Learning-Related Human Brain Activations Reflecting Individual Finances

Abstract

A basic tenet of microeconomics suggests that the subjective value of financial gains decreases with increasing assets of individuals ("marginal utility"). Using concepts from learning theory and microeconomics, we assessed the capacity of financial rewards to elicit behavioral and neuronal changes during reward-predictive learning in participants with different financial backgrounds. Behavioral learning speed during both acquisition and extinction correlated negatively with the assets of the participants, irrespective of education and age. Correspondingly, response changes in midbrain and striatum measured with functional magnetic resonance imaging were slower during both acquisition and extinction with increasing assets and income of the participants. By contrast, asymptotic magnitudes of behavioral and neuronal responses after learning were unrelated to personal finances. The inverse relationship of behavioral and neuronal learning speed with personal finances is compatible with the general concept of decreasing marginal utility with increasing wealth.

How learning shapes the empathic brain

“…We used a linear regression model to compare learning-related changes in emotion ratings in the experimental vs. the control group. To account for potential differences between early and late learning stages (25,26), we also compared the effects in the first (trials 1-10) and the second half (trials [11][12][13][14][15][16][17][18][19][20] of the intervention. Emotions toward the out-group member (experimental group) became more positive than those toward the in-group member (control group), in particular in the first half of the intervention [Treatment (experimental/control group) × Trial (trials 1-20) × Half (first/second half), T = 2.1, P = 0.03; Treatment × Trial interaction, first half, T = −1.95, P = 0.05 (Fig.…”

Neural basis of the undermining effect of monetary reward on intrinsic motivation

“…As such, the undermining effect may involve the interaction of two different types of subjective values when one succeeds at a task: the extrinsic value of obtaining a reward and the intrinsic value of achieving success. Many neuroscience studies have revealed that a dopaminergic reward network plays a pivotal role in representing and updating various types of subjective valuation (10)(11)(12)(18)(19)(20)(21)(22)(23)(24). In particular, recent studies have suggested that activation in response to feedback in the anterior part of the striatum (caudate head) is modulated by one's subjective belief in determining the outcome (23,25), which is considered a key psychological factor in the undermining effect (3-5).…”

Introduction

“…Other studies have added more information to the understanding of the process of financial decision, showing that it involves the participation of orbitofrontal cortex, medial prefrontal cortex (MPFC), amygdala, nucleus accumbens and many other neural structures (e.g., Bland and Schaefer, 2011;Burgess et al, 2011;Breiter et al, 2001;Cohen et al, 2007Cohen et al, , 2008Davis et al, 2011;FitzGerald et al, Gehring and Willoughby, 2002;Knutson et al, 2003Kuhnen and Knutson, 2005;Knutson and Bossaerts, 2007;McClure et al, 2004;Preuschoff et al, 2006a,b;Samanez-Larkin et al, 2010;Tobler et al, 2007). Based on these results, and Rocha (2013) proposed that various neural circuits are recruited to handle the many tasks required by financial decision-making, such as aversion, risk and benefit assessments and analyses of many other variables such as stock price, portfolio value evolution, market volatility, etc.…”

“…Although EEG has been used to study brain correlates of financial decision-making (Bland and Schaefer, 2011;Cohen et al, 2007Cohen et al, , 2008Davis et al, 2011;Gehring and Willoughby, 2002), Functional Magnetic Resonance Imaging (fMRI) has been the tool of choice to investigate decision-making (e.g., Burgess et al, 2011;Breiter et al, 2001;Frydman et al, 2010;Huetell et al, 2006;Kerstin et al, 2006;Knutson et al, 2003Kuhnen and Knutson, 2005;Knutson and Bossaerts, 2007;Knutson, 2007;McClure et al, 2004McClure et al, , 2005McClure et al, , 2006Polezzi et al, 2010;Preuschoff et al, 2006a,b;Samanez-Larkin et al, 2010;Seymour et al, 2008;Tobler et al, 2007). Introduction fMRI has high spatial discriminative power but very poor temporal resolution.…”