Elsevier

Vision Research

Volume 38, Issue 9, May 1998, Pages 1183-1198
Vision Research

External noise distinguishes attention mechanisms

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Abstract

We developed and tested a powerful method for identifying and characterizing the effect of attention on performance in visual tasks as due to signal enhancement, distractor exclusion, or internal noise suppression. Based on a noisy Perceptual Template Model (PTM) of a human observer, the method adds increasing amounts of external noise (white gaussian random noise) to the visual stimulus and observes the effect on performance of a perceptual task for attended and unattended stimuli. The three mechanisms of attention yield three “signature” patterns of performance. The general framework for characterizing the mechanisms of attention is used here to investigate the attentional mechanisms in a concurrent location-cued orientation discrimination task. Test stimuli—Gabor patches tilted slightly to the right or left—always appeared on both the left and the right of fixation, and varied independently. Observers were cued on each trial to attend to the left, the right, or evenly to both stimuli, and decide the direction of tilt of both test stimuli. For eight levels of added external noise and three attention conditions (attended, unattended, and equal), subjects' contrast threshold levels were determined. At low levels of external noise, attention affected threshold contrast: threshold contrasts for non-attended stimuli were systematically higher than for equal attention stimuli, which were, in turn, higher than for attended stimuli. Specifically, when the rms contrast of the external noise is below 10%, there is a consistent 17% elevation of contrast threshold from attended to unattended condition across all three subjects. For higher levels of external noise, attention conditions did not affect threshold contrast values at all. These strong results are characteristics of a signal enhancement, or equivalently, an internal additive noise reduction mechanism of attention.

Keywords

Visual attention
Signal enhancement
Distractor exclusion
Internal noise suppression
Additive internal noise
Multiplicative internal noise
Equivalent internal noise
Perceptual template model
Concurrent paradigm

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