Evidence map›Paper›PMID 34319439›Full record

ArticlePsychological research2022

Context dependency of time-based event-related expectations for different modalities.

Felix Ball, Julia Andreca, Toemme Noesselt

Abstract read
In one paragraph

Article in Psychological research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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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.

Felix BallDepartment of Biological Psychology, Faculty of Natural Science, Otto-Von-Guericke-University, PO Box 4120, 39106, Magdeburg, Germany. Felix.Ball@ovgu.de.ORCID http://orcid.org/0000-0001-5970-8511
Julia AndrecaDepartment of Biological Psychology, Faculty of Natural Science, Otto-Von-Guericke-University, PO Box 4120, 39106, Magdeburg, Germany.
Toemme NoesseltDepartment of Biological Psychology, Faculty of Natural Science, Otto-Von-Guericke-University, PO Box 4120, 39106, Magdeburg, Germany.

Funding

European Funds for Regional Development ZS/2016/04/78113
6 · The paper itself

Abstract

Expectations about the temporal occurrence of events (when) are often tied with the expectations about certain event-related properties (what and where) happening at these time points. For instance, slowly waking up in the morning we expect our alarm clock to go off; however, the longer we do not hear it the more likely we already missed it. However, most current evidence for complex time-based event-related expectations (TBEEs) is based on the visual modality. Here we tested whether implicit TBEEs can act cross-modally. To this end, visual and auditory stimulus streams were presented which contained early and late targets embedded among distractors (to maximise temporal target uncertainty). Foreperiod-modality-contingencies were manipulated run-wise: visual targets either occurred early in 80% of trials and auditory targets occurred late in 80% of trials or vice versa. Participants showed increased sensitivity for expected auditory early/visual late targets which increased over time while the opposite pattern was observed for visual early/auditory late targets. A benefit in reaction times was only found for auditory early trials. Together, this pattern of results suggests that implicit context-dependent TBEEs for auditory targets after short foreperiods (be they correct or not) dominated and determined which modality became more expected at the late position irrespective of the veridical statistical regularity. Hence, TBEEs in cross-modal and uncertain environments are context-dependent, shaped by the dominant modality in temporal tasks (i.e., auditory) and only boost performance cross-modally when expectations about the event after the short foreperiod match with the run-wise context (i.e., auditory early/visual late).

Indexed as

Auditory PerceptionMotivationAcoustic StimulationHumansPhotic StimulationReaction TimeVisual Perception

Identifiers

PMID34319439
PMCPMC9090878

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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.