Evidence map›Paper›PMID 31982481›Full record

ArticleNeuropsychologia2020

Multiple identity tracking strategies vary by age: An ERP study.

Didem Pehlivanoglu, Audrey Duarte, Paul Verhaeghen

Abstract read
In one paragraph

Article in Neuropsychologia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Didem PehlivanogluGeorgia Institute of Technology, Atlanta, GA, USA. Electronic address: dpehlivanoglu@ufl.edu.
Audrey DuarteGeorgia Institute of Technology, Atlanta, GA, USA.
Paul VerhaeghenGeorgia Institute of Technology, Atlanta, GA, USA.

Funding

SEQUENTIAL/COORDINATIVE COMPLEXITY IN COGNITIVE AGINGR01AG016201 · NIA · SYRACUSE UNIVERSITY · PI VERHAEGHEN, PAUL · 1999 to 2014
$3.6M
Aging and Varieties of Cognitive ControlR56AG016201 · NIA · GEORGIA INSTITUTE OF TECHNOLOGY · PI VERHAEGHEN, PAUL · 2009 to 2009
$370k
NIA NIH HHS R01 AG016201NIA NIH HHS R56 AG016201
6 · The paper itself

Abstract

Top-down modulation underlies our ability to focus attention on task-relevant stimuli and ignore irrelevant distractions. Although age-related differences in neural correlates of top-down modulation have been investigated in multiple studies using variety of tasks (Gazzaley et al., 2005; Störmer et al., 2013), the effect of age on top-down modulation in a multiple identity tracking (MIT) task is still unknown. Thus, we investigated age-related differences in the MIT task by employing event-related potentials (ERPs). Participants tracked ten uniquely colored disks, two of which were randomly designated as targets at the beginning of each trial; the targets moved among four stationary distractors (serving as ERP baseline) and four moving distractors. Each type of stimulus was probed during the trial to capture differential patterns of brain activation. Tracking performance was similar across age groups. ERP data showed that younger adults performed the MIT task by enhancing the unique identities associated with targets relative to distractors through feature-based tracking. Older adults showed a pattern of distractor suppression engaging both location- and feature-based tracking strategies. Thus, our findings suggest that compared to younger adults, older adults engage greater levels of neural activity to achieve the same level of performance. These findings are discussed in light of theories of cognitive aging.

Indexed as

AdultAgedAge FactorsAgingAttentionCerebral CortexEvoked PotentialsFemaleHumansMaleMiddle AgedPsychomotor PerformanceSpace PerceptionVisual PerceptionYoung AdultAgingCRUNCHEvent-related potentials (ERPs)InhibitionMultiple identity trackingTop-down modulation

Identifiers

PMID31982481
PMCPMC7024019

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.