Cultural Neuroeconomics of Intertemporal Choice

According to theories of cultural neuroscience, Westerners and Easterners may have distinct styles of cognition (e.g., different allocation of attention). Previous research has shown that Westerners and Easterners tend to utilize analytical and holistic cognitive styles, respectively. On the other hand, little is known regarding the cultural differences in neuroeconomic behavior. For instance, economic decisions may be affected by cultural differences in neurocomputational processing underlying attention; however, this area of neuroeconomics has been largely understudied. In the present paper, we attempt to bridge this gap by considering the links between the theory of cultural neuroscience and neuroeconomic theory\ud of the role of attention in intertemporal choice. We predict that (i) Westerners are more impulsive and inconsistent in intertemporal choice in comparison to Easterners, and (ii) Westerners more steeply discount delayed monetary losses than Easterners. We examine these predictions by utilizing a novel temporal discounting model based on Tsallis' statistics (i.e. a q-exponential model). Our preliminary analysis of temporal discounting of gains and losses by Americans and Japanese confirmed the predictions from the cultural neuroeconomic theory. Future study directions, employing computational modeling via neural networks, are briefly outlined and discussed

Neuroeconomics of suicide.

Suicidal behavior is a leading cause of injury and death worldwide. Suicide has been associated with psychiatric illnesses such as depression and schizophrenia, as well as economic uncertainty, and social/cultural factors. This study proposes a neuroeconomic framework of suicide. Neuroeconomic parameters (e.g., risk-attitude, probability weighting, time discounting in intertemporal choice, and loss aversion) are predicted to be related to suicidal behavior. Neurobiological and neuroendocrinological substrates such as serotonin, dopamine, cortisol (HPA axis), nitric oxide, serum cholesterol, epinephrine, norepinephrine, gonadal hormones (e.g., estradiol and progesterone), dehydroepiandrosterone (DHEA) in brain regions such as the orbitofrontal/dorsolateral prefrontal cortex and limbic regions (e.g., the amygdala) may supposedly be related to the neuroeconomic parameters modulating the risk of suicide. The present framework puts foundations for ―molecular neuroeconomics‖ of decision-making processes underlying suicidal behavior

Neuroeconomics: How Neuroscience Can Inform Economics

Neuroeconomics uses knowledge about brain mechanisms to inform economic analysis, and roots economics in biology. It opens up the "black box" of the brain, much as organizational economics adds detail to the theory of the firm. Neuroscientists use many tools— including brain imaging, behavior of patients with localized brain lesions, animal behavior, and recording single neuron activity. The key insight for economics is that the brain is composed of multiple systems which interact. Controlled systems ("executive function") interrupt automatic ones. Emotions and cognition both guide decisions. Just as prices and allocations emerge from the interaction of two processes—supply and demand— individual decisions can be modeled as the result of two (or more) processes interacting. Indeed, "dual-process" models of this sort are better rooted in neuroscientific fact, and more empirically accurate, than single-process models (such as utility-maximization). We discuss how brain evidence complicates standard assumptions about basic preference, to include homeostasis and other kinds of state-dependence. We also discuss applications to intertemporal choice, risk and decision making, and game theory. Intertemporal choice appears to be domain-specific and heavily influenced by emotion. The simplified ß-d of quasi-hyperbolic discounting is supported by activation in distinct regions of limbic and cortical systems. In risky decision, imaging data tentatively support the idea that gains and losses are coded separately, and that ambiguity is distinct from risk, because it activates fear and discomfort regions. (Ironically, lesion patients who do not receive fear signals in prefrontal cortex are "rationally" neutral toward ambiguity.) Game theory studies show the effect of brain regions implicated in "theory of mind", correlates of strategic skill, and effects of hormones and other biological variables. Finally, economics can contribute to neuroscience because simple rational-choice models are useful for understanding highly-evolved behavior like motor actions that earn rewards, and Bayesian integration of sensorimotor information

The Methodologies of Neuroeconomics

We critically review the methodological practices of two research programs which are jointly called 'neuroeconomics'. We defend the first of these, termed 'neurocellular economics' (NE) by Ross (2008), from an attack on its relevance by Gul and Pesendorfer (2008) (GP). This attack arbitrarily singles out some but not all processing variables as unimportant to economics, is insensitive to the realities of empirical theory testing, and ignores the central importance to economics of 'ecological rationality' (Smith 2007). GP ironically share this last attitude with advocates of 'behavioral economics in the scanner' (BES), the other, and better known, branch of neuroeconomics. We consider grounds for skepticism about the accomplishments of this research program to date, based on its methodological individualism, its ad hoc econometrics, its tolerance for invalid reverse inference, and its inattention to the difficulties involved in extracting temporally lagged data if people's anticipation of reward causes pre-emptive blood flow.

Is neuroeconomics doomed by the reverse inference fallacy?

Neuroeconomic studies are liable to fall into the reverse inference fallacy, a form of affirmation of the consequent. More generally neuroeconomics relies on two problematic steps, namely the inference from brain activities to the engagement of cognitive processes in experimental tasks, and the presupposition that such inferred cognitive processes are relevant to economic theorizing. The first step only constitutes the reverse inference fallacy proper and ways to correct it include a better sense of the neural response selectivity of the targeted brain areas and a better definition of relevant cognitive ontologies for neuroeconomics. This second way also allows increased coherence between the cognitive processes actually involved in neuroeconomics experiments and the theoretical constructs of economics. We suggest means of increasing neural response selectivity in neuroeconomic experimental paradigms. We also discuss how the choice of cognitive ontologies can both avoid implicit reductionist strategies (from economic constructs to neural patterns) and irrelevance, as cognitive processes engaged in experimental tasks may lack immediate bearing on the study of economic behavior. With these joint improvements neuroeconomics can be a progressive science

Can Inform Economics

Who knows what I want to do? Who knows what anyone wants to do? How can you be sure about something like that? Isn’t it all a question of brain chemistry, signals going back and forth, electrical energy in the cortex? How do you know whether something is really what you want to do or just some kind of nerve impulse in the brain. Some minor little activity takes place somewhere in this unimportant place in one of the brain hemispheres and suddenly I want to go to Montana or I don’t want to go to Montana. (White Noise, Don DeLillo) 1

Implications of Neuroscience Developments in Understanding Human Behavior for Teaching Agricultural Economics/Agribusiness

neuroscience, behavioral economics, teaching, Agribusiness, Agricultural Finance, Institutional and Behavioral Economics, Risk and Uncertainty, Teaching/Communication/Extension/Profession,

A framework for studying the neurobiology of value-based decision making

Neuroeconomics is the study of the neurobiological and computational basis of value-based decision making. Its goal is to provide a biologically based account of human behaviour that can be applied in both the natural and the social sciences. This Review proposes a framework to investigate different aspects of the neurobiology of decision making. The framework allows us to bring together recent findings in the field, highlight some of the most important outstanding problems, define a common lexicon that bridges the different disciplines that inform neuroeconomics, and point the way to future applications

Dissociating the Role of the Orbitofrontal Cortex and the Striatum in the Computation of Goal Values and Prediction Errors

To make sound economic decisions, the brain needs to compute several different value-related signals. These include goal values that measure the predicted reward that results from the outcome generated by each of the actions under consideration, decision values that measure the net value of taking the different actions, and prediction errors that measure deviations from individuals' previous reward expectations. We used functional magnetic resonance imaging and a novel decision-making paradigm to dissociate the neural basis of these three computations. Our results show that they are supported by different neural substrates: goal values are correlated with activity in the medial orbitofrontal cortex, decision values are correlated with activity in the central orbitofrontal cortex, and prediction errors are correlated with activity in the ventral striatum