TABLE 1.
Consumer neuroscience research in marketing, consumer research, and neuroscience journals (chronological order).
| Author(s) and Journal* | fMRI-related research question | Major findings | Identified brain areas | Role of fMRI in study | Meta-analysis | Triangulation with psychometric and/or behavioral data |
| McClure et al. (2004), Neuron | What are the neural correlates of the consumer preference for Coke and Pepsi two similar drinks, and how can brand knowledge influence the behavioral preference and brain responses. | When the brands are delivered anonymously, brain activity in the ventromedial prefrontal cortex correlates with participant’s behavioral preferences for the drinks. However, when participants know that it is Coke that they are drinking, behavioral preferences are drastically influenced and activity in the hippocampus, dorsolateral prefrontal cortex, and midbrain are also found. | •Ventromedial prefrontal cortex (reward). •Dorsolateral prefrontal cortex, hippocampus, and midbrain (recall of cultural influences). |
Investigate neural correlates | Yes | |
| Yoon et al. (2006) JCR | Whether semantic judgments about products and persons are processed similarly. | Mental judgments about persons and products are processed differently. | •Medial prefrontal cortex (semantic judgments about persons). •Left inferior prefrontal cortex (semantic judgments about products). |
Distinguish multiple processes | ||
| Knutson et al. (2007), Neuron | How product preference and price are captured in consumer brain and how their neural correlates predict purchase. | Product preference activates the nucleus accumbens. Excessive price, on the other hand, activates the insula and deactivates the medial prefrontal cortex. Activities in each of these regions can independently predict purchase. | •Nucleus accumbens (gain prediction). •Insula (loss prediction). •Medial prefrontal cortex (gain prediction errors). |
Investigate neural correlates and predict behaviors | ||
| Plassmann et al. (2007), JN | How willingness to pay is encoded in the brain. | Willingness to pay is encoded in the medial orbitofrontal cortex and in the dorsolateral prefrontal cortex. | Medial orbitofrontal cortex (reward and valuation) | Investigate neural correlates | ||
| Weber et al. (2007), NI | What are the neural correlates of reference-dependence of utility evaluation (i.e., the endowment effect), before and after the buying/selling decision in real market contexts. | Fear-related processes are observed when a product is being sold but not when it is being bought. After the decision is made, reward related processes are observed if a high external reference price of the product is provided. | •Left amygdala (fear and loss). •Caudate nucleus (action planning and monetary rewards expectation). •Orbitofrontal cortex (reward). •Anterior cingulate (mental conflicts, reward, and valuation). |
Investigate neural correlates | ||
| Bray et al. (2008), JN | What are the neural correlates of the outcome-specific transfer (the consumer tendency to choose the option with a particular outcome when a Pavlovian cue is present, if the Pavlovian cue has previously been associated with that outcome). | A region in the ventral caudolateral putamen is associated with outcome-specific transfer. | Ventral putamen (reward outcome and reward learning) | Investigate neural correlates | ||
| Klucharev et al. (2008), SCAN | What are the neural correlates of the persuasive effect of high expertise of the communicator (i.e., the “expert power”) | Expert content is associated with brain regions associated with active semantic elaboration, memory formation, and trustful behavior, reward processing, and learning | •Left dorsomedial prefrontal cortex, anterior cingulate, superior temporal sulcus (semantic processing). •Hippocampus and parahippocampal gyrus (memory). •Caudate nucleus (trust, reward, learning). |
Investigate neural correlates | ||
| Plassmann et al. (2008), PNAS | How the price of a product influences the neural computations with its experienced pleasantness. | Increase of the price of a wine increases both the activation in the medial orbitofrontal cortex and the subjective report of pleasantness. | •Medial orbitofrontal cortex (encoding of experienced pleasantness). | Identify psychological processes | ||
| De Martino et al. (2009), JN | Whether reference-independent and -dependent value computations are reflected in the same region of the brain. | The computation of reference-independent value is associated with the activity in the orbitofrontal cortex and dorsal striatum. On the other hand, the computation of reference-dependent value is associated with the activity in the ventral striatum. | •Orbitofrontal cortex. •Dorsal striatum. •Ventral striatum. |
Investigate neural correlates | ||
| Dietvorst et al. (2009), JMR | How to judge salespersons’ ability of interpersonal-mentalizing (i.e., inferring the viewpoints of customers). | Interpersonal mentalizing process (“read” others’ minds, process subtle interpersonal cues, and then adjust volitions accordingly). | Medial prefrontal cortex and bilateral temporo-parietal junctions (interpersonal-mentalizing skills) | Predict behaviors | Yes | |
| Hedgcock and Rao (2009), JMR | Why the introduction of a decoy option (i.e., an option that is dominated and thus should not the influence preference for other options) into the choice set makes one of the original options more attractive (the “attraction effect”). | The decoy option produces the attraction effect by reducing negative emotions experienced by the decision maker. | •Amygdala (negative emotions). •Medial prefrontal cortex (self-referential evaluation of preferences). •Dorsal lateral prefrontal cortex (use of decision rules). •Anterior cingulate cortex (conflict monitoring). •Right inferior parietal lobule (numerical magnitude processing). |
Identify psychological processes | Yes | |
| Berns et al. (2010), NI | How the popularity of music influences individual rating thereof. | Popularity rating influences individual rating by creating anxiety due to a mismatch between one’s own and others’ preferences. This anxiety in turn drives choice switch in the direction of popularity rating. Popularity does not seem to change the individual preferences for music per se. | •Caudate nucleus (reward and likability). •Anterior insula and anterior cingulate (physiological arousal and negative affective states). •Middle temporal gyrus (semantic processing). |
Identify psychological processes, and test competing theories | ||
| Linder et al. (2010), NI | How consumers evaluate food with (vs. without) organic labels. | Organic food label is associated with increased activity in the ventral striatum. The difference in such activity can predict the real-world consumption behavior of organic food. | Ventral striatum (reward) | Identify psychological processes and predict behavior | ||
| Rademacher et al. (2010), NI | Whether the anticipation and consumption of rewards (monetary and social) involves the same or different neural networks. | Anticipation and consumption of rewards involve dissociable neural networks. Anticipation of both monetary and social reward involves the reward system including the ventral striatum. On the other hand, the consumption of monetary reward involves the thalamus, whereas the consumption of social reward involves the amygdala. | •Brain reward system including ventral striatum (reward anticipation). •Amygdala (social reward consumption). •Thalamus (monetary reward consumption). |
Investigate neural correlates | ||
| Reimann et al. (2010), JCP | How consumers process aesthetic package design. | The reward system in the brain plays a role in processing aesthetic package design. | •Striatum (anticipated reward). •Ventromedial prefrontal cortex (reward outcome). |
Identify neural correlates and psychological processes | Yes | |
| Schaefer and Rotte (2010), SCAN | How brands are represented in the brain. | Brands rated higher on “social competence” is associated with greater activation in the medial prefrontal cortex, whereas brands rated higher on “potency” is associated with greater activation in the superior frontal gyri. | •Medial prefrontal cortex (social cognition). •Superior frontal gyri (working memory). |
Investigate neural correlates | ||
| Smith et al. (2010), JN | Whether expected and experienced value are reflected in the same part of the brain. | Experienced value is reflected in the anterior ventromedial prefrontal cortex, whereas expected value is reflected in the posterior ventromedial prefrontal cortex. | Ventromedial prefrontal cortex (reward). | Investigate neural correlates | ||
| Tusche et al. (2010), JN | What brain regions can predict consumer choice, and how product attention influences such predictions. | Insula and medial prefrontal cortex activation patterns can predict consumer choice, both under high and low product attention. | Insula and medial prefrontal cortex (reward). | Predict behavior | ||
| Kang et al. (2011), JN | Whether hypothetical and real decision-making processes undergo the same type of valuation and choice computations or not. | Common areas in the orbitofrontal cortex and the ventral striatum are related to both hypothetical and real evaluation of goods. The difference found between the two types of decision-making are quantitative instead of qualitative. | Orbitofrontal cortex and ventral striatum, anterior cingulate cortex, caudate, inferior frontal gyrus (reward). | Identify psychological processes, and test competing theories | ||
| Levy et al. (2011), JN | Does a single neural mechanism capture the reward values of options and thus predict consumer preferences, both when a decision requires subsequent choice and when the choice is absent. | The striatum and medial prefrontal cortex represent values whether choice is required or not. | Striatum and medial prefrontal cortex (reward). | Identify psychological processes and predict behavior | ||
| Bagozzi et al. (2012), JAMS | What is the neural basis of customer orientation (as opposed to sales orientation) in salespersons. | Customer oriented, but not sales oriented, salespersons features greater activity in their mirror neuron systems, as well as empathy-related neural process. | •Posterior inferior frontal cortex, Broca’s area, and anterior inferior parietal lobule (mirror neuron system). •Medial prefrontal cortex, precuneus, and right inferior parietal cortex (empathy). •Insula and amygdala (empathic concern). •Inferior parietal lobule (self-other monitoring). |
Investigate neural correlates | Yes | |
| Berns and Moore (2012), JCP | Whether brain activation acquired from a small sample can predict product acceptance in a broader population. | Although subjective likability of the songs was not predictive of sales, activity within the ventral striatum was significantly correlated with the number of units sold. | Precuneus, orbitofrontal cortex, and ventral striatum/nucleus accumbens (reward). | Predict behavior | Yes | |
| Craig et al. (2012), JMR | How consumers process deceptive advertisement claims. | Consumers process deceptive claims in two distinct stages: First, greater attention may be allocated to more deceptive information; second, more attention and belief reasoning may then be directed toward believable and moderately information. | •Amygdala, precuneus (expectation violation observed in person-to-person cheater detection). •Superior temporal and inferior parietal areas (including superior temporal sulcus and temporo-parietal junctions) (verification and assessment of claims). |
Identify psychological processes and distinguish multiple processes | Yes | |
| Esch et al. (2012), JCP | What are the consumer linguistic encoding/retrieval processes and how do they use declarative/experiential information in the evaluation of unfamiliar vs. familiar (strong and weak) brands. | The evaluation of unfamiliar brands is associated with linguistic encoding, whereas the evaluation of strong brands is associated with information retrieval. Moreover, consumers use experienced emotions rather than declarative information to evaluate brands. | •Broca’s area (linguistic processing). •Wernicke’s area (brand retrieval). •Pallidum (positive emotions). |
Investigate neural correlates and identify psychological processes | ||
| Falk et al. (2012), PS | Can neural responses collected from a small group of people predict the effectiveness of an anti-smoking television campaign. | Activations in the medial prefrontal cortex predicts the population-level effectiveness of the campaign. | Medial prefrontal cortex (individual behavior change). | Predict behavior | Yes | |
| Hedgcock et al. (2012), JCP | How depletion causes self-control failure in a two-stage model (stage 1: recognizing the need for self-control; stage 2: implementing controlled responses). Specifically, whether depletion undermines stage 1 only, stage 2 only, or both. | Depletion affects the implementation stage only and leaves intact the ability to recognize the need for self-control. | •Anterior cingulate cortex (goal conflict identification). •Dorsolateral prefrontal cortex (controlled actions implementation). |
Identify psychological processes, and test competing theories | Yes | |
| Lawrence et al. (2012), NI | How the nucleus accumbens is associated with food cue and predicts subsequent food consumption and body mass index. | Food cue related activations in the nucleus accumbens predicts subsequent snack food consumption (but not subjective hunger) in female participants. Nucleus accumbens activities also predict body mass index but only in participants with lowered self-control. | •Left nucleus accumbens (food motivation, reward, wanting). •Ventromedial prefrontal cortex (subject hunger/appetite). |
Investigate neural correlates and predict behavior | ||
| Reimann et al. (2012), JCP | •How consumers relate to their beloved brands. | Emotional arousal decreases over the brand relationship span, while inclusion of the brand into the self increases over time. | Insula (urging, addiction, loss aversion, and interpersonal love) | Identify neural correlates and psychological processes | Yes | |
| Grabenhorst et al. (2013), NI | How sample food labels influence consumer healthy food choice. | Food labels can bias food evaluations in the amygdala, and the strength of such biases can predict behaviors toward healthier food choices. | Amygdala (emotion). | Identify psychological processes | ||
| Bruce et al. (2014a), SCAN | How children’s brains react to food brand logos in children. | Food logos (vs. baseline) are associated with activity in the orbitofrontal cortex and inferior prefrontal cortex. Food logos (vs. non-food logos) are associated with activity in the posterior cingulate cortex. | •Orbitofrontal cortex (motivation). •Inferior prefrontal cortex (cognitive control). •Posterior cingulate cortex (visual engagement). |
Investigate neural correlates | ||
| Bruce et al. (2014b), JNPE | How consumers react to food attributes presented to them, especially the food’s price and technology used to produce it. | Increased number of presented attributes is associated with increased activity in the dorsolateral prefrontal cortex | Dorsolateral prefrontal cortex (working memory and uncertainty). | Investigate neural correlates | ||
| Gearhardt et al. (2014), SCAN | What the neural responses of food-related (vs. non-food-related) commercials, and how weight influences such neural responses. | Adolescents exhibit overall greater activation in brain regions associated with visual processing, attention, cognitive processing, movement, somatosensory responses, and reward, when they process food-related (vs. non-food-related) commercials. Moreover, during food relative to non-food commercials, obese participants feature less activation in brain regions associated with visual processing, attention, reward, and salience detection. Obese participants also feature more activation in brain regions associated with semantic control. | •Occipital gyrus, cuneus (visual processing). •Parietal lobes, posterior cerebellar lobe, temporal gyrus (attention and cognition). •Anterior cerebellar cortex (movement). •Postcentral gyrus (somatosensory response). •Orbitofrontal cortex, anterior cingulate cortex, ventromedial prefrontal cortex (reward). •Precuneus (salience detection). •Medial temporal gyrus (semantic control). |
Investigate neural correlates | ||
| Kanayet et al. (2014), PS | Whether numeric magnitude and monetary value are processed by distinct regions in the neural network involved in the valuation of monetary reward. | Changes in numeric magnitude is associated with activities in intraparietal sulcus, whereas monetary value is associated in the activity in orbitofrontal cortex. | •Intraparietal sulcus (numeric information). •Orbitofrontal cortex (reward, valuation). |
Investigate neural correlates and distinguish multiple processes | ||
| Lighthall et al. (2014), JN | How older adults compensate their age-related memory decline during memory-dependent decision-making in consumption. | Medial prefrontal cortex provides functional compensation for aging adults in memory-dependent decision-making tasks. | Medial prefrontal cortex and its connectivity with dorsolateral prefrontal cortex. | Identify psychological processes | ||
| Tang et al. (2014), PS | How actual and perceived foods’ caloric content influences the neural predictors of food choice. | Actual, but not perceived, food caloric content is associated with activations in the ventromedial prefrontal cortex, which is known as a predictor of food choice. The ventromedial prefrontal cortex demonstrates a functional connectivity with an appetitive brain network, which is modulated by the willingness to pay. | •Ventromedial prefrontal cortex (reward). •Functional connectivity to ventromedial prefrontal cortex, including amygdala, hippocampus, ventral stratum (computation of subject value). •Insula (sensory characteristics of food). |
Identify psychological processes, investigate neural correlates, and predict behavior | ||
| Yokoyama et al. (2014), NI | What are the brain regions associated with the perception of social risk when purchase decisions are being made. | In a purchase intention task, ratings of social risk during purchase decision are associated with activity in the left anterior insula. In a social risk task, ratings of social risk are associated with activity in the left temporal parietal junction and medial prefrontal cortex. | •Left anterior insula (emotion-related network). •Left temporal parietal junction and medial prefrontal cortex (theory of mind). |
Investigate neural correlates | ||
| Cascio et al. (2015), JMR | How consumers make recommendation decisions in light of the preferences and opinions of others. | Decisions to update other-directed recommendations in response to peer opinions may unite brain systems associated with social influence and the concept of being a “successful idea salesperson.” | •Precuneus/posterior cingulate cortex, dorsal, dorsal anterior cingulate cortex, ventral striatum, anterior insula, orbitofrontal cortex/dorsomedial prefrontal cortex (social influence). •bilateral temporo-parietal junctions, medial prefrontal cortex (successful recommendations). |
Identify psychological processes | Yes | |
| Chen et al. (2015), JMR | Whether consumers have an a priori network in their minds that reflects personality traits associated with brands and, if so, what cognitive processes are captured by such a network. | An a priori neural network is distributed widely across the brain and reflects personality traits associated with brands. | A wide range of brain areas including the anterior cingulate, middle cingulate, dorsomedial prefrontal, medial prefrontal, premotor, dorsolateral prefrontal, posterior cingulate, primary visual, lateral prefrontal, and inferior frontal cortices; the insula; and the hippocampus. | Investigate neural correlates | Yes | |
| Genevsky and Knutson (2015), PS | What factors influence the outcomes of online microlending, and whether a neural activity may forecast this outcome. | Positive affect, both self-reported and captured by the activity in the nucleus accumbens can promote the success of loan requests. | Nucleus accumbens (positive arousal) | Identify psychological processes and predict behavior | Yes | |
| Karmarkar et al. (2015), JMR | Whether seeing the price of a product before or after seeing the product influences the way the product is processed. | Price primacy (i.e., seeing the product price before seeing the product) makes consumers evaluate the product based on its monetary worth, whereas product primacy (i.e., seeing the product before seeing the product price) makes consumers evaluate the product based on its attractiveness and likability. | •Medial prefrontal cortex (perceived monetary value). •Nucleus accumbens (attractiveness or expressed preference). |
Identify psychological processes | Yes | |
| Plassmann and Weber (2015), JMR | What individual differences can predict the consumer responsiveness to the “marketing placebo effects” (i.e., the effect by which consumption experience and subsequent behavior are influenced by marketing-based expectations such as price, quality beliefs, etc.). | Reward seeking, somatosensory awareness, and need for cognition can predict marketing placebo effects. | •Gray matter volume of the striatum (reward responsiveness/learning). •Gray matter volume of prefrontal structures (i.e., lateral orbitofrontal, lateral prefrontal, and dorsomedial prefrontal cortex) (cognitive top-down processing). •Gray matter volume of the posterior insula and somatosensory cortices (Somatosensory bottom-up processing). |
Identify psychological processes | Yes | Yes |
| Venkatraman et al. (2015), JMR | How to predict ads’ effectiveness using fMRI. | Product desirability measured at the brain level is associated with real-world, market-level response to advertising. | •Amygdala (affective processing). •Dorsolateral prefrontal cortex (cognitive processing). •Ventromedial prefrontal cortex, striatum (desirability). |
Predict behavior | Yes | |
| Falk et al. (2016), SCAN | Whether and the brain activation acquired in a small group of smokers react to an anti-smoking email campaign can predict the effectiveness of the campaign on a population-level. If yes, via what mechanism. | Neural activity in the medial prefrontal cortex acquired in a small group of smokers is predictive of population-level responses to the campaign. Self-related processing is the neurocognitive mechanism that links neural and behavioral responses. | Medial prefrontal cortex (self-related processing). | Identify psychological processes and predict behavior | Yes | Yes |
| Kühn et al. (2016), NI | How to predict product sales in the real market using fMRI. | fMRI signal acquired in a small sample in eight brain regions that are associated with product decision-making predicts the real-world sales of products shown in the scanner. | •Nucleus accumbens, medial orbitofrontal cortex, amygdala, hippocampus, inferior frontal gyrus, and dorsomedial prefrontal cortex (a range of mental processes associated positively with sales). •Dorsolateral prefrontal cortex and insula (a range of mental processes associated negatively with sales). |
Predict behavior | Yes | |
| Reimann et al. (2016), JACR | Why offering consumers the choice between a full-sized food portion alone and a half-sized food portion paired with a small non-food premium (e.g., a small toy or the mere possibility of winning frequent flyer miles) can motivate smaller portion choice. | Food and the expectation of receiving a non-food premium activate a common area of the brain (the striatum), which is associated with reward, desire, and motivation. | Striatum (reward processing). | Identify neural correlates and psychological processes | Yes | Yes |
| Chung et al. (2017), JN | What is the underlying mental process of decoy effect. | Underlying decoy effect seems to be context-dependent valuation. Moreover, deliberate control that monitors and corrects decision-making errors and biases is associated with the successful overcome of decoy effect. | •Left ventral striatum (reward value). •Right inferior frontal gyrus (response inhibition). |
Identify psychological processes | ||
| Genevsky et al. (2017), JN | Whether and, if yes, what neural activities can predict real crowdfunding outcomes weeks later from the time of fMRI scan. | The nucleus accumbens and medial prefrontal cortex both predict individual choices to fund in crowdfunding. However, only the nucleus accumbens predicts the market-level funding outcome. | •Nucleus accumbens (positive arousal). •Medial prefrontal cortex (value integration). |
Predict behavior | Yes | Yes |
| Dal Mas and Wittmann (2017), Cortex | How consumers react to boredom and what are the neural systems underlying these reactions. | Consumer accept higher prices to avoid expected boredom, a behavioral bias modulated by caudate nucleus. During the actual performance of a boring task, insula is activated and is associated with individual differences in boredom-related decision making | •Caudate nucleus (reward). •Insula (experiencing boredom). |
Investigate neural correlates | ||
| Chan et al. (2018), JMR | How to profile brand image using neuroimaging methods. | Perceived cobranding suitability, brand image strength can be used to profile brand image. | Occipital cortex, precuneus, posterior cingulate cortex, parahippocampal gyrus, and temporoparietal junction (areas associated with visual processing, episodic memory, self-awareness, and the default network) | Predict behavior | Yes | |
| Reimann et al. (2018), JACR | Whether brand betrayal is an extreme form of brand dissatisfaction. | Brand dissatisfaction can be distinguished from brand betrayal. | Dorsolateral prefrontal cortex, angular gyrus, caudate tail (betrayal experience) | Identify psychological processes and distinguish multiple processes | Yes | Yes |
| Schmidt et al. (2018), JN | What underlies the individual differences in making healthy food choices. | The gray matter volume in the ventromedial prefrontal cortex and the dorsolateral prefrontal cortex predict individual differences in shifting to healthier food. | Ventromedial prefrontal cortex and dorsolateral prefrontal cortex (reward and valuation) | Predict behavior | ||
| Chan et al. (2019), NI | Whether the predictive power of neural similarity distributes across the whole brain or only in specific regions (“neural similarity” here refers to the similar neural responses to stimuli across individuals). Whether similarity acquired in a small group of individuals is known to predict preference for the stimuli in a larger population. | Neural similarity of temporal lobe and cerebellum across a small group of individuals can predict the preference and recall of stimuli (e.g., commercials or products) in a larger sample. | Temporal lobe and cerebellum (level of engagement with video stimuli, sensory integration, emotional processing). | Investigate neural correlates and predict behavior | Yes | Yes |
| Doré et al. (2019), JN | How affective reactivity, valuation, and emotion regulation interact to deliver the impact of emotionally evocative messages (e.g., ads). | Increased activation in the amygdala predicts the effectiveness of emotionally evocative message both on individual and population levels. This effect is mediated by activity in the ventromedial prefrontal cortex and moderated by an emotion regulation pattern in the brain. | •Amygdala (affective reactivity). •Ventromedial prefrontal cortex (integrative valuation). •Whole-brain pattern of emotion regulation. |
Identify psychological processes and predict behavior | ||
| Huang and Yu (2019), NI | What are the neural substrates of the money illusion (the phenomenon wherein consumers evaluate money based on its face value instead of its true purchasing power), in both win and loss domains. | Posterior insula encodes the true value of money in the win domain but not in the loss domain. The ventral striatum, ventromedial prefrontal cortex, and amygdala process money illusion in both win and loss domains. Functional connectivity is also associated with money illusion, such that individuals with greater money illusion exhibit stronger functional connectivity between the ventral striatum and ventral anterior cingulate cortex in the win domain, but stronger functional connectivity between the ventral striatum and amygdala in the loss domain. | •Posterior insula (emotional and somatosensory arousal). •Ventral striatum, ventromedial prefrontal cortex, ventral anterior cingulate cortex (reward). •Amygdala (emotion). |
Investigate neural correlates | ||
| Huijsmans et al. (2019), PNAS | How the “scarcity mindset” created by insufficient resources (e.g., state of poverty) influences consumer decision-making. | A scarcity mindset is associated with increased activity in the orbitofrontal cortex and decreased activity in the dorsolateral prefrontal cortex | •Orbitofrontal cortex (valuation). •Dorsolateral prefrontal cortex (goal-directed choice). |
Identify psychological processes | ||
| Warren and Reimann (2019), JACR | What distinguishes products that look cool from those that look funny. | Cool [humorous] products diverge from the norm in a way that does [does not] make sense. Thus, cool (vs. humorous) products are processed differently in the brain. | Anterior cingulate cortex (resolution of conflict in the environment, error detection, and problem resolution). | Identify psychological processes and distinguish multiple processes | Yes | Yes |
| Wiggin et al. (2019), JCR | How curiosity influences indulgence behavior. | Curiosity gives rise to desire for rewards, which in turn encourages indulgent behavior. | Insula (desire for rewards) | Identify neural correlates and psychological processes | Yes | |
| Tong et al. (2020), PNAS | What are the neural mechanism underlying online video watching. | Video viewing engagement (duration, frequency, etc.) can be predicted by increased activity in the nucleus accumbens and medial prefrontal cortex, and decreased activity in the anterior insula. | •Nucleus accumbens (positive arousal). •Medial prefrontal cortex (value integration of affect with other considerations). •Anterior insula (negative or general arousal). |
Investigate neural correlates and predict behavior |
*JACR, Journal of Association for Consumer Research; JAMS, Journal of the Academy of Marketing Science; JCR, Journal of Consumer Research; JMR, Journal of Marketing Research; JN, Journal of Neuroscience; JNPE, Journal of Neuroscience, Psychology, and Economics; NI, NeruoImage; PNAS, Proceedings of the National Academy of Sciences of the United States of America; PS, Psychological Science; SCAN, Social Cognitive and Affective Neuroscience.