A dual-fMRI investigation of the iterated Ultimatum Game reveals that reciprocal behaviour is associated with neural alignment

Dyadic interactions often involve a dynamic process of mutual reciprocity; to steer a series of exchanges towards a desired outcome, both interactants must adapt their own behaviour according to that of their interaction partner. Understanding the brain processes behind such bidirectional reciprocity is therefore central to social neuroscience, but this requires measurement of both individuals’ brains during realworld exchanges. We achieved this by performing functional magnetic resonance imaging (fMRI) on pairs of male individuals simultaneously while they interacted in a modifed iterated Ultimatum Game (iUG). In this modifcation, both players could express their intent and maximise their own monetary gain by reciprocating their partner’s behaviour – they could promote generosity through cooperation and/or discourage unfair play with retaliation. By developing a novel model of reciprocity adapted from behavioural economics, we then show that each player’s choices can be predicted accurately by estimating expected utility (EU) not only in terms of immediate payof, but also as a reaction to their opponent’s prior behaviour. Finally, for the frst time we reveal that brain signals implicated in social decision making are modulated by these estimates of EU, and become correlated more strongly between interacting players who reciprocate one another

Putting ourselves in another’s skin: using the plasticity of self-perception to enhance empathy and decrease prejudice

The self is one the most important concepts in social cognition and plays a crucial role in determining questions such as which social groups we view ourselves as belonging to and how we relate to others. In the past decade, the self has also become an important topic within cognitive neuroscience with an explosion in the number of studies seeking to understand how different aspects of the self are represented within the brain. In this paper, we first outline the recent research on the neurocognitive basis of the self and highlight a key distinction between two forms of self-representation. The first is the “bodily” self, which is thought to be the basis of subjective experience and is grounded in the processing of sensorimotor signals. The second is the “conceptual” self, which develops through our interactions of other and is formed of a rich network of associative and semantic information. We then investigate how both the bodily and conceptual self are related to social cognition with an emphasis on how self-representations are involved in the processing and creation of prejudice. We then highlight new research demonstrating that the bodily and conceptual self are both malleable and that this malleability can be harnessed in order to achieve a reduction in social prejudice. In particular, we will outline strong evidence that modulating people’s perceptions of the bodily self can lead to changes in attitudes at the conceptual level. We will highlight a series of studies demonstrating that social attitudes towards various social out-groups (e.g. racial groups) can lead to a reduction in prejudice towards that group. Finally, we seek to place these findings in a broader social context by considering how innovations in virtual reality technology can allow experiences of taking on another’s identity are likely to become both more commonplace and more convincing in the future and the various opportunities and risks associated with using such technology to reduce prejudice

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution-individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.Published versio

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic

Foraging Optimally in Social Neuroscience: Computations and Methodological considerations

Research in social neuroscience has increasingly begun to use the tools of computational neuroscience to better understand behaviour. Such approaches have proven fruitful for probing underlying neural mechanisms. However, little attention has been paid to how the structure of experimental tasks relates to real-world decisions, and the problems that brains have evolved to solve. To go significantly beyond current understanding, we must begin to use paradigms and mathematical models from behavioural ecology, which offer insights into the decisions animals must make successfully in order to survive. One highly influential theory—Marginal Value Theorem (MVT)—precisely characterises and provides an optimal solution to a vital foraging decision that most species must make: the patch-leaving problem. Animals must decide when to leave collecting rewards in a current patch (location) and travel somewhere else. We propose that many questions posed in social neuroscience can be approached as patch-leaving problems. A richer understanding of the neural mechanisms underlying social behaviour will be obtained by using MVT. In this ‘tools of the trade’ article, we outline the patch-leaving problem, the computations of MVT, and discuss is application to social neuroscience. Furthermore, we consider practical challenges and offer solutions for designing paradigms probing patch-leaving, both behaviourally and when using neuroimaging techniques

Motivational fatigue: a neurocognitive framework for the impact of effortful exertion on subsequent motivation

Fatigue - a feeling of exhaustion arising from exertion - is a significant barrier to successful behaviour and one of the most prominent symptoms in primary care. During extended behaviours, fatigue increases over time, leading to decrements in performance in both cognitively and physically demanding tasks. However, to date, theoretical accounts of fatigue have not fully characterised the neuroanatomical basis of cognitive and physical fatigue nor placed results within broader discussions of the functional properties of the systems implicated. Here, we review recent neurophysiological and neuroimaging research that has begun to identify the neural mechanisms underlying changes in behaviour occurring due to fatigue. Strikingly, this research has implicated systems in the brain, including the dorsal anterior cingulate cortex (dACC), anterior insula, and lateral prefrontal cortex, that in separate lines of research have been linked to motivating the exertion of effort, to persisting towards goals and to processing one's internal states. We put forward a neurocognitive framework for fatigue and its impact on motivation. Levels of fatigue arising from effortful behaviours impact on processing in systems that weigh up the costs and benefits of exerting effort. As a result, as levels of fatigue rise, the value of exerting effort into a task declines, leading to reductions in performance. This account provides a new framework for understanding the effects of fatigue during cognitively and physically demanding tasks as well as for understanding motivational impairments in health and disease

Motivational fatigue: a neurocognitive framework for the impact of effortful exertion on subsequent motivation

Fatigue - a feeling of exhaustion arising from exertion - is a significant barrier to successful behaviour and one of the most prominent symptoms in primary care. During extended behaviours, fatigue increases over time, leading to decrements in performance in both cognitively and physically demanding tasks. However, to date, theoretical accounts of fatigue have not fully characterised the neuroanatomical basis of cognitive and physical fatigue nor placed results within broader discussions of the functional properties of the systems implicated. Here, we review recent neurophysiological and neuroimaging research that has begun to identify the neural mechanisms underlying changes in behaviour occurring due to fatigue. Strikingly, this research has implicated systems in the brain, including the dorsal anterior cingulate cortex (dACC), anterior insula, and lateral prefrontal cortex, that in separate lines of research have been linked to motivating the exertion of effort, to persisting towards goals and to processing one's internal states. We put forward a neurocognitive framework for fatigue and its impact on motivation. Levels of fatigue arising from effortful behaviours impact on processing in systems that weigh up the costs and benefits of exerting effort. As a result, as levels of fatigue rise, the value of exerting effort into a task declines, leading to reductions in performance. This account provides a new framework for understanding the effects of fatigue during cognitively and physically demanding tasks as well as for understanding motivational impairments in health and disease