Flavia Ciminaghi

Introduction: This study examined EEG and autonomic responses during an emotionally intense and morally paradoxical film scene from Sophie’s Choice. Methods: The cinematic content was segmented into 56 segments based on characters’ facial expressions and categorized by emotional valence. EEG and autonomic analyses were conducted across the full scene and by character. Results: Results showed increased delta activity in left frontal areas during morally ambiguous segments, indicating anticipatory control; theta in left temporoparietal regions reflected empathic engagement with the narrative; gamma increased during the victim’s distress, signaling emotional resonance. Skin conductance rose during Nazi-related scenes, highlighting external threat salience. Discussion: Findings illustrate how film can elicit distinct neurophysiological patterns, offering a powerful lens to study moral and emotional processing in immersive, narrative-driven contexts. These findings should be considered preliminary and exploratory, offering initial evidence on neurophysiological dynamics during morally complex cinematic experiences.

The study explored differences in decision recall between junior and senior decision-makers, focusing on accuracy (ACC) and response times (RTs) under varying feedback conditions. 117 participants completed 10 real-life decision-making scenarios, and their decision recall was examined in relation to feedback valence (positive or negative), decision-making styles, and tendencies toward Maximization. Results indicated that both junior and senior decision-makers recalled decisions with positive feedback more accurately than those with negative feedback, aligning with the “positivity bias” theory, where individuals tend to remember positive experiences more than negative ones. Seniors showed stronger recall for decisions with positive feedback but weaker for those with negative feedback compared to juniors, who performed better with negative feedback decisions recall. This pattern may reflect differences in professional experience and feedback processing across career stages, consistent with research on positivity and negativity biases. Regarding RTs, seniors had slower recall for decisions with positive feedback, potentially reflecting deeper cognitive processing, while both groups were slower to recall decisions with positive information overall. The study also found that individuals with higher Maximization tendencies, especially juniors, recalled decisions with negative feedback better, while seniors with avoidant decision-making styles were less accurate in recalling decisions with negative feedback. These findings highlight the importance of feedback delivery in professional environments and suggest that balancing positive and negative feedback is critical to maintain motivation and performance. Future research should further explore how expertise and individual differences affect decision recall and consider a neuroscientific approach to better understand the cognitive processes involved.

Empathy plays a key role in moral reasoning, yet its neural correlates during real-life moral decision-making remain unclear. This study examined how individual differences in trait empathy relate to EEG oscillatory activity (delta, theta, alpha, beta, and gamma bands) during a dyadic moral verbal exchange. Twenty-eight adults (14 same-gender dyads) completed the Interpersonal Reactivity Index (IRI) and the Balanced Emotional Empathy Scale (BEES) before engaging in a three-minute moral exchange. Correlation analyses revealed that affective empathy (BEES) was positively associated with temporo-central gamma power, cognitive empathy (IRI-PT) with frontal gamma and temporo-central alpha power, and fantasy (IRI-FS) with posterior alpha activity. In contrast, personal distress (IRI-PD) correlated negatively with temporo-central beta power. These findings indicate that individual differences in empathy dimension are associated with differentiated frequency-specific neural dynamics during moral exchanges, emphasizing the role of both affective and cognitive processes in socially embedded moral reasoning.

Background/Objectives: Goal-directed praxis actions (GOPAs) integrate perception, motor planning, and executive control. While neural correlates of single actions are known, less is understood about how complexity conditions and their hierarchical organization into elementary tasks shape neural dynamics during ecologically manual assembly tasks. This study tested how electrophysiological (EEG) activity reflects global complexity and selective engagement of executive and sensorimotor systems across GOPAs. Methods: 38 healthy young adults completed two assembly conditions differing in complexity (basic and advanced) decomposed into four elementary tasks: identification, handling, alignment, and joining. EEG was recorded across five frequency bands (delta, theta, alpha, beta, and gamma) and four regions of interest (ROI): frontal, fronto-central, temporo-central, and parieto-occipital. Results: Neural activity varied significantly depending on different complexity, elementary task, and ROI. The advanced-complexity condition elicited stronger neural responses compared to the basic-complexity condition, reflecting greater cognitive, and sensorimotor demands. A task-related gradient emerged, with joining showing the highest activity, followed by alignment, while identification and handling showed lower activation. Frontal regions, particularly in theta activity, were more involved under higher complexity, suggesting increased executive control. In contrast, beta and gamma activity predominated in temporo-central and parieto-occipital regions, supporting visuomotor and sensorimotor integration. Conclusions: EEG oscillatory dynamics during ecological GOPAs are selectively modulated by complexity condition and hierarchical task organization. Neural activity tracks functional demands of specific action phases rather than general arousal, highlighting dynamic coordination between executive and sensorimotor systems during complex manual behavior.

Introduction: Moral persuasion engages cognitive, emotional, and interpersonal regulation processes. While autonomic synchrony has been linked to cooperation, empathy and mutual influence, its role in moral persuasion remains underexplored. This study examines how physiological synchrony – measured via heart rate (HR), heart rate variability (HRV), and skin conductance level (SCL) – is associated with the subjective perception of opinion change within interacting pairs. Methods: Thirty young adults (15 unacquainted same-sex pairs, mean age = 23.6) participated in a structured, realistic moral persuasion task while their autonomic physiological signals were recorded. Dissimilarity indices (Euclidean distance) were computed for HR, HRV, and SCL within each pair. Dyads were grouped according to Self-evaluation of Opinion Change (SOC) concordance: higher SOC (both members reported relatively higher opinion change), mixed SOC (only one reporting opinion change), and lower SOC (both reporting no opinion change). Results: HRV dissimilarity significantly differed by SOC group: mixed SOC pairs showed significantly higher HRV dissimilarity than high SOC pairs, whereas other physiological signals did not show different profiles. Discussion: Preliminary findings suggest that convergence in cardiac autonomic activity during the persuasive exchange varies as a function of the concordance of perceived opinion change. This pattern may reflect that interpersonal dynamics contribute to shaping moral interactions and autonomic co-regulation, consistent with perspectives emphasizing the social and embodied nature of moral decision-making.

Group decision-making requires integrating different perspectives through persuasion, which involves unidirectional social influence, and negotiation, which is a reciprocal interaction based on cooperation and competition. While neuroscientific research has focused on identifying brain activations associated with these processes and their influencing factors, the impact of a prior persuasive dynamic on a subsequent negotiation task remains unexplored. This study examines whether engaging in a persuasive task, in which one individual has a role of social influence, affects neural activity during a subsequent negotiation. Using a hyperscanning paradigm with electroencephalography (EEG), frequency bands (delta, theta, alpha, beta and gamma) were analyzed in frontal, temporo-central and parieto-occipital regions in a sample of 26 participants. Results highlight distinct brain activation patterns between former persuaders and former receivers, with increased left-hemisphere delta activity and frontal theta and alpha activation in persuaders, while former receivers exhibited higher beta activity in the right parieto-occipital regions in the final stage of negotiation and higher gamma activity in right-lateralized regions. Overall, the study suggests that prior persuasive interactions shape subsequent negotiation at a neural level, influencing emotional, cognitive, and strategic engagement, with potential implications for understanding social dynamics in group interactions.

Recently, growing research has focused on analyzing the emotional impact of films, driven by the potential to enhance audience engagement, improve content recommendation systems, and deepen narrative understanding. Advances in artificial intelligence (AI) have opened new avenues for automated emotion recognition across various domains. This study explores the integration of AI, specifically ChatGPT, with human expertise to analyze complex emotional dynamics in cinema. Using a key scene from Sophie's Choice , we investigated ChatGPT's ability to recognize and interpret emotions through a multimodal approach combining visual, auditory, and textual inputs. Two human judges segmented 56 sequences based on characters’ facial expressions, and AI tools were employed for emotion analysis of facial recognition, dialogues, audio cues, and cinematographic elements, through an approach that simulated a real-world analytical workflow and the output of several libraries. Results highlight ChatGPT's ability in detecting nuanced emotional cues, such as micro-expressions and contextual elements, while acknowledging challenges in low-visibility conditions. This study demonstrates AI's capability to decode emotions and narrative dynamics and highlights the importance of multimodal frameworks in improving AI-driven emotion recognition. Future research should examine fully autonomous AI analyses and integrate subjective viewer experiences to bridge the gap between AI interpretations and human emotional responses.