Do Political and Economic Choices Rely on Common Neural Substrates? A Systematic Review of the Emerging Neuropolitics Literature

Health involvement modulates physician preference in the brain during online health consultation

In traditional offline health-seeking behavior, patients consistently exhibit a preference for similar types of physicians due to limited access to physicians' information. Nevertheless, with the advent of online health consultation platforms offering comprehensive physicians' information for patients, raises the question: do patients continue to exhibit uniform preference for physicians? To address this issue, we first employed a behavioral experiment to discern patients' preferences for different types of physicians' information under different health involvement, and then conducted a functional magnetic resonance imaging (fMRI) experiment to furnish neural/physiological evidence. The results showed that health involvement modulates patients' preferences, when health involvement was low, patients had diverse preferences for physicians, that is, different types of physicians' information could individually impact patients' choice and could serve as substitutes for each other. When health involvement was high, patients' preference for physicians were uniform, highlighting that the collective influence of different types of physicians' information on patients' choice behavior. From the neural level, an explanation for the results was that the ventromedial prefrontal cortex (VMPFC) and ventral striatum (VS) brain regions, two key brain regions reflecting individual cognitive resource allocation, had different activation levels under different health involvement, indicating that patients allocated different cognitive resources.

Unraveling neural pathways of political engagement: bridging neuromarketing and political science for understanding voter behavior and political leader perception

Introduction

Political neuromarketing is an emerging interdisciplinary field integrating marketing, neuroscience, and psychology to decipher voter behavior and political leader perception. This interdisciplinary field offers novel techniques to understand complex phenomena such as voter engagement, political leadership, and party branding.

Methods

This study aims to understand the neural activation patterns of voters when they are exposed to political leaders using functional near-infrared spectroscopy (fNIRS) and machine learning methods. We recruited participants and recorded their brain activity using fNIRS when they were exposed to images of different political leaders.

Results

This neuroimaging method (fNIRS) reveals brain regions central to brand perception, including the dorsolateral prefrontal cortex (dlPFC), the dorsomedial prefrontal cortex (dmPFC), and the ventromedial prefrontal cortex (vmPFC). Machine learning methods were used to predict the participants' perceptions of leaders based on their brain activity. The study has identified the brain regions that are involved in processing political stimuli and making judgments about political leaders. Within this study, the best-performing machine learning model, LightGBM, achieved a highest accuracy score of 0.78, underscoring its efficacy in predicting voters' perceptions of political leaders based on the brain activity of the former.

Discussion

The findings from this study provide new insights into the neural basis of political decision-making and the development of effective political marketing campaigns while bridging neuromarketing, political science, and machine learning, in turn enabling predictive insights into voter preferences and behavior.

Functional connectivity signatures of political ideology

Emerging research has begun investigating the neural underpinnings of the biological and psychological differences that drive political ideology, attitudes, and actions. Here, we explore the neurological roots of politics through conducting a large sample, whole-brain analysis of functional connectivity (FC) across common fMRI tasks. Using convolutional neural networks, we develop predictive models of ideology using FC from fMRI scans for nine standard task-based settings in a novel cohort of healthy adults (n = 174, age range: 18 to 40, mean = 21.43) from the Ohio State University Wellbeing Project. Our analyses suggest that liberals and conservatives have noticeable and discriminative differences in FC that can be identified with high accuracy using contemporary artificial intelligence methods and that such analyses complement contemporary models relying on socio-economic and survey-based responses. FC signatures from retrieval, empathy, and monetary reward tasks are identified as important and powerful predictors of conservatism, and activations of the amygdala, inferior frontal gyrus, and hippocampus are most strongly associated with political affiliation. Although the direction of causality is unclear, this study suggests that the biological and neurological roots of political behavior run much deeper than previously thought.

Decision neuroscience and neuroeconomics: Recent progress and ongoing challenges

In the past decade, decision neuroscience and neuroeconomics have developed many new insights in the study of decision making. This review provides an overarching update on how the field has advanced in this time period. Although our initial review a decade ago outlined several theoretical, conceptual, methodological, empirical, and practical challenges, there has only been limited progress in resolving these challenges. We summarize significant trends in decision neuroscience through the lens of the challenges outlined for the field and review examples where the field has had significant, direct, and applicable impacts across economics and psychology. First, we review progress on topics including reward learning, explore-exploit decisions, risk and ambiguity, intertemporal choice, and valuation. Next, we assess the impacts of emotion, social rewards, and social context on decision making. Then, we follow up with how individual differences impact choices and new exciting developments in the prediction and neuroforecasting of future decisions. Finally, we consider how trends in decision-neuroscience research reflect progress toward resolving past challenges, discuss new and exciting applications of recent research, and identify new challenges for the field. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Emotion and Motivation.

The Dark Side of Morality - Neural Mechanisms Underpinning Moral Convictions and Support for Violence

People are motivated by shared social values that, when held with moral conviction, can serve as compelling mandates capable of facilitating support for ideological violence. The current study examined this dark side of morality by identifying specific cognitive and neural mechanisms associated with beliefs about the appropriateness of sociopolitical violence, and determining the extent to which the engagement of these mechanisms was predicted by moral convictions. Participants reported their moral convictions about a variety of sociopolitical issues prior to undergoing functional MRI scanning. During scanning, they were asked to evaluate the appropriateness of violent protests that were ostensibly congruent or incongruent with their views about sociopolitical issues. Complementary univariate and multivariate analytical strategies comparing neural responses to congruent and incongruent violence identified neural mechanisms implicated in processing salience and in the encoding of subjective value. As predicted, neuro-hemodynamic response was modulated parametrically by individuals' beliefs about the appropriateness of congruent relative to incongruent sociopolitical violence in ventromedial prefrontal cortex, and by moral conviction in ventral striatum. Overall moral conviction was predicted by neural response to congruent relative to incongruent violence in amygdala. Together, these findings indicate that moral conviction about sociopolitical issues serves to increase their subjective value, overriding natural aversion to interpersonal harm.

How Does Motivation Modulate the Operation of the Mentalizing Network in Person Evaluation?

The mentalizing network is theorized to play a central role in making sense of people (compared with nonsocial targets), but is its involvement affected when we make sense of people in a nondispassionate manner (e.g., favoritism toward others on the basis of group membership)? First, mixed findings and small samples have prevented strong conclusions about whether intergroup evaluation increases or decreases activation regions associated with the mentalizing network. Second, little is known about the psychological mechanism underlying mentalizing network activation shaped by ingroup versus outgroup evaluations. Psychological models suggest two hypotheses that can be challenging to disentangle with self-report: Ingroup trait evaluations may benefit from a priori expectations and/or preferential evidence accumulation. Therefore, the current study (n = 50) drew on a combination of drift diffusion modeling and fMRI to examine how group membership affects the engagement of the mentalizing network for trait evaluation and whether group-differentiated activation is associated with a priori expectations and/or preferential evidence accumulation. Outgroup trait evaluations engaged dorsomedial pFC activation, whereas ingroup trait evaluations engaged ventromedial pFC activation as well as other regions associated with mentalizing such as precuneus, posterior cingulate cortex, and right TPJ. Furthermore, the ventromedial pFC and posterior cingulate cortex activation was associated with differential expectations applied to ingroup trait evaluation. The current findings demonstrate the importance of combining motivational factors, computational modeling, and fMRI to deepen our understanding of the neural basis of person evaluation.

Neuropolitics: Twenty years later

Neuropolitics is the intersection of neuroscience and political science, and it has the interdisciplinary goal of transforming both disciplines. This article reviews the past 20 years of work in the field, identifying its roots, some overarching themes-reactions to political attitudinal questions and candidates faces, identification of political ideology based on brain structure or reactivity to nonpolitical stimuli, and racial attitudes-and obstacles to its progress. I then explore the methodological and analytical advances that point the way forward for the future of neuropolitics. Although the field has been slow to develop compared with neurolaw and neuroeconomics, innovations look ripe for dramatically improving our ability to model political behaviors and attitudes in individuals and predict political choices in mass publics. The coming advancements, however, pose risks to our current norms of democratic deliberation, and academics need to anticipate and mitigate these risks.

Issues or Identity? Cognitive Foundations of Voter Choice

Voter choice is one of the most important problems in political science. The most common models assume that voting is a rational choice based on policy positions (e.g., key issues) and nonpolicy information (e.g., social identity, personality). Though such models explain macroscopic features of elections, they also reveal important anomalies that have been resistant to explanation. We argue for a new approach that builds upon recent research in cognitive science and neuroscience; specifically, we contend that policy positions and social identities do not combine in merely an additive manner, but compete to determine voter preferences. This model not only explains several key anomalies in voter choice, but also suggests new directions for research in both political science and cognitive science.

The Neuroscience of Human Decision-Making Through the Lens of Learning and Memory

We are called upon to make decisions, large and small, many times a day. Whether in the voting booth, the stock exchange, or the cafeteria line, we identify potential options, estimate and compare their subjective values, and make a choice. Decision-making has only recently become a focus for cognitive neuroscience. The last two decades have seen rapid progress in our understanding of the brain basis of at least some aspects of this rather complex aspect of cognition. This work has provided fresh perspectives on poorly understood brain regions, such as orbitofrontal cortex and ventral striatum. It has led to interesting interdisciplinary exchanges with diverse fields, notably economics, but also ecology and political science, among others. The novel perspectives arising from these exchanges have begun to be related to better understood aspects of cognition. In particular, it is increasingly clear that decision-making is tightly interlinked with learning and memory. Key early insights in decision neuroscience came from what were essentially reinforcement learning tasks. Recent work has made similar links to aspects of declarative memory. Indeed, decision-making can be seen as the link between memory of the past and future actions. This chapter reviews selected topics in decision neuroscience, with a particular focus on the links to learning and memory, and a particular emphasis on regions within prefrontal cortex.