Social Neuroeconomics

Mechanistic Integration of the Neurosciences and the Social Sciences

Jens Harbecke, Carsten Herrmann-Pillath

• Publisher: Routledge
• Year: 2020
• ISBN:
  9781000097566
• Edition: 1
• Topic: Economía
• Subtopic: Teoría económica

Neuroeconomics has emerged as a paradigmatic field where neuroscience and the social sciences are integrated in one analytical and empirical approach. However, the different disciplines involved often only relate to each other via the shared object of research, and less through the constructing of precise models of integrative mechanisms. Social Neuroeconomics explores the potential of philosophical and methodological reflections in the neurosciences and the social sciences to inform those efforts at cross-disciplinary integration, with a special focus on recent contributions to mechanistic explanations. The collected essays are drawn from the fields of neuroscience, psychology, economics, sociology and philosophy, and examine the ways and methods of constructing unified conceptual frameworks that can guide empirical work and hypothesis building. This is demonstrated in a range of applications, particularly regarding finance and consumer behavior. The concept of the 'social brain' is also explored; a multilevel framework in which complex analytical categories such as emotions or socially mediated cognitive processes connect neuronal and social phenomena in specific mechanisms that generate behavior.This book addresses a wide audience across the various disciplines, reaching from the neurosciences to the social sciences and philosophy.

1
Introduction

Jens Harbecke and Carsten Herrmann-Pillath

Economic science increasingly incorporates insights from psychology and the neurosciences. These developments have already resulted in new approaches to the design of economic policies, inspired by the popular term of “nudging” consumers towards more rational behaviour (Thaler and Sunstein 2009). However, integrative theoretical approaches have also with considerable criticism.

Apart from ethical and practical considerations concerning “nudging” approaches to policy making, which have sometimes challenged a facts-oriented debate in Germany and other European countries (Bornemann and Smeddinck 2016; McFadden 2006; Schnellenbach 2012), the cross-disciplinary integration of results from economics, behavioural economics, and neuroeconomics into more unified theories and models has been charged with lacking a systematic and coherent methodological framework. Indeed, until today it is difficult to find accepted scientific standards and/or a shared heuristics for integrating results from the cognitive sciences and generally accepted models from economics, game theory, and decision theory. When do we consider the integration of such results and models successful? How do we deal with a lack of fit? In what sense are fragmented experimental results from the cognitive sciences relevant for economics, if the former were attained without integrating environmental and institutional factors into the experimental design? How do we expand further successfully integrated models in the sense of an overarching theory? And, going beyond the world of science, which models and theories should inform us when designing policy? Given the importance of these questions for the progress of science as well as policy making, the literature contains surprisingly few attempts to answer them in detail.

Perhaps as a reaction to this methodological obscurity, economists have sometimes doubted whether truly original insights can be reached from integrating research in economics and the cognitive sciences that goes beyond what can be achieved by studying market mechanisms that determine and constrain the behaviour of actors (Gul and Pesendorfer 2008; Harrison 2008; Rubinstein 2008; Bernheim 2009). Others, on the other hand, have emphasized the need for advancement in studying theory integration of economics and other scientific fields (e.g. Fehr and Rangel 2011).

The INSOSCI¹ project, which ran from 2016 until 2019, aimed at answering at least some of these questions by clarifying the methodological and philosophical foundations of the integration of economics and the neurosciences. It sought to achieve this goal by constructing a conceptual framework, which allows identifying interactive and mechanistic structures between neuronal, psychological, behavioural, and institutional phenomena. The project members expected such a kind of theoretical integration to have significant consequences for policy design (Camerer et al. 2005; Camerer 2013; Ross 2012).

Towards its final phase, the INSOSCI project held a symposium at Witten/Herdecke University in February 2019, which was attended by leading researchers working either in philosophy or in scientific projects at the intersection of economics, game theory, decision theory, and the neurosciences. During the meeting, the participants discussed potential titles for the methodological vision for theoretical integration that had already emerged from their interactions during the project, and especially during the symposium. Eventually, the notion of “Social Neuroeconomics” was chosen as a term that captures best the normative-methodological approach required for an adequate and successful integration of economics and the cognitive sciences.

The term has already been used occasionally in the literature, whilst a generally accepted meaning has not been settled. It is found in the specific context of neuroeconomic research on social preferences (Fehr and Camerer 2007). This research has produced the insight that social preferences may be rooted in mechanisms of choice that correspond to individual preferences in activating the same dopaminergic reward circuits. That means, acting with a social orientation produces rewards in the same way as, say, experiencing satisfaction from consuming positively valued goods. Hence, the motivation for using the term “Social Neuroeconomics” is that the analysis of social behaviour builds on the basic neuroeconomic model of choice.

It is remarkable that this view seems to reinstate Adam Smith’s notion of “fellow feeling”. In his Theory of Moral Sentiments, Smith distinguishes between “sympathy” and “fellow feeling”. Sympathy is very similar to the modern term “empathy”, especially in the cognitive meaning, and may be conceived as a capacity to generate social preferences: Sympathy enables us to take the position of others and thereby develop moral judgments that take into account their interests. Sympathy does not mean that we really “feel” like others: We can imagine the pain of others, but we do not feel that pain. However, we have “fellow-feelings”: That means, we enjoy the plain fact that we can “sympathize” with others. That means, if we sympathize with their pain, that goes along with a positive feeling. That seems very similar to the modern neuroeconomic analysis of rewards gained from socially oriented behaviour.

From the viewpoint of the members of the INSOSCI project and the participants of the symposium, this notion of Social Neuroeconomics is too narrow. The main reason for this assessment is expressed in the well-known criticism of neuroeconomics as focusing too narrowly on mechanisms of choice, thus following a similarly narrow definition of economics as a science of choice. Such an approach is dubbed the “neuroclassical” analysis in Camerer’s (2013) review of Glimcher’s Foundation of Neuroeconomic Analysis.

In the alternative view, neuroscience not only offers proofs of concept but crucially contributes to a rethinking of standard conceptions of economics. This has already happened in parts of behavioural economics and economic psychology. However, the field is complex and messy: Neuroeconomists often do not support the views of behavioural economists, as far as the standard model of choice is concerned. For instance, they often refute the “dual systems” approach that many behavioural economists maintain in opposition to the standard economic model (Kable and Glimcher 2007). At the same time, however, neuroscience, as including subdisciplines such as social neuroscience, may offer a third alternative transcending these methodological battles (Herrmann-Pillath 2019). This is indicated by the fact that today, often the term “decision neuroscience” has substituted for “neuroeconomics” (Bossaerts and Murawski 2015).

The concept of “Social Neuroeconomics” that emerged from the INSOSCI project differs fundamentally from the aforementioned narrow Smithian sense, although it can include the latter. At the same time, it transcends the specific dispute between neuroeconomists and behavioural economists. “Social Neuroeconomics” is rather intended to dub a general normative-methodological approach, which, on the one hand, considers the neurosciences as a device to confirm but also correct and reconceptualize economic models and the phenomena they describe; but which, on the other hand, emphasizes the social and economic context as indispensable for the identification, localization, and adequate understanding of specific brain mechanisms. The specific role of the latter typically remains opaque if not related to a social or economic environment. We suggest that the theoretical framework of such integration is that of a mechanistic explanation (Machamer et al. 2000; Craver and Darden 2001; Craver 2001, 2007; Bechtel and Richardson 1993; Glennan 1996) in the sense that, in a successful and adequate integrated explanation, neural phenomena are typically characterized as constituents (Craver 2007; Harbecke 2010, 2014) of economic phenomena in a specific context, together with other constituents. Such a two-way oriented integration is predicted to achieve better and more adequate theories of social and economic phenomena. In this sense, what “Social Neuroeconomics” characterizes in the view of the INSOSCI team members and the participants of the symposium is a general methodological approach that has multiple directions of explanation and that involves a hypothesis about the adequacy and success of certain kinds of theories.

One case in point is the analysis of emotions (which Camerer 2013 also emphasizes). Emotions do not play a prominent role in neuroeconomics as practised so far, especially in terms of foundational theoretical concepts. In our understanding of Social Neuroeconomics, we would assign emotions a central place in the theory, as it is done in social neuroscience. The theory of emotions often goes along with a modular view of the brain, rejecting “general purpose” rationality as a model for mechanisms, as in the theory of choice. Another important difference is the explicit recognition of the flexibility and context-dependence of neuronal mechanisms: This implies the analysis of media that connect the brain with its social environment, such as language. In both cases, satisfying the approach of Social Neuroeconomics does not mean merely that neuroeconomics, as it stands, is now applied to social phenomena, but that a genuine integration of social science theories and neuroscience is aimed at when understanding certain behavioural phenomena in the economy.

Some of the results, case studies, philosophical discussions, and theoretical proposals surrounding the INSOSCI project and its final symposium are presented in this book. In what follows, we will not summarize the book chapters, as all chapters have an abstract. Instead, we want to highlight the threads that connect the chapters and bring out how each chapter makes a specific kind of contribution to the overarching methodological vision and approach that we have named “Social Neuroeconomics”.

We start with a section that explores the implications of mechanistic philosophy of science for the integration project (for readers who are not familiar with the concept, we recommend the Stanford Encyclopedia entry by Craver and Tabery (2015)). Our initial idea was that the mechanistic or constitutive explanations approach would be powerful in designing integration strategies, because it is employed in both the philosophy of the neurosciences and the social sciences. There is a difference in outlook, as far as the philosophical dimension is concerned, since in reference to neurosciences, mechanistic approaches intend to describe and analyse the factual practice and standards of neuroscientific research, whereas with reference to the social sciences, mechanistic philosophy adopts a normative methodological stance. Yet, both concur in the basic idea that explanations do not follow the covering-law model of explanation but aim at identifying mechanisms that generate the phenomena in question. Here, a “mechanism” is a complex bounded structure that consists of levels of organization involving a set of constituent elements which interact causally and that underlie the phenomenon. Hence, explanation is concerned not with identifying laws as general regularities that govern the causal relationship between inputs and outputs of mechanisms, but with finding out how a specific mechanism works that connects the two on the highest level of analysis where this mechanism still remains a black box. Often, a major issue is to identify the mechanism in the first place and then dissect it analytically. This differs fundamentally from much of economic research that presents a model of a causal relationship which is then tested econometrically, and which does not necessarily claim to give a realistic account of the underlying mechanisms.

Mechanistic philosophy clearly describes the ways how neuroscientists work. Against this background, Chapter 2 by Caterina Marchionni and Jack Vromen asks whether neuroeconomics conforms to the standards that mechanistic philosophy and methodology have developed, especially with regard to the claims made by leading protagonists such as Padoa-Schioppa and Glimcher that neuroscience will result in a reductionist integration of economics and the neuro-sciences. They conclude that this project so far has failed to achieve its aims, as fundamental concepts such as “value” still differ fundamentally across the levels, i.e. neuronal, psychological, and economic, and the corresponding disciplines. The next chapter by Saúl Pérez-González continues with this mechanistic deconstruction of easy integration claims: He shows that the apparent convergence of mechanistic approaches in the neurosciences and the social sciences does not imply that we can straightforwardly identify and empirically specify certain mechanisms that factually integrate across levels. This is a principled issue, since the underlying concepts of mechanisms differ, for example, with respect to the conception of boundary. He concludes that one central challenge is to identify a third type of mechanisms that connect different mechanisms on the neuronal and the social level. In this spirit, the first section concludes with the chapter by Carsten Herrmann-Pillath which presents an external-ist conceptual framework for integration that centres on such a third type of mechanisms, semiotic mechanisms that encompass both internal, neuronal entities, and external entities, signs. This differs radically from standard reductionist references to mechanisms in which lower levels of mechanism would include only internal, i.e. neuronal entities. It is claimed that this framework adequately reflects how neuroscientists deal with complex phenomena such as empathy, especially with regard to the social contextualization of neuronal mechanisms.

Part 2 builds on this philosophical framing of Social Neuroeconomics in demonstrating how empirical research reflects mechanistic principles. The two chapters are intimately connected. Carolyn H. Declerck presents a paradigmatic case of Social Neuroeconomics research, the role of oxytocin in mediating cooperative behaviour and trust among agents. Trust, after all, is an important concept in understanding successful economic interaction and cooperation. Declerck analyses the new literature and own research on the “metafunctionality” of oxytocin which reveals that it can work both in a prosocial and an antisocial way, depending on how test persons perceive their environment, especially along the lines of in-group/out-group distinctions and degrees of perceived threats from others. In other words, the precise working of oxytocin-based mechanisms depends on contextualization via social cues. That means it is impossible to treat the hormone as an initial causal agent, but one must always envisage a complete neurophysiological and cognitive structure that produces behaviour as an outcome. To this end, we would have to include a theory that explains the emergence of such perceptions in the social environment. One cannot reduce the phenomenon of trust to the level of neuronal phenomena but needs a combination of neuronal and social mechanisms in order to achieve a full explanation. This is where the multi-directional character of what we call “Social Neuroeconomics” research becomes visible.

In the following chapter, Jens Harbecke focuses on the methods and the explanatory ideals applied in the research on oxytocin and prosocial behaviour. He interprets the research strategy of Declerck and others as aiming at the identification of parts of a “mechanistic” or “constitutive explanation” of economic decision making. Moreover, he outlines three different formal methods that have been offered as candidate heuristics for the establishment of mechanistic explanations. One the one hand, his aim is to evaluate the merits of these various methodologies, and on the other hand, he uses Declerck’s chapter as a case study that in detail investigates which methodology factually underlies her research. In doing this, he achieves two goals. One is to improve implicit methodological standards of empirical research, the other is proof of concept: Researchers in Social Neuroeconomics indeed pursue constituti...

Table of contents

• Cover
• Half Title
• Series Page
• Title Page
• Copyright Page
• Contents
• List of contributors
• 1 Introduction
• Part 1 Mechanistic frames for cross-disciplinary integration in social neuroeconomics
• Part 2 Mechanistic methodology and methods in social neuroeconomics
• Part 3 The social neuroeconomics of individual behaviour in context
• Part 4 Social neuroeconomics, institutions and interventions
• Index