Hyperscanning EEG Paradigm Applied to Remote vs. Face-To-Face Learning in Managerial Contexts: Which Is Better?

Relational neuroscience: Insights from hyperscanning research

Humans are highly social, typically without this ability requiring noticeable efforts. Yet, such social fluency poses challenges both for the human brain to compute and for scientists to study. Over the last few decades, neuroscientific research of human sociality has witnessed a shift in focus from single-brain analysis to complex dynamics occurring across several brains, posing questions about what these dynamics mean and how they relate to multifaceted behavioural models. We propose the term 'Relational Neuroscience' to collate the interdisciplinary research field devoted to modelling the inter-brain dynamics subserving human connections, spanning from real-time joint experiences to long-term social bonds. Hyperscanning, i.e., simultaneously measuring brain activity from multiple individuals, has proven to be a highly promising technique to investigate inter-brain dynamics. Here, we discuss how hyperscanning can help investigate questions within the field of Relational Neuroscience, considering a variety of subfields, including cooperative interactions in dyads and groups, empathy, attachment and bonding, and developmental neuroscience. While presenting Relational Neuroscience in the light of hyperscanning, our discussion also takes into account behaviour, physiology and endocrinology to properly interpret inter-brain dynamics within social contexts. We consider the strengths but also the limitations and caveats of hyperscanning to answer questions about interacting people. The aim is to provide an integrative framework for future work to build better theories across a variety of contexts and research subfields to model human sociality.

Competition during verbal creative processes influences on ERS/ERD

Humans are social creatures, and many tasks in our daily lives are solved together. The two main forms of social interaction in problem solving could be defined as competition and cooperation. In our study, we compared the ERS/ERD when performing a creative task (Alternative Uses Test, AUT) and a control task ("naming the objects from the presented category") under competitive conditions in dyads (22 dyads, m-m, f-f, 18-23 years old) compared to the performance of tasks individually. The number of answers given by subjects under competitive conditions was significantly lower than during the execution of the tasks individually. The solving of the creative task in competition versus individual performance was accompanied by EEG synchronization (9-30 hz) clusters: 140-1220 ms and 900-1780 ms after stimulus presentation; 13.5-30 hz (1800-1980 ms), reflecting the creative thinking mode, and expected cognitive, emotional answers' assessment. The control task under competitive conditions was accompanied by pronounced synchronization of low frequencies in the frontal areas (2-7 hz, 0-1980 ms), due to a greater working memory load; synchronization clusters in broadband (10-30 hz, 100-320 ms, 400-860 ms) and in the beta EEG band (17-30 hz, 1140-1980 ms). The competitive conditions significantly modulated the brain activity underlying creative and non-creative cognitive task performance, and resulted in greater induced EEG synchronization.

From physical to digital: A theoretical-methodological primer on designing hyperscanning investigations to explore remote exchanges

As individuals increasingly engage in social interactions through digital mediums, understanding the neuroscientific underpinnings of such exchanges becomes a critical challenge and a valuable opportunity. In line with a second-person neuroscience approach, understanding the forms of interpersonal syntonisation that occur during digital interactions is pivotal for grasping the mechanisms underlying successful collaboration in virtual spaces. The hyperscanning paradigm, involving the simultaneous monitoring of the brains and bodies of multiple interacting individuals, seems to be a powerful tool for unravelling the neural correlates of interpersonal syntonisation in social exchanges. We posit that such approach can now open new windows on interacting brains' responses even to digitally-conveyed social cues, offering insights into how social information is processed in the absence of traditional face-to-face settings. Yet, such paradigm shift raises challenging methodological questions, which should be answered properly to conduct significant and informative hyperscanning investigations. Here, we provide an introduction to core methodological issues dedicated to novices approaching the design of hyperscanning investigations of remote exchanges in natural settings, focusing on the selection of neuroscientific devices, synchronization of data streams, and data analysis approaches. Finally, a methodological checklist for devising robust hyperscanning studies on digital interactions is presented.

EEG Correlates of Moral Decision-Making: Effect of Choices and Offers Types

BACKGROUND

Moral decision-making consists of a complex process requiring individuals to evaluate potential consequences of personal and social decisions, including applied organizational contexts.

METHODS

This research aims to investigate the behavioral (offer responses and reaction times, RTs) and electrophysiological (EEG) correlates underlying moral decision-making during three different choice conditions (professional fit, company fit, and social fit) and offers (fair, unfair, and neutral).

RESULTS

An increase of delta and theta frontal activity (related to emotional behavior and processes) and beta frontal and central activity (linked to cognitive and attentional processes) was found. A left beta, delta, and theta frontal activity was observed for fair offers in professional fit conditions, while increased right frontal delta and theta activity was found in response to unfair offers in company fit conditions. Also, an increase of left delta and theta parietal activity for unfair offers in social fit condition was detected. Finally, higher accepted responses were found for fair and neutral offers in professional and social fit conditions, with increased RTs for unfair offers suggesting decisions' cognitive load and complexity.

CONCLUSIONS

By revealing a greater involvement of left and right frontal areas in decision-making processes based on choices and offers, personal interest evaluations and emotional values, and of parietal areas in more prosocial and altruistic moral behavior, current findings provide information about the neural and behavioral correlates underlying company moral behavior.

Sensorimotor Simulation's Influence on Stress: EEG and Autonomic Responses in Digital Interviews

This study explored the role of sensorimotor simulation in modulating the stress response in individuals exposed to stressful digital simulated interviews. Participants were assigned to two different versions of a Digital Social Stress Test: a simulated version with a dynamic-realistic examining committee (Dyn-DSST) and a version with a static examining committee (Stat-DSST). During interview preparation, behavioral indices reflecting stress regulation and resistance, response times, and electroencephalographic (EEG) and autonomic indices were collected. Higher regulation scores were found for the Stat-DSST group compared to the Dyn-DSST group, probably induced by the presence of limited external sensory input in time and space, perceived as less stressful. The EEG results revealed a distinct contribution of the low- and high-frequency bands for both groups. Dyn-DSST required greater cognitive regulation effort due to the presence of a continuous flow of information, which can enhance sensory and motor activation in the brain. The SCR increased in the Dyn-DSST group compared to the Stat-DSST group, reflecting greater emotional involvement in the Dyn-DSST group and reduced sensory stimulation in the static version. In conclusion, the results suggest that sensorimotor simulation impacts the stress response differently in dynamic interviews compared to static ones, with distinct profiles based on behavioral, EEG, and autonomic measures.