Evidence map›Paper›PMID 41727173›Full record

ArticlebioRxiv : the preprint server for biology2026

Voluntary temporal attention improves perception even in the absence of temporal competition.

Karen J Tian, Jennifer A Motzer, Rachel N Denison

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. 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.

Karen J TianDepartment of Psychological and Brain Sciences, Boston University.ORCID 0000-0002-5399-2010
Jennifer A MotzerDepartment of Psychological and Brain Sciences, Boston University.ORCID 0009-0003-0368-6714
Rachel N DenisonDepartment of Psychological and Brain Sciences, Boston University.ORCID 0000-0002-6304-5236

Funding

Testing a Dynamic Spatiotemporal Normalization Framework for Human VisionR01EY037358 · NEI · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI Rachel Denison · 2025 to 2026
$967k
NEI NIH HHS R01 EY037358
6 · The paper itself

Abstract

When successive stimuli occur close enough together in time, their perception can be impaired. Such impairments indicate temporal competition between successive stimuli for representational resources. Voluntary temporal attention can bias processing resources in favor of a behaviorally relevant moment, improving perception at the attended time at the expense of impairments at unattended times. However it is unclear whether these perceptual tradeoffs across time arise because voluntary temporal attention selects among actively competing stimulus representations, such as within visual working memory, or if instead, temporal attention facilitates stimulus processing prior to a competitive stage. Here we used a temporal cueing task with up to two targets in succession to test whether and how the effects of temporal attention depend on temporal competition. We found that voluntary temporal attention improved performance even in the absence of temporal competition, when only one stimulus appeared during the trial. Moreover, the magnitude of attentional enhancement was comparable with and without competition. These results suggest that voluntary temporal attention enhances perception by facilitating processing prior to a competitive stage, rather than by resolving conflicts between actively competing stimulus representations.

Indexed as

selective attentiontemporal attentiontemporal competitionvisual perceptionvoluntary attention

Identifiers

PMID41727173
PMCPMC12918836

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.