Making Decisions with a Continuous Mind

Article excerpt

Neuroeconomics is a rapidly expanding field at the interfaces of the human sciences. The interdisciplinary nature of this field results in several challenges when attempts are made to solve puzzling questions in human decision making, such as why and how people discount future gains. We argue that an empirical approach based on dynamic systems theory (DST) could inspire and advance the neuroeconomic investigation of decisionmaking processes in three ways: by enriching the mental model, by extending the empirical tool set, and by facilitating interdisciplinary exchange. The present article addresses the challenges neuroeconomics faces by focusing on intertemporal choice. After a brief introduction of DST and related research, a DST-based conceptual model of decision making is developed and linked to underlying neural principles. On this basis, we outline the application of DST-informed empirical strategies to intertemporal choice. Finally, we discuss the general consequences of and possible objections to the proposed approach to research in intertemporal choice and the field of neuroeconomics.

Decision making, the selection of an action among several alternatives, is a central part of human behavior. Various disciplines, such as philosophy, economics, psychology, and neuroscience, have been concerned with the processes and problems involved in decision making. Over the last decade, these fields have grown together, as is apparent from the increasing number of studies in the emerging interdisciplinary field of neuroeconomics (e.g., Loewenstein, Rick, & Cohen, 2008; cf. Sanfey, Loewenstein, McClure, & Cohen, 2006). Neuroeconomics has enhanced both neuroscience and economics in terms of paradigms and methods. However, the interdisciplinary cooperation has resulted not only in an expansion of the scientific horizon, but also in an incorporation of the blind spots of the collaborating fields (see Glimcher, Dorris, & Bayer, 2005).

In this article, we propose to enrich the scientific investigation of human decision making by an empirical approach based on the concepts of dynamic systems theory (DST). Although this approach is rooted in mathematics and philosophy (e.g., Ashby, 1956, 1960; van Gelder & Port, 1995), the focus of this article is to offer empirical inspiration to researchers in the field of human decision making by a moderate DST-informed approach. DST has been applied successfully to different subfields of the above-mentioned disciplines (e.g., Juarrero, 1999; Kelso, 1995; Spivey, 2007; Thelen & Smith, 1996; but see Grush, 1997). It can contribute to neuroeconomics on two counts. At the theoretical level, DST can form a common conceptual ground for all of the participating fields and could enable researchers to define and investigate innovative research questions. At the methodological level, a DST-informed approach can enrich the design and analysis of empirical studies. Although the methods proposed here are not new per se, the combination of these methods within a common framework provides a new perspective on human decision making.

In the following, we will outline current approaches to decision making, focusing on the field of neuroeconomics and, in particular, on intertemporal choice. Subsequently, we will briefly review current DST-informed research and will introduce the concepts of the DST perspective, their neural basis, and a theoretical model of a dynamic decision system. Next, we will build on this new mental model and will elaborate on DST-informed empirical strategies applied to intertemporal choice. We then will examine the potential benefits of the DST-informed contribution to both intertemporal choice and neuroeconomics. Finally, we will discuss the limits of the approach presented and possible objections against a DST-informed approach to decision making and to cognition in general.

INTERDISCIPLINARY RESEARCH ON DECISION MAKING

Traditionally, the various disciplines involved in the study of decision making have taken different perspectives on their topic (see Glimcher et al. …

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