Morality and management: an oxymoron? fNIRS and neuromanagement perspective explain us why things are not like this

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.

A brief real-time fNIRS-informed neurofeedback training of the prefrontal cortex changes brain activity and connectivity during subsequent working memory challenge

Working memory (WM) represents a building-block of higher cognitive functions and a wide range of mental disorders are associated with WM impairments. Initial studies have shown that several sessions of functional near-infrared spectroscopy (fNIRS) informed real-time neurofeedback (NF) allow healthy individuals to volitionally increase activity in the dorsolateral prefrontal cortex (DLPFC), a region critically involved in WM. For the translation to therapeutic or neuroenhancement applications, however, it is critical to assess whether fNIRS-NF success transfers into neural and behavioral WM enhancement in the absence of feedback. We therefore combined single-session fNIRS-NF of the left DLPFC with a randomized sham-controlled design (N = 62 participants) and a subsequent WM challenge with concomitant functional MRI. Over four runs of fNIRS-NF, the left DLPFC NF training group demonstrated enhanced neural activity in this region, reflecting successful acquisition of neural self-regulation. During the subsequent WM challenge, we observed no evidence for performance differences between the training and the sham group. Importantly, however, examination of the fMRI data revealed that - compared to the sham group - the training group exhibited significantly increased regional activity in the bilateral DLPFC and decreased left DLPFC - left anterior insula functional connectivity during the WM challenge. Exploratory analyses revealed a negative association between DLPFC activity and WM reaction times in the NF group. Together, these findings indicate that healthy individuals can learn to volitionally increase left DLPFC activity in a single training session and that the training success translates into WM-related neural activation and connectivity changes in the absence of feedback. This renders fNIRS-NF as a promising and scalable WM intervention approach that could be applied to various mental disorders.

"We will be in touch". A neuroscientific assessment of remote vs. face-to-face job interviews via EEG hyperscanning

In the last decades, improving remote communications in companies has been a compelling issue. With the outspread of SARS-CoV-2 pandemic, this phenomenon has undergone an acceleration. Despite this, little to no research, considering neurocognitive and emotional systems, was conducted on job interview, a critical organizational phase which significantly contributes to a company long-term success.In this study, we aimed at exploring the emotional and cognitive processes related to different phases of a job interview (introductory, attitudinal, technical and conclusion), when considering two conditions: face-to-face and remote, by simultaneously gathering EEG (frequency bands: alpha, beta, delta, and theta) and autonomic data (skin-conductance-level, SCL, skin-conductance-response, SCR, and heart rate, HR) in both candidates and recruiters. Data highlighted a generalized alpha desynchronization during the job interview interaction. Recruiters showed increased frontal theta activity, which is connected to socio-emotional situations and emotional processing. In addition, results showed how face-to-face condition is related to increased SCL and theta power in the central-brain area, associated with learning processes, via the mid-brain dopamine system and the anterior cingulate cortex. Furthermore, we found higher HR in the candidates. Present results call to re-examine the impact of information-technology in the organization, opening to translational opportunities.

Judgment and Embodied Cognition of Lawyers. Moral Decision-Making and Interoceptive Physiology in the Legal Field

Past research showed that the ability to focus on one’s internal states (e.g., interoceptive ability) positively correlates with the self-regulation of behavior in situations that are accompanied by somatic and/or physiological changes, such as emotions, physical workload, and decision-making. The analysis of moral oriented decision-making can be the first step for better understanding the legal reasoning carried on by the main players in the field, as lawyers are. For this reason, this study investigated the influence of the decision context and interoceptive manipulation on the moral decision-making process in the legal field gathering the responses of two groups of lawyers. A total of 20 lawyers were randomly divided into an experimental group (EXP), which was explicitly required to focus the attention on its interoceptive correlates, and a control group (CON), which only received the general instruction to perform the task. Both groups underwent a modified version of the Ultimatum Game (UG), where are presented three different moral conditions (professional, company, and social) and three different offers (fair, unfair, and equal). Results highlighted a significant increase of Acceptance Rate (AR) in those offers that should be considered more equal than fair or unfair ones, associated with a general increase of Reaction Times (RTs) in the equal offers. Furthermore, the interoceptive manipulation oriented the Lawyers toward a more self-centered decision. This study shows how individual, situational, contextual, and interoceptive factors may influence the moral decision-making of lawyers. Future research in the so-called Neurolaw field is needed to replicate and expand current findings.

Job Assessment Through Bioelectrical Measures: A Neuromanagement Perspective

During recruitment, human resource departments face two challenges: finding the right people for the job and attracting talent. Therefore, the hiring process requires both the ability to communicate a good company brand image and to understand the characteristics and potential of candidates. In this study, we used a neuroscientific approach to measure the experience of candidates during a job interview. The experiment involved 30 participants that individually took part in a job interview lasting 40 min. During the experiment, their engagement and stress levels were measured in real-time with skin conductance and electroencephalographic (EEG) data. From the results, we identified both the most stressful phases (the second and the fourth parts, relating to the explanation of the job and remuneration) and the most engaging phases (the first and the third phases, relating to the presentation of the company and the explanation of the career process) of the interview, suggesting implications for the assessment process. This study is a contribution to the field of neuromanagement, as a neuroscientific approach was applied to management issues in light of work and organizational psychology.

Predicting Student Performance Using Machine Learning in fNIRS Data

Increasing student involvement in classes has always been a challenge for teachers and school managers. In online learning, some interactivity mechanisms like quizzes are increasingly used to engage students during classes and tasks. However, there is a high demand for tools that evaluate the efficiency of these mechanisms. In order to distinguish between high and low levels of engagement in tasks, it is possible to monitor brain activity through functional near-infrared spectroscopy (fNIRS). The main advantages of this technique are portability, low cost, and a comfortable way for students to concentrate and perform their tasks. This setup provides more natural conditions for the experiments if compared to the other acquisition tools. In this study, we investigated levels of task involvement through the identification of correct and wrong answers of typical quizzes used in virtual environments. We collected data from the prefrontal cortex region (PFC) of 18 students while watching a video lecture. This data was modeled with supervised learning algorithms. We used random forests and penalized logistic regression to classify correct answers as a function of oxyhemoglobin and deoxyhemoglobin concentration. These models identify which regions best predict student performance. The random forest and penalized logistic regression (GLMNET with LASSO) obtained, respectively, 0.67 and 0.65 area of the ROC curve. Both models indicate that channels F4-F6 and AF3-AFz are the most relevant for the prediction. The statistical significance of these models was confirmed through cross-validation (leave-one-subject-out) and a permutation test. This methodology can be useful to better understand the teaching and learning processes in a video lecture and also provide improvements in the methodologies used in order to better adapt the presentation content.

Functional Effects of Bilateral Dorsolateral Prefrontal Cortex Modulation During Sequential Decision-Making: A Functional Near-Infrared Spectroscopy Study With Offline Transcranial Direct Current Stimulation

The ability to learn sequential contingencies of actions for predicting future outcomes is indispensable for flexible behavior in many daily decision-making contexts. It remains open whether such ability may be enhanced by transcranial direct current stimulation (tDCS). The present study combined tDCS with functional near-infrared spectroscopy (fNIRS) to investigate potential tDCS-induced effects on sequential decision-making and the neural mechanisms underlying such modulations. Offline tDCS and sham stimulation were applied over the left and right dorsolateral prefrontal cortex (dlPFC) in young male adults (N = 29, mean age = 23.4 years, SD = 3.2) in a double-blind between-subject design using a three-state Markov decision task. The results showed (i) an enhanced dlPFC hemodynamic response during the acquisition of sequential state transitions that is consistent with the findings from a previous functional magnetic resonance imaging (fMRI) study; (ii) a tDCS-induced increase of the hemodynamic response in the dlPFC, but without accompanying performance-enhancing effects at the behavioral level; and (iii) a greater tDCS-induced upregulation of hemodynamic responses in the delayed reward condition that seems to be associated with faster decision speed. Taken together, these findings provide empirical evidence for fNIRS as a suitable method for investigating hemodynamic correlates of sequential decision-making as well as functional brain correlates underlying tDCS-induced modulation. Future research with larger sample sizes for carrying out subgroup analysis is necessary in order to decipher interindividual differences in tDCS-induced effects on sequential decision-making process at the behavioral and brain levels.