Evidence map›Paper›PMID 40637499›Full record

ArticleJournal of vision2025

Regularities in temporal context influence the window of temporal integration.

Ramya Mudumba, Narayanan Srinivasan

Abstract read
In one paragraph

Article in Journal of vision, 2025. 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

2 authors.

Ramya MudumbaDepartment of Cognitive Science, Indian Institute of Technology Kanpur, Kanpur, India.
Narayanan SrinivasanDepartment of Cognitive Science, Indian Institute of Technology Kanpur, Kanpur, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Perceptual content is integrated as it unfolds in real time within temporal windows. Understanding the dynamics of temporal integration requires understanding the influence of an ongoing temporal context. Toward this goal, we developed a novel paradigm of temporal integration where two halves of a Kanizsa square are integrated together (seen as a full square) or segregated (not seen as a full square) as a function of a temporal gap between them. The two halves are embedded within a preceding and succeeding context of rotating Kanizsa discs leading up to and trailing away from them. We wanted to investigate whether integration is subject to frames of interest or whether the dynamics of the context influence form-part integration. Through three experiments, we manipulated the nature of the rotation: (a) the context being temporally correlated or random in Experiment 1, (b) the variance of the temporally correlated context in Experiment 2, and (c) the mean of the temporally correlated context in Experiment 3. Our results showed that the sensitivity of seeing an integrated square was better when the context aided anticipation of the target frames, the effect being selective at different inter-stimulus intervals depending on the properties of the context. We interpret these results in light of a probabilistic view of temporal windows of integration. Our results provide evidence for an inherent adaptiveness in the extent or window of temporal integration. The results also reinforce the general account of extended temporal processing and iterative updating and inform rough timescales of context effects on this process.

Indexed as

Form PerceptionPattern Recognition, VisualTime PerceptionAdultFemaleHumansMalePhotic StimulationTime FactorsYoung Adult

Identifiers

PMID40637499
PMCPMC12255175

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.