Evidence map›Paper›PMID 35445159›Full record

ArticleHeliyon2022

Where to display vital information? ERP evidence for background changes.

Greeshma Sharma, Joy Chatterjee, Sushil Chandra

Abstract read
In one paragraph

Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Greeshma SharmaDept. of Biomedical Engineering, Institute of Nuclear Medicine and Allied Sciences, DRDO, New Delhi, India.
Joy ChatterjeeElectrical Engineering Department, National Institute of Technology, Kurukshetra, Haryana, India.
Sushil ChandraDept. of Biomedical Engineering, Institute of Nuclear Medicine and Allied Sciences, DRDO, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Critical decision systems require expeditious and accurate responses to the displayed information. In addition to content, location and background are equally important. Several visual search studies have pointed out the differences and compared modes of top-down attention allocation: distractor suppression and attentional capture. Previous studies have used color (mainly) and shape as a feature but have overlooked luminance as a feature for studying underlying attention mechanisms. The present study attempts to bridge this gap. In this study, participants performed a target-distractor discrimination task by identifying a randomly appearing target from the pool of distractors based on defined luminance levels. Background change was noticed by manipulating the task such as making visible quadrant boundaries over the screen. The preliminary evidence suggested that displaying information at the top-left of the screen had higher percentage accuracy; whereas, response time (RT) remained unaffected. Improvement in RT and percentage accuracy was observed with task manipulation. Event-related potential (ERP) analysis revealed elicited Distractor Positivity (PD), providing evidence for the distractor suppression hypothesis. Further, differences emerged in the topographic plot of N2pc and PD. In sum, the result contributes to classic debate of capture vs. suppression and provides a crucial connection between display design and electrophysiological indices, emphasizing locations and background as equally important factors.

Indexed as

Attentional captureDistractor positivity (PD)Distractor suppression hypothesisEvent-related potentials (ERP)Target-distractor discrimination tasks

Identifiers

PMID35445159
PMCPMC9014389

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.