Evidence map›Paper›PMID 40011458›Full record

ArticleNature communications2025

Expectation violations signal goals in novel human communication.

Tatia Buidze, Tobias Sommer, Ke Zhao, Xiaolan Fu, Jan Gläscher

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

5 authors.

Tatia BuidzeInstitute of Systems Neuroscience, University Medical Center Eppendorf, Hamburg University, Hamburg, Germany. tatiabuidze@gmail.com.ORCID http://orcid.org/0009-0007-6686-1523
Tobias SommerInstitute of Systems Neuroscience, University Medical Center Eppendorf, Hamburg University, Hamburg, Germany.ORCID http://orcid.org/0000-0002-3504-7357
Ke ZhaoState Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
Xiaolan FuState Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0002-6944-1037
Jan GläscherInstitute of Systems Neuroscience, University Medical Center Eppendorf, Hamburg University, Hamburg, Germany. glaescher@uke.de.ORCID http://orcid.org/0000-0002-1020-7115

Funding

Deutsche Forschungsgemeinschaft (German Research Foundation) TRR169 "Cross-Modal Learning" (Project C9)
6 · The paper itself

Abstract

Communication, often grounded in shared expectations, faces challenges when a Sender and Receiver lack a common linguistic background. Our study explores how people instinctively turn to the fundamental principles of the physical world to overcome such barriers. Specifically, through an experimental game in which Senders convey messages via trajectories, we investigate how they develop novel strategies without relying on common linguistic cues. We build a computational model based on the principle of expectancy violations and a set of common universal priors derived from movement kinetics. The model replicates participant-designed messages with high accuracy and shows how its core variable-surprise-predicts the Receiver's physiological and neuronal responses in brain areas processing expectation violations. This work highlights the adaptability of human communication, showing how surprise can be a powerful tool in forming new communicative strategies without relying on common language.

Indexed as

CommunicationGoalsAdultBrainComputer SimulationCuesFemaleHumansMaleYoung Adult

Identifiers

PMID40011458
PMCPMC11865554

What OpenQuestion holds

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LicenceCC BY
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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.