What does distractibility in ADHD reveal about mechanisms for top-down attentional control?

Abstract

In this study, we attempted to clarify whether distractibility in ADHD might arise from increased sensory-driven interference or from inefficient top-down control. We employed an attentional filtering paradigm in which discrimination difficulty and distractor salience (amount of image "graying") were parametrically manipulated. Increased discrimination difficulty should add to the load of top-down processes, whereas increased distractor salience should produce stronger sensory interference. We found an unexpected interaction of discrimination difficulty and distractor salience. For difficult discriminations, ADHD children filtered distractors as efficiently as healthy children and adults; as expected, all three groups were slower to respond with high vs. low salience distractors. In contrast, for easy discriminations, robust between-group differences emerged: ADHD children were much slower and made more errors than either healthy children or adults. For easy discriminations, healthy children and adults filtered out high salience distractors as easily as low salience distractors, but ADHD children were slower to respond on trials with low salience distractors than they did on trials with high salience distractors. These initial results from a small sample of ADHD children have implications for models of attentional control, and ways in which it can malfunction. The fact that ADHD children exhibited efficient attentional filtering when task demands were high, but showed deficient and atypical distractor filtering under low task demands suggests that attention deficits in ADHD may stem from a failure to efficiently engage top-down control rather than an inability to implement filtering in sensory processing regions.

Published by Elsevier B.V.

Figures

Fig. 1

Examples of stimuli and stimulus configurations. 1a) Examples of target images created from morphing an image of an ape with an image of a woman, in 1000 steps. Perceptual thresholds could be calculated using the number of morphing steps to quantify the images. 1b–d) Examples of stimulus groupings, illustrating different levels of distractor salience and spatial configurations.

Fig. 2

In 2a and 2c, response time is plotted as a function of distractor salience for difficult and easy discriminations, for each of the three participant groups. In 2b and 2d, filtering cost (the intra-individual difference in response time for trials with high salience distractors and response time for trials with low salience distractors) is plotted for difficult and easy discriminations, for each subject group.

Fig. 3

Error rate as a function of distractor salience for easy and difficult discriminations.

Fig. 4

Analysis of speed-accuracy trade-off for healthy adults, healthy children, and ADHD children.