The prioritization of perceptual processing in categorization

Abstract

The influence of attention on perception has been the focus of much research in the last 30 years. Typically, the effects of visual attention have been examined using tasks in which attention is directed by a cue to a particular location and a judgment is required about a stimulus at this location. These paradigms have demonstrated that spatially cued attention enhances stimulus discrimination (Downing, 1988;Hawkins et al., 1990;Henderson, 1996;Lu & Dosher, 1998;Luck, Hillyard, Mouloua, & Hawkins, 1996;Posner, 1980), enhances spatial resolution (Carrasco, Williams, & Yeshurun, 2002;Yeshurun & Carrasco, 1998, 1999, increases contrast sensitivity (Carrasco, Ling, & Read, 2004), and even accelerates the rate at which visual information is processed (Carrasco & McElree, 2001). A number of physiological studies, including f MRI studies (Liu, Pestilli, & Carrasco, 2005), PET studies (Corbetta, Miezin, Dobmeyer, Shulman, & Petersen, 1990), ERP studies (Hillyard, Vogel, & Luck, 1998;Luck et al., 1994), and single-cell studies (Luck, Chelazzi, Hillyard, & Desimone, 1997;Moran & Desimone, 1985; see Treue, 2001, for a review), have also shown attention-related modulation of sensory processes. For example, attention increases spatial resolution by contracting a neuron's receptive field around the attended stimulus (e.g., Desimone & Duncan, 1995;Luck et al., 1997;Moran & Desimone, 1985;Reynolds & Desimone, 1999).Despite these advances in understanding the influence of attention on perception, an unresolved issue concerns the extent to which attention influences perceptual processes in object categorization. In many models of categorization, the role of attention is located at the decision stage of categorization (Ashby & Gott, 1988;Estes, 1994;Nosofsky, 1986;Smith & Minda, 2000). For example, in Nosofsky's (1986) generalized context model (GCM), selectively attending to an object dimension stretches the psychological distance between the object representation and stored representations that differ along that dimension, decreasing the similarity between them. Since attention is limited in capacity, selectively attending to one dimension contracts psychological distance along other, less attended object dimensions. By dynamically altering the similarity relationships between an object representation and stored representations, selective attention has a major influence on category decision. Nevertheless, it is recognized that under particular conditions, such as when perceptual confusability between stimuli is high, attention can also influence perceptual processes-for example, by decreasing the variability of perceptual representations of stimuli along the attended object dimension (Ennis, 1988;Nosofsky, 1988).In order to examine the influence of attention on both decision and perception, it is necessary that a model of categorization should formally separate decision processes and perceptual processes. Two models that do this are decision bound theory (Ashby & Gott, 1988;Ashby & Maddox, 1994) and the extended generalized con...

Relative judgement is relatively difficult: Evidence against the role of relative judgement in absolute identification

“…Moreover, the most parsimonious explanation of the data is that a similar comparison process underlies both tasks. Indeed, one of the important aspects of the exemplar models of absolute identification is that they have also provided a very good account of data from other tasks including categorisation (Nosofsky, 1986;Lamberts, 2000, Guest & Lamberts, 2010, recognition (Brockdorff & Lamberts, 2000;Zaki & Nosofsky, 2001), same-different judgements (Cohen & Nosofsky, 2000), and visual search (Guest & Lamberts, 2011). This suggests that these processes are fundamental to cognition, adding weight to the notion that the similarity of the pattern of responses in absolute identification and simultaneous matching is an indication of a common underlying process.…”

Aging and the rate of visual information processing

“…The advantage of the TAF methodology is that it enables a purer estimate of processing speed than standard accuracy or RT designs, because the estimate is not contaminated by performance levels or the time taken to start processing. Indeed, this approach has been used to model the time course of performance and gain estimates of visual information processing rates in a variety of tasks such as perceptual categorization, visual search, recognition, and word identification (Brockdorff & Lamberts, 2000;Carrasco & McElree, 2001;Guest & Lamberts, 2010, 2011Kent, Howard, & Gilchrist, 2012; see Kent, Guest, Adelman, and Lamberts, 2014, for a review).…”

Stochastic accumulation of feature information in perception and memory

“… Lamberts (1995 , 1998) suggested that processing rates were independent of the utility of the dimension (how important a dimension is for correct categorization) and in several experiments demonstrated that perceptual processing rates were determined largely by perceptual salience of the dimension and not dimension utility (changing the category structure had little effect on processing rates; see also Ashby and Maddox, 1994 ; Maddox and Bogdanov, 2000 ; Maddox, 2001 ; Maddox and Dodd, 2003 ). However, given that visual attention is known to modulate sensory processing (e.g., Luck et al, 1994 ; Treue, 2001 ; Carrasco et al, 2002 ), accelerate the rate of perceptual processing ( Carrasco and McElree, 2001 ), and can be flexibly allocated ( Bundesen, 1990 ), Guest and Lamberts (2010) re-examined conditions under which knowledge of the category structure can influence perceptual processing rates. Their experiments used a categorization task in which all stimulus dimensions needed to be processed in order to ensure correct categorization but where stimulus dimensions clearly differed in their diagnosticity (how diagnostic they were of category membership) and diagnosticity was pitted against the perceptual salience of stimulus dimensions.…”