Decoding the processing of lying using functional connectivity MRI
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BACKGROUND: Previous functional MRI (fMRI) studies have demonstrated group differences in brain activity between deceptive and honest responses. The functional connectivity network related to lie-telling remains largely uncharacterized. METHODS: In this study, we designed a lie-telling experiment that emphasized strategy devising. Thirty-two subjects underwent fMRI while responding to questions in a truthful, inverse, or deceitful manner. For each subject, whole-brain functional connectivity networks were constructed from correlations among brain regions for the lie-telling and truth-telling conditions. Then, a multivariate pattern analysis approach was used to distinguish lie-telling from truth-telling based on the functional connectivity networks. RESULTS: The classification results demonstrated that lie-telling could be differentiated from truth-telling with an accuracy of 82.81% (85.94% for lie-telling, 79.69% for truth-telling). The connectivities related to the fronto-parietal networks, cerebellum and cingulo-opercular networks are most discriminating, implying crucial roles for these three networks in the processing of deception. CONCLUSIONS: The current study may shed new light on the neural pattern of deception from a functional integration viewpoint.
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Increased cognitive load can result in differential verbal behaviours between liars and truthtellers.
“Increased cognitive load in such circumstances (e.g., Bhatt et al., 2009; Jiang et al., 2015) can result in differential verbal behaviours between liars and truthtellers.”
From Sorting Insiders From Co-Workers: Remote Synchronous Computer-Mediated Triage for Investigating Insider Attacks (2024) · cites this paper as Jiang et al., 2015
The Discussion (Deception-modulated network; page unavailable) links lying to greater cognitive load, and the Results (Behavioral data; page unavailable) report longer reaction times for lying than truth-telling. But participants responded by button press, not verbally, and the study did not test whether increasing cognitive load causes differences in verbal behaviour. (LLM, conf=0.86)
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- Authors
- Jiang, W., Liu, H., Zeng, L., Liao, J., Shen, H., Luo, A., Hu, D., & Wang, W.
- Affiliations
- Central South University (CN)
- National University of Defense Technology (CN)
- Corresponding author
- Hu, Dewen
- Wang, Wei
- Venue
- Behavioral and Brain Functions
- Published
- 2015-01-17
- Volume
- 11
- Issue
- 1
- Pages
- 1-1
- ISSN
- 1744-9081 (ISSN-L)
- PMC
- PMC4316800
- OpenAlex
- W1965695782
- Cited by
- 61
- References
- 87
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 2 · 2023: 2 · 2022: 6 · 2021: 15 · 2020: 6 · 2019: 7 · 2018: 4 · 2017: 8 · 2016: 6 · 2015: 1
- FWCI
- 10.39
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Behavioral and Brain Functions (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (13B013, 61375111, 61420106001)
- Topics
- Social Sciences › Psychology › Social Psychology › Deception detection and forensic psychology
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Keywords
- deception, lying, deception detection, functional connectivity networks, frontoparietal network, cerebellum, cingulo-opercular network, truth-telling, deception strategies
- MeSH terms
- Brain Mapping, Cerebellum, Female, Frontal Lobe, Generalization, Psychological, Gyrus Cinguli, Humans, Image Processing, Computer-Assisted, Deception, Magnetic Resonance Imaging, Male, Nerve Net, Neural Pathways, Parietal Lobe, Reaction Time, Young Adult
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