
John ClitheroUniversity of Oregon | UO · Department of Marketing
John Clithero
PhD
About
35
Publications
6,160
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2,018
Citations
Citations since 2017
Introduction
John Clithero is an Assistant Professor of Marketing at the Lundquist College of Business, University of Oregon.
Additional affiliations
July 2011 - June 2014
July 2006 - May 2011
Education
July 2005 - May 2011
Publications
Publications (35)
Money can be tainted when it is associated with direct or indirect harm to others. Deciding whether to accept “dirty money” poses a dilemma because money can be used to help others, but accepting dirty money has moral costs. How people resolve the dilemma of dirty money remains unknown. One theory casts the dilemma as a valuation conflict that can...
The goal of this article is to introduce readers to theories, tools, and evidence from the field of neuroeconomics and to describe how health psychology and neuroeconomics can be mutually informative in the study of preventative health behaviors. Preventative health behavior here refers to both individual actions that impact one's health (e.g., exe...
Direct elicitation, guided by theory, is the standard method for eliciting individual-level latent variables. We present an alternative approach, supervised machine learning (SML), and apply it to measuring individual valuations for goods. We find that the approach is superior for predicting out-of-sample individual purchases relative to a canonica...
How do we make choices for others with different preferences from our own? Although neuroimaging studies implicate similar circuits in representing preferences for oneself and others, some models propose that additional corrective mechanisms come online when choices for others diverge from one’s own preferences. Here we used event-related potential...
How do we make choices for others with different preferences from our own? Although neuroimaging studies implicate similar circuits in representing preferences for oneself and others, some models propose that additional corrective mechanisms come online when choices for others diverge from one’s own preferences. Here we used event-related potential...
A basic problem in empirical economics involves using data from one domain to make out-of-sample predictions for a different, but related environment. When the choice data are binary, a canonical method for making these types of predictions is the logistic choice model. This paper investigates whether it is possible to improve out-of-sample predict...
Defined as increased sensitivity to losses, loss aversion is often conceptualized as a cognitive bias. However, findings that loss aversion has an attentional or emotional regulation component suggest that it may instead reflect differences in information processing. To distinguish these alternatives, we applied the drift-diffusion model (DDM) to c...
In the classic gain/loss framing effect, describing a gamble as a potential gain or loss biases people to make risk-averse or risk-seeking decisions, respectively. The canonical explanation for this effect is that frames differentially modulate emotional processes, which in turn leads to irrational choice behavior. Here, we evaluate the source of f...
In the classic gain/loss framing effect, describing a gamble as a potential gain or loss biases people to make risk-averse or risk-seeking decisions, respectively. The canonical explanation for this effect is that frames differentially modulate emotional processes – which in turn leads to irrational choice behavior. Here, we evaluate the source of...
A basic problem in empirical economics involves using data from one domain to make out-of-sample predictions for a different, but related environment. When the choice data are binary, a canonical method for making these types of predictions is the logistic choice model. This paper investigates whether it is possible to improve out-of-sample predict...
A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two s...
According to many studies, the ventromedial prefrontal cortex (VMPFC) encodes the subjective value of disparate rewards on a common scale. Yet, a host of other reward factors-likely represented outside of VMPFC-must be integrated to construct such signals for valuation. Using functional magnetic resonance imaging (fMRI), we tested whether the inter...
This chapter reviews what is known about how the brain computes stimulus values during the process of making simple choices. Stimulus values provide a measure of the expected benefit of consuming the different options, independently of the action costs required to get them. Although they are only one of several value signals computed at the time of...
Understanding how the brain computes value is a basic question in neuroscience. Although individual studies have driven this
progress, meta-analyses provide an opportunity to test hypotheses that require large collections of data. We carry out a meta-analysis
of a large set of functional magnetic resonance imaging studies of value computation to ad...
The ventromedial prefrontal cortex (vmPFC) plays a critical role in processing appetitive stimuli. Recent investigations have shown that reward value signals in the vmPFC can be altered by emotion regulation processes; however, to what extent the processing of positive emotion relies on neural regions implicated in reward processing is unclear. Her...
The Fall 2011 issue of this journal published a
two-paper section on “Neuroeconomics.” One
paper, by Ernst Fehr and Antonio Rangel, clearly
and concisely summarized a small part of the fast-growing
literature. The second paper, “It’s about
Space, It’s about Time, Neuroeconomics, and the
Brain Sublime,” by Marieke van Rooij and Guy Van
Orden, is bea...
The study of stroke patients with modern lesion-symptom analysis techniques has yielded valuable insights into the representation of spatial attention in the human brain. Here we introduce an approach-multivariate pattern analysis-that no longer assumes independent contributions of brain regions but rather quantifies the joint contribution of multi...
A sizable body of evidence has shown that the brain computes
several types of value-related signals to guide decision making,
such as stimulus values, outcome values, and prediction errors.
A critical question for understanding decision-making
mechanisms is whether these value signals are computed using
an absolute or a normalized code. Under an ab...
The social and neural sciences share a common interest in understanding the mechanisms that underlie human behaviour. However, interactions between neuroscience and social science disciplines remain strikingly narrow and tenuous. We illustrate the scope and challenges for such interactions using the paradigmatic example of neuroeconomics. Using qua...
A sizable body of evidence has shown that the brain computes several types of value-related signals to guide decision making, such as stimulus values, outcome values, and prediction errors. A critical question for understanding decision-making mechanisms is whether these value signals are computed using an absolute or a normalized code. Under an ab...
A core goal for marketers is effective segmentation: partitioning a brand's or product's consumer base into distinct and meaningful groups with differing needs. Traditional segmentation data include factors like geographic location, demographics, and shopping history. Yet, research into the cognitive and affective processes underlying consumption d...
To dissociate a choice from its antecedent neural states, motivation associated with the expected outcome must be captured in the absence of choice. Yet, the neural mechanisms that mediate behavioral idiosyncrasies in motivation, particularly with regard to complex economic preferences, are rarely examined in situations without overt decisions. We...
Activation in frontopolar cortex (FPC; BA 10) has been associated both with attending to mental states and with integrating multiple mental relations. However, few previous studies have manipulated both of these cognitive processes, precluding a clear functional distinction among regions within FPC. To address this issue, we developed an fMRI task...
Investigating the neuroanatomy of spatial neglect with multi-voxel pattern analysis
Analyzing distributed patterns of brain activation using multivariate pattern analysis (MVPA) has become a popular approach for using functional magnetic resonance imaging (fMRI) data to predict mental states. While the majority of studies currently build separate classifiers for each participant in the sample, in principle a single classifier can...
Adaptive behavior frequently requires planning, or the ability to anticipate the consequences of actions and modify behavior accordingly. Situations that necessitate planning pervade our daily lives: engaging in strategic social interactions, determining the best route to an unfamiliar location, scheduling meetings in the midst of a hectic day, amo...
For effective decision making, individuals must be able to form subjective values from many types of information. Yet, the neural mechanisms that underlie potential differences in value computation across different decision scenarios are incompletely understood. Here, we used functional magnetic resonance imaging (fMRI), in conjunction with the mac...
Would you be willing to pay more for a new television the same day you bought a new house? Would you be more likely to purchase that television if it was marked on sale? Most individuals respond affirmatively to questions of this form, likely because they use a “reference point” to help with evaluating their options. A common example is when owners...
How can we use neuroscience to better understand economic behavior? By quelling concerns about the nascent field of neuroeconomics, the authors defend future integrations of the biological and social sciences.
Although there have been many recent studies of the housing market and the possible housing bubble, very few studies take a micro-oriented approach. We construct a repeat-sales housing price index from a new data set for Irvine, California to understand recent trends in its housing market. Our analysis for 1984 to 2003 suggests that Irvine’s housin...
Questions
Question (1)
I am curious because it seems like very few fMRI papers become known to the general economics community, and many of the those known were published at least 5 or 6 years ago.