Dataset Information

Using Functional Near-Infrared Spectroscopy to Assess Brain Activation Evoked by Guilt and Shame.

ABSTRACT: Functional near-infrared spectroscopy (fNIRS) is a promising brain imaging modality for studying the neural substrates of moral emotions. However, the feasibility of using fNIRS to measure moral emotions has not been established. In the present study, we used fNIRS to detect the brain activation evoked by two typical moral emotions-guilt and shame. We presented the participants with guilt and shame context to evoke emotional responses and measured the brain activity by using fNIRS. The univariate general linear model analysis showed significant activations for both emotions in the orbitofrontal cortex, dorsolateral prefrontal cortex, and middle temporal gyrus, and specific activation for guilt in the right temporoparietal junction. The multivariate classification analysis showed an overall recognition accuracy of 52.50%, which was significantly higher than the chance level in classifying the guilt, shame, and neutral emotions. These results suggested the feasibility of using fNIRS to assess the brain activation evoked by guilt and shame and demonstrated the potentials of fNIRS in studying the neural correlates of moral emotions.

SUBMITTER: Duan L

PROVIDER: S-EPMC7298148 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Using Functional Near-Infrared Spectroscopy to Assess Brain Activation Evoked by Guilt and Shame.

Duan Lian L Feng Qiudi Q Xu Pengfei P

Frontiers in human neuroscience 20200610

Functional near-infrared spectroscopy (fNIRS) is a promising brain imaging modality for studying the neural substrates of moral emotions. However, the feasibility of using fNIRS to measure moral emotions has not been established. In the present study, we used fNIRS to detect the brain activation evoked by two typical moral emotions-guilt and shame. We presented the participants with guilt and shame context to evoke emotional responses and measured the brain activity by using fNIRS. The univariat ...[more]

PMID: 32587508

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Project description:Experiencing frustration while driving can harm cognitive processing, result in aggressive behavior and hence negatively influence driving performance and traffic safety. Being able to automatically detect frustration would allow adaptive driver assistance and automation systems to adequately react to a driver's frustration and mitigate potential negative consequences. To identify reliable and valid indicators of driver's frustration, we conducted two driving simulator experiments. In the first experiment, we aimed to reveal facial expressions that indicate frustration in continuous video recordings of the driver's face taken while driving highly realistic simulator scenarios in which frustrated or non-frustrated emotional states were experienced. An automated analysis of facial expressions combined with multivariate logistic regression classification revealed that frustrated time intervals can be discriminated from non-frustrated ones with accuracy of 62.0% (mean over 30 participants). A further analysis of the facial expressions revealed that frustrated drivers tend to activate muscles in the mouth region (chin raiser, lip pucker, lip pressor). In the second experiment, we measured cortical activation with almost whole-head functional near-infrared spectroscopy (fNIRS) while participants experienced frustrating and non-frustrating driving simulator scenarios. Multivariate logistic regression applied to the fNIRS measurements allowed us to discriminate between frustrated and non-frustrated driving intervals with higher accuracy of 78.1% (mean over 12 participants). Frustrated driving intervals were indicated by increased activation in the inferior frontal, putative premotor and occipito-temporal cortices. Our results show that facial and cortical markers of frustration can be informative for time resolved driver state identification in complex realistic driving situations. The markers derived here can potentially be used as an input for future adaptive driver assistance and automation systems that detect driver frustration and adaptively react to mitigate it.

Dataset Information

Using Functional Near-Infrared Spectroscopy to Assess Brain Activation Evoked by Guilt and Shame.

Publications

Using Functional Near-Infrared Spectroscopy to Assess Brain Activation Evoked by Guilt and Shame.

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