Evidence map›Paper›PMID 34677007›Full record

ArticleBrain and behavior2021

Lie to my face: An electromyography approach to the study of deceptive behavior.

Anastasia Shuster, Lilah Inzelberg, Ori Ossmy, Liz Izakson, Yael Hanein, Dino J Levy

Open access · goldAbstract read
In one paragraph

Article in Brain and behavior, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.1field-weighted citation impact, top 9% of its field
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

4 citing papers in PubMed, 16 citations in OpenAlex.

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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

6 authors at 2 institutions in 3 countries.

Anastasia ShusterSagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
Lilah InzelbergSagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
Ori OssmyDepartment of Psychology and Center of Neural Science, New York University, New York City, New York, USA.ORCID 0000-0002-7675-0890
Liz IzaksonSagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
Yael HaneinSagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
Dino J LevySagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
Tel Aviv University · ILCity University of New York · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDeception is present in all walks of life, from social interactions to matters of homeland security. Nevertheless, reliable indicators of deceptive behavior in real-life scenarios remain elusive.

methodsBy integrating electrophysiological and communicative approaches, we demonstrate a new and objective detection approach to identify participant-specific indicators of deceptive behavior in an interactive scenario of a two-person deception task. We recorded participants' facial muscle activity using novel dry screen-printed electrode arrays and applied machine-learning algorithms to identify lies based on brief facial responses.

resultsWith an average accuracy of 73%, we identified two groups of participants: Those who revealed their lies by activating their cheek muscles and those who activated their eyebrows. We found that the participants lied more often with time, with some switching their telltale muscle groups. Moreover, while the automated classifier, reported here, outperformed untrained human detectors, their performance was correlated, suggesting reliance on shared features.

conclusionsOur findings demonstrate the feasibility of using wearable electrode arrays in detecting human lies in a social setting and set the stage for future research on individual differences in deception expression.

Indexed as

DeceptionIndividualityAlgorithmsElectromyographyHumansMachine Learningcognitionelectrophysiologyexperimental psychologypsychology

Identifiers

PMID34677007
PMCPMC8671780
OpenAlexW3165524924

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.