Academic journal article Attention, Perception and Psychophysics

How Do We Select Multiple Features? Transient Costs for Selecting Two Colors Rather Than One, Persistent Costs for Color-Location Conjunctions

Academic journal article Attention, Perception and Psychophysics

How Do We Select Multiple Features? Transient Costs for Selecting Two Colors Rather Than One, Persistent Costs for Color-Location Conjunctions

Article excerpt

Published online: 19 November 2013

© Psychonomic Society, Inc. 2013

Abstract In a previous study Lo, Howard, & Holcombe (Vision Research 63:20- 33, 2012), selecting two colors did not induce a performance cost, relative to selecting one color. For example, requiring possible report of both a green and a red target did not yield a worse performance than when both targets were green. Yet a cost of selecting multiple colors was observed when selection needed be contingent on both color and location. When selecting a red target to the left and a green target to the right, superimposing a green distractor to the left and a red distractor to the right impeded performance. Possibly, participants cannot confine attention to a color at a particular location. As a result, distractors that share the target colors disrupt attentional selection of the targets. The attempt to select the targets must then be repeated, which increases the likelihood that the trial terminates when selection is not effective, even for long trials. Consistent with this, here we find a persistent cost of selecting two colors when the conjunction of color and location is needed, but the cost is confined to short exposure durations when the observer just has to monitor red and green stimuli without the need to use the location information. These results suggest that selecting two colors is time-consuming but effective, whereas selection of simultaneous conjunctions is never entirely successful.

Keywords Feature-based attention . Perceptual lag . Multiple-feature cost . Resource theory . Mixture model

Introduction

Feature-based selection

Here, we seek to better understand the nature of the mental representations that attention is allocated to. Evidence suggests that attention can be allocated to features (such as colors), as well as regions and objects (e.g., Arman, Ciaramitaro, & Boynton, 2006; Bichot, Rossi, & Desimone, 2005; Chelazzi, Miller, Duncan, & Desimone, 1993;Sàenz, Buracas, & Boynton, 2002, 2003; White & Carrasco, 2011). Just as selecting multiple objects or regions reduces performance, relative to selecting a single object, so might selecting multiple features. We will investigate this here.

Any performance cost for processing multiple stimuli might arise at selection or at access. Selection and access are thought to be separate stages of processing required to report on stimuli in the presence of distractors (Huang & Pashler, 2007).

Selection refers to confining processing to relevant stimuli from a complex display that includes irrelevant stimuli. It has been theorized to precede access, which refers to processing the contents of the selected stimuli. Consider that a person waiting to pick up a friend in an airport arrival hall may search for the color blue because the friend said she would be wearing a blue dress. So, using feature-based attention, the waiting person directs attention to all the passengers with blue outfits. This is selection. Once the candidates are selected, their characteristics must be apprehended to identify which is the friend. Apprehending the candidates' characteristics, such as their height, skin color, and identity, requires access.

Evidence for feature-based selection was found by Bichot et al. (2005) among others. Bichot et al. demonstrated that searching for a target with a particular color enhanced the activity of the population of V4 neurons that prefer that color throughout the visual field, suggesting that attention can be allocated to a particular color regardless of stimulus location.

If featural attention has limited capacity in the same way as other forms of attention, selecting multiple features should induce a cost. For example, selecting both red and green objects might be less effective than selecting an equal total number of green objects. Here, we will use the word attribute to refer to a feature dimension, such as color, and feature will refer to an individual value, such as red. …

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