9.1 Neural basis of value and utility

The brain's neural networks encode subjective value, guiding our decisions and shaping consumer behavior. Key regions like the orbitofrontal cortex, ventromedial prefrontal cortex, and striatum work together to represent and update value signals based on context and experience.

Understanding these neural mechanisms offers insights for marketers. By leveraging framing effects, anchoring, and scarcity, companies can influence perceived value and willingness to pay. Neuroeconomic research challenges assumptions of rational choice, revealing how emotions and cognitive biases shape our preferences and purchasing decisions.

Neural representations of value

• The brain encodes the subjective value we assign to options and outcomes in our environment
• These value representations guide our decision making by allowing us to compare and choose between alternatives
• Different brain regions are involved in representing value in different ways and contexts

Orbitofrontal cortex

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• Represents the subjective value of sensory stimuli like tastes, smells, and textures
• Encodes the economic value of goods in a common neural currency that allows comparison
• Damage to the OFC impairs value-based decision making (choosing between food rewards)
• Involved in updating value representations based on changing circumstances (devaluation)

Ventromedial prefrontal cortex

• Integrates value signals from multiple sources to compute an overall subjective value
• Represents the value of complex, abstract rewards like money, social praise, or charitable donations
• vmPFC activity predicts consumer preferences and willingness-to-pay for goods
• Patients with vmPFC damage make more impulsive, shortsighted decisions

Striatum and dopamine

• Striatum receives dopaminergic input encoding reward prediction errors - the difference between expected and received rewards
• These RPE signals drive learning to update future value expectations
• Ventral striatum encodes the incentive salience or "wanting" of rewards
• Dorsal striatum is involved in action selection based on learned action-outcome contingencies

Amygdala and emotions

• Amygdala represents the emotional significance of stimuli, including both positive and negative valence
• Interactions between amygdala and vmPFC may underlie emotional influences on value-based choice (avoiding losses)
• Amygdala damage impairs recognition of emotional facial expressions and learning of fear associations
• Amygdala responses to marketing stimuli predict future purchasing behavior

Subjective value vs market price

• The subjective value an individual assigns to a good often differs from its objective market price
• This divergence arises from individual differences in preferences, budget constraints, and psychological factors
• Neuromarketing techniques aim to measure subjective value to predict consumer choice and willingness-to-pay

Willingness to pay

• The maximum price a consumer is willing to pay for a good, reflecting their subjective valuation
• Can be measured through incentive-compatible auction procedures like the Becker-DeGroot-Marschak method
• Neural activity in the vmPFC and ventral striatum correlates with willingness-to-pay bids
• Allows estimation of demand curves and price elasticity for products

Consumer surplus

• The difference between a consumer's willingness-to-pay and the actual market price paid
• Represents the net value captured by the consumer in a transaction
• Increasing consumer surplus (through sales, promotions, loyalty programs) can drive purchases
• Perceived consumer surplus activates reward circuitry and predicts brand preferences

Prospect theory and loss aversion

• Prospect theory is a descriptive model of decision-making under risk developed by Kahneman and Tversky
• It states that losses have a greater psychological impact than equivalent gains (loss aversion)
• The value function is concave for gains but convex for losses and steeper for losses than gains
• Framing outcomes as losses rather than gains can therefore have a strong influence on choice

Temporal discounting of value

• Humans and animals tend to discount the value of future rewards compared to immediate rewards
• This time preference reflects opportunity costs, uncertainty, and impulsive tendencies
• Steep temporal discounting is associated with shortsighted behaviors like overeating, gambling, and substance abuse

Immediate vs future rewards

• Given a choice, both humans and animals often prefer smaller immediate rewards over larger future rewards
• This preference reverses when both rewards are shifted into the future (preference reversal)
• Suggests the discounting function is steeper in the near future than far future
• Individuals differ in their discounting rates, with steeper discounters being more impulsive

Hyperbolic discounting

• The empirical discounting function is better fit by a hyperbola than an exponential curve
• Hyperbolic discounting leads to dynamically inconsistent preferences and preference reversals over time
• Can explain impulsive preference for immediate gratification and failures of self-control
• Implies that future rewards are discounted at a higher rate in the near future than far future

Impulsivity and self-control

• Impulsivity is the tendency to act on immediate urges without considering future consequences
• Associated with steeper temporal discounting and preference for immediate rewards
• Involves a failure of self-control mechanisms that prioritize long-term goals over short-term temptations
• Linked to disorders like ADHD, addiction, and obesity, as well as risky behaviors like unsafe sex

Context-dependent value

• The subjective value of an option depends not only on its intrinsic properties but also the context of the choice set
• Contextual factors like framing, anchoring, and perceived scarcity can systematically influence valuation
• Marketers can leverage these context effects to shift preferences and boost perceived value

Framing effects

• Describing an option in terms of its positive features (gains) or negative features (losses) influences its attractiveness
• Consumers tend to be risk-averse for gains but risk-seeking for losses (reflection effect)
• Framing a price difference as a discount rather than a surcharge makes it more appealing
• Framing an option as the default or status quo increases its likelihood of being chosen

Anchoring and adjustment

• Presenting an arbitrary initial price influences willingness-to-pay by serving as an anchor
• Consumers adjust their valuations away from this anchor but often insufficiently
• Even irrelevant anchors like a random number or the last digits of one's social security number can bias estimates
• Anchoring high and then offering a discount makes a price seem more attractive

Scarcity and perceived value

• Perceiving a good as rare or scarce boosts its desirability and perceived value
• Scarcity implies high demand, exclusivity, and a potential for status signaling
• Artificial scarcity through limited editions or time-bounded offers leverages this effect
• Avoiding a loss of access to scarce goods motivates choice through psychological reactance

Neuroeconomics of utility

• Utility is a construct representing the satisfaction or benefit a consumer derives from a good
• Neoclassical economics assumes that agents have stable, well-defined utility functions and always maximize expected utility
• Neuroeconomics research probes the neural basis of utility and challenges assumptions of rational choice

Revealed preferences

• Economists assume we can infer utility functions from observed choice behavior (revealed preferences)
• If an agent chooses apples over oranges, this implies apples have higher utility
• But choice can be inconsistent across contexts and influenced by biases and heuristics
• Revealed preferences may not reflect true underlying utility, which is subjective and context-dependent

Expected utility theory

• Expected utility theory proposes that agents choose to maximize their expected utility
• The expected utility of an option is the sum of the utilities of each possible outcome weighted by their probabilities
• But humans often violate the axioms of expected utility theory and show risk preferences
• Prospect theory is an alternative model that better fits observed choice under risk

Axioms of rational choice

• Expected utility theory assumes certain logical principles of rational choice called axioms
• Axioms include completeness, transitivity, continuity, and independence
• But actual human choice often violates these axioms due to psychological biases
• For example, adding an irrelevant alternative can alter preferences between two options (violating independence)

Neural value signals

• Neuroeconomic studies have identified neural signals that encode the subjective value of options
• These value signals are represented in a common currency that allows comparison and choice
• Value signals can be measured at different scales, from single neurons to brain-wide networks

Single-neuron recordings

• In monkeys and humans, neurons in frontal and parietal cortices encode offer and chosen values
• These value signals are menu-invariant - they reflect the intrinsic value of an option regardless of alternatives
• OFC neurons adapt to the value range in a given context, representing relative rather than absolute values
• Striatal neurons encode action values - the value of taking a particular action in a given state

fMRI decoding of value

• fMRI can detect value signals from regional hemodynamic responses reflecting neural population activity
• The OFC and vmPFC consistently show correlations with subjective value across many task domains
• Multivariate decoding methods can predict choice from these value-related fMRI patterns
• Value signals are modulated by individual differences in preferences and choice behavior

EEG markers of value processing

• EEG potentials like the feedback-related negativity (FRN) and reward positivity (RewP) reflect reward processing
• The FRN is a negative deflection that scales with reward prediction errors and is linked to dopamine signaling
• The RewP is a positive potential that scales with reward magnitude and is generated in the ACC and striatum
• These potentials reveal the rapid dynamics of value computation and can predict learning and choice

Modulation of value signals

• Neural value representations are not static but can be modulated by internal and external factors
• Attention, emotion, and cognitive regulation strategies can all influence subjective value
• Identifying factors that shift value coding may yield new approaches for changing behavior

Attention and saliency

• Directing attention to a stimulus feature amplifies its neural representation and influence on choice
• Manipulating visual saliency through color, motion, or contrast can draw attention and boost valuation
• Value signals in the vmPFC are enhanced for attended relative to unattended items
• Suggests that active attentional strategies during choice (like evaluating opportunity costs) could alter preferences

Cognitive regulation strategies

• Cognitive reappraisal strategies can modulate emotion and value responses in the brain
• Reinterpreting the meaning of a stimulus in a less negative way reduces amygdala and vmPFC responses
• Focusing on alternative uses or non-consummatory aspects of a food reduces craving-related activity
• Explicitly considering opportunity costs during choice recruits the ACC and alters vmPFC value signals

Transcranial stimulation approaches

• Non-invasive brain stimulation techniques like TMS and tDCS can modulate value-related processing
• Disrupting OFC activity with TMS impairs value comparison and increases choice inconsistency
• Enhancing dlPFC excitability with anodal tDCS improves self-control in dieters and reduces impulsive choice
• Stimulating frontopolar cortex alters exploration-exploitation tradeoffs in foraging tasks

Implications for marketing

• Insights from decision neuroscience and neuroeconomics can inform marketing strategies
• Understanding what factors influence neural value representation and choice can help predict and shape consumer behavior
• Specific tactics like pricing, framing, and positioning can be optimized based on brain responses

Pricing strategies

• Neural value signals in the striatum and vmPFC correlate with market demand and purchase rates
• Responses to prices in these regions predict individual differences in price elasticity
• Measuring neural responses to different possible price points for a product could help optimize pricing
• Personalized pricing based on neural markers of individual willingness-to-pay could boost profitability

Product positioning and framing

• The framing of a product (what attributes are emphasized) influences neural value signals and choice
• Framing a food as healthy vs. indulgent shifts value responses in vmPFC and behavioral preferences
• Framing a price as a discount vs. a surcharge alters striatal reward responses
• Positioning a product to align with personal values and identity increases vmPFC value representations

Influencing consumer choice

• Priming, anchoring, and decoy effects can alter preferences by changing the choice context
• Presenting an expensive decoy option makes the target option seem more attractive
• Priming concepts like prestige or scarcity activates associated brain networks and influences valuation
• Narratives, celebrity/expert endorsements, and social proof can all enhance subjective value and vmPFC representation