Deception detection and forensic psychology

Breakthrough Percepts of Familiar Faces

The paper demonstrates the effectiveness of the Fringe-P3 method in detecting the intrinsic salience of personally-familiar faces in an RSVP paradigm.

Lie Detectors for Face Recognition

This paper proposes an fMRI-based lie detection method for face recognition that identifies brain regions specific to face familiarity rather than general deception.

Evaluating Physiological Indicators in Detecting Deception and Truthfulness using the Comparison Question Test (CQT)

This study evaluates physiological indicators like pupil response, EDA, HR, and facial temperature to detect deception using CQT in an Asian context, finding pupil response as the strongest predictor.

Dynamic valuation bias explains social influence on cheating behavior

The paper investigates how observing others' dishonesty influences cheating behavior through dynamic valuation bias and identifies neural mechanisms involved in this process.

Nothing but lies: improving the validity of neural predictors of deception

The paper improves the validity of neural predictors of deception by identifying and removing confounding signals using novel machine learning methods.

Reputation risk during dishonest social decision-making modulates anterior insular and cingulate cortex activity and connectivity

The paper investigates neural activity and connectivity during dishonest decision-making under reputation risk, finding increased involvement of ACC and AI in immoral decisions.

Meta-analytic connectivity modelling of deception-related brain regions

The paper uses meta-analytic connectivity modelling to identify brain regions and their connections involved in deception, finding the supramarginal gyrus as key to sociocognitive deception processes.

Collaborations and deceptions in strategic interactions revealed by hyperscanning fMRI

This study uses hyperscanning fMRI to analyze deception and cooperation in a game, finding brain connectivity patterns linked to lying behavior and social trust.

Catching a liar through facial expression of fear

The paper tests the leakage theory of deception by analyzing fear facial expressions in video clips using computer vision and machine learning, finding that fear-related features can distinguish liars from truth-tellers with over 80% accuracy.

Contribution of self- and other-regarding motives to (dis)honesty

This study investigates how self- and other-regarding motives independently influence dishonesty and identifies distinct neural networks associated with each motive.

How the Motor Aspect of Speaking Influences the Blink Rate

This study finds that motor activity, specifically lip movements during speaking, significantly increases blink rate, suggesting caution in using blinks as neurological indicators during interviews.

Individual differences in (dis)honesty are represented in the brain's functional connectivity:Robust out-of-sample prediction of cheating behavior

This study predicts cheating behavior using brain connectivity patterns and finds that neural networks related to self-referential thinking and control are key predictors of honesty.

When honest people cheat, and cheaters are honest: Cognitive control processes override our moral default

The paper investigates how cognitive control influences honesty and dishonesty by examining neural activity in specific brain regions during a cheating task.

fMRI Correlates of Reaction Time Prolongation during intentional False Responding; an inter-individual difference study

The paper investigates how brain activity correlates with reaction time prolongation during intentional false responding, identifying regions associated with RT cost and baseline speed.