Neuroeconomics

Written by Simone Le Roux

June 2, 2017

Introduction

Neuroeconomics is the study of the neural mechanisms and computational basis of value-based decision-making and their economic significance (Figure 1). Value-based decision-making occurs whenever an organism makes a choice from several alternatives based on the subjective value that it places on them 1 2. Examples include basic animal behaviours such as foraging, and complicated human decisions such as trading in the stock-market.

FIGURE 1. BASIC COMPUTATIONS INVOLVED IN MAKING A CHOICE 3.

This interdisciplinary research field integrates marketing, economics, psychology, neuroscience, and cognitive science and consists of:

  • Decision making
  • The influence of advertising and brands
  • Influence of emotion, biases, etc.
  • Influence of other people
  • Segments – elderly, children, males, females, etc.
  • Addictive consumption

To explain the internal processes governing the occurrences in the economic world, neuroeconomics is an emerging interdisciplinary field attempting to merge psychology and economic theory. Simply put, the biological basis of behavioural economics – how and why people make judgements and decisions with economic consequences in terms of simple cerebral biology.

While neuroeconomics aims to explain how the brain chooses (i.e., often with respect to resource allocation), different disciplines have historically approached this question from different vantage points. Three prototypical views can be identified- those of neuroscientists, psychologists, economists and computer scientists.

  • Neuroscientists typically start from neurons.
  • Psychologists typically start from experiential phenomena related to affect, cognition, and behaviour.
  • Economists typically start from axioms or mathematically consistent specifications.
  • Computer scientists provide computational models of machine learning and decision-making

To investigate how the brain “chooses”, researchers have typically adopted one of two strategies:

  1. “Correlational” strategy seeks to identify neural correlates of choice (consistent with behavioural neuroscience, behavioural psychological, and revealed preference economic approaches).
  2. “Process” strategy seeks to determine how different neural components causally influence future choice (consistent with cognitive neuroscience, cognitive psychology, and prospect-theoretic economic approaches).

But why should we be interested? Neuroeconomics attempts to bridge the gap between input (information) and output, (decision) by analysing the chemicals and structures that provide the biological basis for individuality in processing and decision-making. Neuroeconomics assumes that the neurotransmission in cerebral areas that are responsible for higher order information processing and consciousness (such as the prefrontal cortex) result in the socioemotional basis for most of our decisions 4.

Brain imaging techniques and genetic screening in consumers and the aging population has given us greater insight into the likelihood of decisions, judgment and risk taking, allowing those utilizing the information the potential to cash in on their carefully biologically tailored advertisements, behavioural change interventions, and so on. Does this mean in years to come scientists will be able to access unconscious desires and preferences for profit?

Ethical considerations

Whilst the ethical implications of feeding the consumer’s biological process for preference is questionable, using these reductionist techniques to better inform consumer choice is not necessarily beneficial. Studies have shown that whilst initial choice in blind tasting, for example, is unconscious, contrary decisions are made based upon branding, cultural preference and so on 5 6.

Moreover, to an extent, neuroeconomic study still relies on the same economic principles of assumption – this being that human brains, unfortunately for scientists, do not work in uniformity, and rather, decisions are made irrationally, regardless of the unconscious biology informing us otherwise.

More specifically within the field of neuroeconomics, neuromarketing seems to provide the most controversy in terms of its future applications 7. Currently, the field aims to utilize the findings of neurological study regarding consumer choice, and aims to appeal to certain unconscious mechanisms, which govern decision boosting purchase and profit – in theory. Previous research has already attempted to determine the chemical basis of ‘trust’ (well established as oxytocin 8 9 10) as a powerful component in judgement and decision in terms of brand trust and familiarity.

Cognitive Neuroscience

Like economics, the history of the neuroscientific study of behaviour also reflects an interaction between two approaches – in this case, a neurological approach and a physiological approach. In the standard neurological approach of the last century, human patients or experimental animals with brain lesions were studied in a range of behavioural tasks. The behavioural deficits of the subjects were then correlated with their neurological injuries and the correlation used to infer function. The classic example of this is probably the work of the British neurologist David Ferrier (1878), who demonstrated that destruction of the precentral gyrus of the cortex led to quite precise deficits in movement generation 411.

Human Brain Imaging of Reward Expectancy

Neuroimaging in humans has provided a step forward in understanding reward processing 12. However, there are constraints that limit the study of reward processing in humans with non-invasive brain imaging. Another major limitation for studying reward processing in humans is the profligate use to which the term reward is subjected. Reward is used in many ways in many contexts, and it is often used interchangeably with the term reinforcement. Most investigators have taken the definition of reward to be a stimulus that can act as a positive reinforcer, although in any given experiment, a reward may or may not be used to reinforce anything. In humans, reward generally takes the form of appetitive stimuli (food, water, drugs) or money. There has been a proliferation of human experiments probing reward expectancy in humans using fMRI, and these may well serve to define new and more highly differentiated notions of reward, that is, more detailed, algorithmic descriptions.

Functional Magnetic Resonance Imaging (fMRI)

fMRI enables researchers to visualize changes in blood oxygenation. In the blood oxygen level, dependent (BOLD) effect, approximately 4–6 seconds after neural activity occurs, an excess of oxygenated blood is delivered to that brain region. This localized pooling of oxygenated haemoglobin creates a transient magnetic inhomogeneity that can be detected with a magnetic resonance scanner. fMRI activation correlates more closely with changes in postsynaptic membrane potential than with changes in presynaptic firing, and so has been postulated to index the combined input to a brain region 13.

As a neural probe, fMRI cannot measure directly the efflux of dopamine or other neuromodulators. However, one can still use fMRI to make meaningful differentiations between reward and the reward expectancy in the human brain. fMRI cannot presently index specific neurochemical changes, although combined pharmacological and fMRI studies may eventually elucidate these links 14. Additionally, many brain areas of central interest to reward researchers (e.g., the NAcc, orbital frontal cortex, and mPFC) lie near tissue boundaries (i.e., next to ventricles and sinuses), which can cause artifacts unless care is taken to minimize magnetic inhomogeneities (e.g., by use of special pulse sequences or acquisition parameters).

  • fMRI affords increased spatial resolution (e.g., as small as 1 mm 3 versus 8 mm 3).
  • Substantially increased temporal resolution (e.g., seconds rather than minutes).
  • Safe and convenient – since blood itself provides the signal, researchers need not inject radioactive compounds or other agents into subjects prior to scanning.

Positron Emission Tomography (PET)

PET includes a variety of techniques that enable researchers to visualize metabolic and neurochemical changes in brain activity. In metabolic PET, researchers typically inject radioactively tagged oxygen or glucose into subjects, which is taken up into active brain regions as subjects perform a task. The tagged positron decays, emitting two electrons at 180°C that can be coincidentally detected with a PET camera.

  • PET can facilitate neurochemical inference and does not suffer from artifacts in regions near tissue boundaries
  • PET typically has less spatial (~ 8 mm) and temporal resolution (> 2 min) than FMRI.

The visually compelling nature of the results obtained from fMRI and PET, showing brain areas “lighting up”, has been highly influential not just in the neuroscientific and psychological communities, but also beyond. The result has been that scientists in many disciplines began to consider the possibilities of measuring the brain activity of humans during decision making. The challenge now is that there is no clear theoretical tool for organizing this huge amount of information.

Conclusions

Neuroeconomics research helps to disentangle the complex interrelationships between the neural mechanisms with which evolution has endowed our brains, the mechanisms that our brains have built into our external institutions, and the joint computations of these mechanisms from which social and economic outcomes emerge. Neuroeconomics can help to distinguish between these mechanisms, and is certain to play a fundamental role in the process of discovering how people decide.

References

  1. RANGEL, A., CAMERER, C. & MONTAGUE, P. R. A FRAMEWORK FOR STUDYING THE NEUROBIOLOGY OF VALUE-BASED DECISION MAKING. NAT REV NEUROSCI 9, 545–556 (2008).
  2. GLIMCHER, P. W. & RUSTICHINI, A. NEUROECONOMICS: THE CONSILIENCE OF BRAIN AND DECISION. SCIENCE (80-. ). 306, 447 LP-452 (2004).
  3. RANGEL, A., CAMERER, C. & MONTAGUE, P. R. NEUROECONOMICS: THE NEUROBIOLOGY OF VALUE-BASED DECISION-MAKING. NAT. REV. NEUROSCI. 9, 545–556 (2008).
  4. FEHR, E. & CAMERER, C. F. SOCIAL NEUROECONOMICS: THE NEURAL CIRCUITRY OF SOCIAL PREFERENCES. TRENDS COGN. SCI. 11, 419–427 (2017).
  5. PLATT, M. L. & HUETTEL, S. A. RISKY BUSINESS: THE NEUROECONOMICS OF DECISION MAKING UNDER UNCERTAINTY. NAT. NEUROSCI. 11, 398–403 (2008).
  6. KABLE, J. W. & GLIMCHER, P. W. THE NEUROBIOLOGY OF DECISION: CONSENSUS AND CONTROVERSY. NEURON 63, 733–745 (2009).
  7. LEE, N., BRODERICK, A. J. & CHAMBERLAIN, L. WHAT IS ‘NEUROMARKETING’? A DISCUSSION AND AGENDA FOR FUTURE RESEARCH. INT. J. PSYCHOPHYSIOL. 63, 199–204 (2007).
  8. KOSFELD, M., HEINRICHS, M., ZAK, P. J., FISCHBACHER, U. & FEHR, E. OXYTOCIN INCREASES TRUST IN HUMANS. NATURE 435, 673–676 (2005).
  9. ADOLPHS, R. ET AL. A MECHANISM FOR IMPAIRED FEAR RECOGNITION AFTER AMYGDALA DAMAGE. NATURE 433, 68–72 (2005).
  10. BAUMGARTNER, T., HEINRICHS, M., VONLANTHEN, A., FISCHBACHER, U. & FEHR, E. OXYTOCIN SHAPES THE NEURAL CIRCUITRY OF TRUST AND TRUST ADAPTATION IN HUMANS. NEURON 58, 639–650 (2017).
  11. KAWASHIMA, T., OKUNO, H. & BITO, H. A NEW ERA FOR FUNCTIONAL LABELING OF NEURONS: ACTIVITY-DEPENDENT PROMOTERS HAVE COME OF AGE. FRONT. NEURAL CIRCUITS 8, 37 (2014).
  12. BREITER, H. C., AHARON, I., KAHNEMAN, D., DALE, A. & SHIZGAL, P. FUNCTIONAL IMAGING OF NEURAL RESPONSES TO EXPECTANCY AND EXPERIENCE OF MONETARY GAINS AND LOSSES. NEURON 30, 619–639 (2017).
  13. LOGOTHETIS, N. K., PAULS, J., AUGATH, M., TRINATH, T. & OELTERMANN, A. NEUROPHYSIOLOGICAL INVESTIGATION OF THE BASIS OF THE FMRI SIGNAL. NATURE 412, 150–157 (2001).
  14. KNUTSON, B. & GIBBS, S. E. B. LINKING NUCLEUS ACCUMBENS DOPAMINE AND BLOOD OXYGENATION. PSYCHOPHARMACOLOGY (BERL). 191, 813–822 (2007).

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