Impaired social cognition in schizophrenia during the Ultimatum Game: An EEG study

Horat, Sibylle K.; Favre, Grégoire; Prévot, Anne; Ventura, Joseph; Herrmann, Françoís; Gothuey, Isabelle; Merlo, M.C.G.; Missonnier, Pascal

doi:10.1016/j.schres.2017.05.037

Cited by 23 publications

(22 citation statements)

References 40 publications

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“…If the responder accepts the proposal, money is shared accordingly and both win money. However, if the responder refuses, both players end up with (Horat et al, 2017). Classically, the game ends after the responder’s decision (Guth et al, 1982).…”

Section: Methodsmentioning

confidence: 99%

“…It presented as a smiling or frowning face in the proposer condition, whereas the smiley was neutral in the responder condition. This figure has been adapted from Horat et al (2017). …”

Section: Methodsmentioning

confidence: 99%

“…The parameters of the recording and data processing have been replicated from Horat et al (2017). The participants were comfortably seated in an electrically shielded, sound- and light-attenuated room.…”

Section: Methodsmentioning

confidence: 99%

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Differences in Social Decision-Making between Proposers and Responders during the Ultimatum Game: An EEG Study

Horat

Prévot

Richiardi

et al. 2017

Front. Integr. Neurosci.

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The Ultimatum Game (UG) is a typical paradigm to investigate social decision-making. Although the behavior of humans in this task is already well established, the underlying brain processes remain poorly understood. Previous investigations using event-related potentials (ERPs) revealed three major components related to cognitive processes in participants engaged in the responder condition, the early ERP component P2, the feedback-related negativity (FRN) and a late positive wave (late positive component, LPC). However, the comparison of the ERP waveforms between the responder and proposer conditions has never been studied. Therefore, to investigate condition-related electrophysiological changes, we applied the UG paradigm and compared parameters of the P2, LPC and FRN components in twenty healthy participants. For the responder condition, we found a significantly decreased amplitude and delayed latency for the P2 component, whereas the mean amplitudes of the LPC and FRN increased compared to the proposer condition. Additionally, the proposer condition elicited an early component consisting of a negative deflection around 190 ms, in the upward slope of the P2, probably as a result of early conflict-related processing. Using independent component analysis (ICA), we extracted one functional component time-locked to this deflection, and with source reconstruction (LAURA) we found the anterior cingulate cortex (ACC) as one of the underlying sources. Overall, our findings indicate that intensity and time-course of neuronal systems engaged in the decision-making processes diverge between both UG conditions, suggesting differential cognitive processes. Understanding the electrophysiological bases of decision-making and social interactions in controls could be useful to further detect which steps are impaired in psychiatric patients in their ability to attribute mental states (such as beliefs, intents, or desires) to oneself and others. This ability is called mentalizing (also known as theory of mind).

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Section: Methodsmentioning

confidence: 99%

“…It presented as a smiling or frowning face in the proposer condition, whereas the smiley was neutral in the responder condition. This figure has been adapted from Horat et al (2017). …”

Section: Methodsmentioning

confidence: 99%

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Differences in Social Decision-Making between Proposers and Responders during the Ultimatum Game: An EEG Study

Horat

Prévot

Richiardi

et al. 2017

Front. Integr. Neurosci.

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“…EEG signal is a non-stationary time series. It can be analyzed in time domain by extracting features such as standard deviation, skewness, peak mean absolute value of the signal or by using event-related potential (ERP) [19]. Frequency domain features also should be paid attention to.…”

Section: Introductionmentioning

confidence: 99%

Four-classes Human Emotion Recognition Via Entropy Characteristic and Random Forest。

Zhang

Min²

2020

ITC

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Human Emotion Recognition is of vital importance to realize human-computer interaction (HCI), while multichannel electroencephalogram (EEG) signals gradually replace other physiological signals and become the main basis of emotional recognition research with the development of brain-computer interface (BCI). However, the accuracy of emotional classification based on EEG signals under video stimulation is not stable, which may be related to the characteristics of EEG signals before receiving stimulation. In this study, we extract the change of Differential Entropy (DE) before and after stimulation based on wavelet packet transform (WPT) to identify individual emotional state. Using the EEG emotion database DEAP, we divide the experimental EEG data in the database equally into 15 sets and extract their differential entropy on the basis of WPT. Then we calculate value of DE change of each separated EEG signal set. Finally, we divide the emotion into four categories in the two-dimensional valence-arousal emotional space by combining it with the integrated algorithm, Random Forest (RF). The simulation results show that the WPT-RF model established by this method greatly improves the recognition rate of EEG signal, with an average classification accuracy of 87.3%. In addition, we use WPT-RF model to train individual subjects, and the classification accuracy reached 97.7%.

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“…In this perspective, facial recognition ability falls into the first domain, social perception. While patients with schizophrenia show deficits in all three domains [ 6 , 34 , 35 ], previous studies have consistently demonstrated that the lack of facial emotion recognition is related to reduced temporal lobe volume. In particular, a review stated that abnormalities in face processing in schizophrenia are strongly associated with structural abnormalities in regions such as fusiform gyrus, superior temporal sulcus, amygdala and prefrontal cortex [ 36 ].…”

Section: Introductionmentioning

confidence: 99%

Empathy and Social Attribution Skills Moderate the Relationship between Temporal Lobe Volume and Facial Expression Recognition Ability in Schizophrenia

Jung

Baik

Kim

et al. 2020

Clin Psychopharmacol Neurosci

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Objective While impaired facial expression recognition has been closely associated with reduced temporal lobe volume in patients with schizophrenia, this study aimed at examining whether empathy and social attribution affect such a relationship. Methods A total of 43 patients with schizophrenia and 43 healthy controls underwent a facial expression recognition task (FERT) and magnetic resonance imaging. Basic empathy scale and the social attribution task-multiple choice were used to measure empathy and social attribution. Results Patients with schizophrenia showed significant positive correlations between the total temporal lobe volume and the FERT-accuracy (FERT-ACC). Diminished temporal lobe volume predicted the impaired facial emotion recognition ability. Both empathy and social attribution played roles as moderators of the path from the left amygdala volume, left fusiform gyrus volume, both sides of the superior temporal gyrus volume, and left middle temporal gyrus volume to the FERT-ACC. In contrast, empathy alone functioned as a moderator between the right fusiform gyrus volume, right middle temporal gyrus volume, and FERT-ACC. No significant interaction was found for healthy controls. Conclusion Our results suggest that social cognition remediation training on empathy and social attribution, could buffer the negative effects of small temporal lobe volume on interpersonal emotional communication in patients with schizophrenia.

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Impaired social cognition in schizophrenia during the Ultimatum Game: An EEG study

Cited by 23 publications

References 40 publications

Differences in Social Decision-Making between Proposers and Responders during the Ultimatum Game: An EEG Study

Differences in Social Decision-Making between Proposers and Responders during the Ultimatum Game: An EEG Study

Four-classes Human Emotion Recognition Via Entropy Characteristic and Random Forest。

Empathy and Social Attribution Skills Moderate the Relationship between Temporal Lobe Volume and Facial Expression Recognition Ability in Schizophrenia

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