Examining a Single-Salience-Map Hypothesis for Feature- Based Attention: Centroid Judgments for Orientation and Contrast

Inverso, Matthew; Wright, C. Wayne; Chubb, Charles; Sun, Peng; Sperling, George

doi:10.1037/e528942014-718

Cited by 1 publication

(2 citation statements)

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“…It has been traditionally studied with visual search tasks, and several studies indicated age-related deficits therein (Ball et al, 1990). Nonetheless, visual search tasks have been criticized because they do not clearly isolate the attentional filters guiding selection (Inverso, 2017). Furthermore, because these tasks are reaction-time based, and aging reduces processing speed, visualsearch may conflate age differences in feature-based selection with processing speed or response caution.…”

Section: Feature-based Attentionmentioning

confidence: 99%

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Older yet Sharp: No General Age-Related Decline in Focusing Attention

Souza¹,

Frischkorn²,

Oberauer³

2023

Preprint

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Attention is a multifaceted mechanism operating on space, features, and memory. Previous studies reported both decline and preservation of attention in aging. Yet, it is unclear if healthy aging differentially affects attentional selection in these domains. To address these inconsistencies, we evaluated the ability to focus attention in a battery of 11 tasks in a large sample of younger and older adults (n = 172/174). We addressed if (1) aging effects are consistent across different attention tasks, and (2) if there is domain-specific or domain-general age-related decline in focused attention. Both younger and older adults benefited from focusing attention on space, features, and memory representations. Within the same domain, some tasks showed a decline, whereas others showed improvement with aging; and, on average, attentional benefits were similar across age groups. These results are inconsistent with the claim that aging is associated with either domain-specific or domain-general deficits in focused attention.

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Section: Feature-based Attentionmentioning

confidence: 99%

“…Recently, a centroid paradigm was proposed to measure feature-based attention (Inverso, 2017;Sun et al, 2016). In this task, participants have to locate the center of gravity (aka centroid) of a briefly displayed cloud of dots varying in one feature dimension (e.g., color).…”

Section: Feature-based Attentionmentioning

confidence: 99%