchin, 1981;Friedman, Cycowicz, & Gaeta, 2001;Goldstein, Spencer, & Donchin, 2002;Na¨a¨ta¨nen & Gaillard, 1983;Polich & Comerchero, 2003;Spencer, Dien, & Donchin, 1999, 2001Squires, N. K., Squires, & Hillyard, 1975).Commonly observed in combination with the P3a and P3b is the smaller, earlier N2. The label ''N2'' refers to the second negative peak in the averaged ERP waveform and is labeled as such because it follows a prominent frontocentral negative peak at around 100 ms in the auditory modality or a prominent temporooccipital negative peak at around 180 ms in the visual modality. So linked were the N2 and P3 in early research that they were often referred to as the ''N2-P3 complex,'' and some studies measured them in combination for purposes of correlation with stimulus probability (Squires, K. C., Petuchowsky, Wickens, & Donchin, 1977;Squires, K. C., Wickens, Squires, & Donchin, 1976).Recent years have seen a renewed interest in N2 components of the ERP as functionally distinct from P3 components and useful for understanding the nature and sequence of cognitive processes. For instance, a large literature has emerged focusing on the role of anterior N2s in cognitive control. Cognitive control is partly defined as the monitoring or regulation of ...

Learning to categorize objects can transform how they are perceived, causing relevant perceptual dimensions predictive of object category to become enhanced. For example, an expert mycologist might become attuned to species-specific patterns of spacing between mushroom gills but learn to ignore cap textures attributable to varying environmental conditions. These selective changes in perception can persist beyond the act of categorizing objects and influence our ability to discriminate between them. Using functional magnetic resonance imaging adaptation, we demonstrate that such category-specific perceptual enhancements are associated with changes in the neural discriminability of object representations in visual cortex. Regions within the anterior fusiform gyrus became more sensitive to small variations in shape that were relevant during prior category learning. In addition, extrastriate occipital areas showed heightened sensitivity to small variations in shape that spanned the category boundary. Visual representations in cortex, just like our perception, are sensitive to an object's history of categorization.

No abstract

How does learning to categorize objects affect how we visually perceive them? Behavioral, neurophysiological, and neuroimaging studies have tested the degree to which category learning influences object representations, with conflicting results. Some studies find that objects become more visually discriminable along dimensions relevant to previously learned categories, while others find no such effect. One critical factor we explore here lies in the structure of the morphspaces used in different studies. Studies finding no increase in discriminability often use “blended” morphspaces, with morphparents lying at corners of the space. By contrast, studies finding increases in discriminability use “factorial” morphspaces, defined by separate morphlines forming axes of the space. Using the same four morphparents, we created both factorial and blended morphspaces matched in pairwise discriminability. Category learning caused a selective increase in discriminability along the relevant dimension of the factorial space, but not in the blended space, and led to the creation of functional dimensions in the factorial space, but not in the blended space. These findings demonstrate that not all morphspaces stretch alike: Only some morphspaces support enhanced discriminability to relevant object dimensions following category learning. Our results have important implications for interpreting neuroimaging studies reporting little or no effect of category learning on object representations in the visual system: Those studies may have been limited by their use of blended morphspaces.

We manipulated categorical typicality and the presence of conflicting information as participants categorized multifeatured artificial animals. In Experiment 1, rule-irrelevant features were correlated with particular categories during training. In the test phase, participants applied a one-dimensional rule to stimuli with rule-irrelevant features that were category-congruent, category-incongruent, or novel. Category-incongruent and novel features delayed RT and P3 latency, but had no effect on the N2. Experiment 2 used a two-dimensional rule to create conflict between rule-relevant features. Conflict resulted in prolonged RTs and larger amplitudes of a prefrontal positive component, but had no impact on the N2. Stimuli with novel features did elicit a larger N2 than those with frequent features. These results suggest limitations on the generality of the N2′s sensitivity to conflicting information while confirming its sensitivity to attended visual novelty. KeywordsN2; N200; Event-related potentials; Conflict; Rule; P300 latencyThe study of perceptual categorization has long been concerned with the effects of typicality, selective attention to an object's features, and the need to suppress the influence of features suggesting the incorrect category (Allen & Brooks, 1991;Nosofsky, 1986;Regehr & Brooks, 1993;Rosch & Mervis, 1975;Smith, Patalano, & Jonides, 1998). The current study focuses on the influences of typicality and conflicting information during visual categorization and explores the degree to which ERP measures will reflect and perhaps help tease apart these two factors.For natural categories, typical exemplars (e.g., SPARROWas a type of bird) elicit faster verification responses than atypical exemplars (e.g., CHICKEN). Typicality can be thought of as the extent to which an item overlaps with the central tendency of a category or the amount of positive evidence supporting the assignment of an item to a category. Category verification times are also influenced by the presence of conflicting information or the amount of evidence suggesting assignment to the wrong category. For natural categories, this is most easily seen in prolonged RTs to reject items that share features with a target category but are not in fact members (as in rejecting BATas a type of bird; Heinze, Münte, & Kutas, 1998;McCloskey & Glucksberg, 1979). Despite these examples, it is fairly difficult to tease apart the influences of typicality and conflicting information, particularly for trials that receive the same response. For instance, as compared to sparrows, chickens are poor birds because they lack some common Address reprint requests to: Jonathan Folstein, Psychology Department, Vanderbilt University, 301 Wilson Hall, 111 21st Avenue South, Nashville, TN 37203, USA. E-mail: jonathan.r.folstein@vanderbilt.edu. NIH Public Access Author ManuscriptPsychophysiology. Author manuscript; available in PMC 2009 April 1. Published in final edited form as:Psychophysiology. 2008 April ; 45(3): 467-479. NIH-PA Author ManuscriptNIH-PA Aut...