O TROS SERVICIOS DISPONIBLES PARA EL ESTUDIANTE

While the human brain consists of structurally separable brain areas, the functional specificity of a single brain region is not clear-cut. Further, since the different brain regions are heavily connected with each other, a single cognitive process is often performed by a network of interacting brain areas. Here we limit our review to two central neuronal networks that relate to affective processing (the affective salience network) and deliberation (the executive-control system).

Increases in Affective Salience Network with Gains and Losses

The neuroscience literature indicates some specificity to the processing of positive and negative events. The processing of positive events and rewards is closely related to the functioning of the neurotransmitter dopamine. The dopaminergic neurons in the midbrain project to multiple brain areas, such as the striatum and the medial orbitofrontal cortex (mOFC), which are often reported to reflect valuation. For instance, these brain regions are known to activate for the receipt of both primary and secondary rewards, such as drinks (Berns, et al., 2001;

Plassmann, et al., 2008) and financial rewards (Delgado, et al., 2003; Knutson, et al., 2000; O'Doherty, et al., 2001; Thut, et al., 1997), and they also reflect the hedonic value of rewards (de Araujo, et al., 2003; Kringelbach, 2005; Plassmann, et al., 2008). In line with the behavioral reference dependence of valuation, the reward circuitry also processes outcomes largely in a reference dependent manner, and a variety of contextual aspects have been shown to influence the

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evaluation of received outcomes, such as other possible outcomes (Breiter, et al., 2001) and the outcomes of others (Fliessbach, et al., 2007)²⁹.

Dopamine has an important role in guiding behavior (Schultz &

Dickinson, 2000). In general, increased dopamine activity at the time of the receipt of rewards, as reflected in the midbrain and the striatum, reinforces the behaviors that lead to the rewarding outcomes. Indeed, recent neuroscience literature already provides some initial evidence that the reinforcement signals in the dopamine system (or the striatum) are linked to future risky choices (Cohen, 2008;

Kuhnen & Knutson, 2005). Thus, based on the role of dopamine both in receipt of rewards and in guiding future behavior, the dopamine system and related brain regions are a good candidate for driving the increases in risk appetite after prior gains.

The negative affective brain mechanisms are less consistent across different studies in neuroscience. Multiple experiments show that the lateral parts of the OFC have increased activity when punishments are received (see Kringelbach, 2005 for a review). In contrast, other studies report that negative monetary outcomes decrease activity in the reward structures, such as the striatum (Tom, et al., 2007), or may even evoke activity in other affective brain structures such as the amygdala or the anterior insula (Kuhnen & Knutson, 2005;

Yacubian, et al., 2006). The negatively valenced insula reaction also predicts an increase in risk aversion (Kuhnen & Knutson, 2005), which is suggested to indicate the role of negative affect in guiding future choice behavior.

Though the insula is often related to negative experiences, converging evidence indicates that the anterior insula reflects also positive affective arousal.

This reaction in the anterior insula when experiencing subjective emotions co-occurs frequently with emotional parts of the anterior cingulate cortex (ACC). As summarized by Craig (2009), this network is consistently activated in studies that include affective arousal with a vast range of different types of emotions, ranging from love and happiness to anger, disgust, and social exclusion. Similar to other affective brain regions, also the anterior insula and the ACC have been linked to risky decision making in multiple studies, though there is little convergence in the conclusions—while some researchers report a positive correlation between anterior insula activity and safe choices (Campbell-Meiklejohn, Woolrich,

29 See Section 2.3 for more detailed information.

Path Dependence in Risky Choice Affective and Deliberative Processes in Brain and Behavior 53 Passingham, & Rogers, 2008; Knutson & Bossaerts, 2007; Liu et al., 2007), others find a negative correlation (Clark, Lawrence, Astley-Jones, & Gray, 2009; Paulus, Rogalsky, Simmons, Feinstein, & Stein, 2003; Platt & Huettel, 2008; Xue, Lu, Levin,

& Bechara, 2010). For the ACC the results seem to be more consistent, pointing towards positive correlation between activity level and risky choices (Christopoulos, Tobler, Bossaerts, Dolan, & Schultz, 2009; Cohen, Heller, &

Ranganath, 2005).

Earlier we proposed that high involvement of affective processes increases path dependence in risky choice, and that the affective reaction related to gains and losses increases risk appetite. Based on the review of the neuroscience literature on affective brain mechanisms, we form the following hypotheses:

Hypothesis 1a: The affect-related, interconnected affective salience network, consisting of the midbrain, striatum, insula, parts of ACC, thalamus, and amygdala (Seeley et al., 2007), has stronger activity when experiencing gains and losses than when the outcome is relatively neutral.

Hypothesis 1b: The activity in the affective salience network correlates positively with risky choices.

Decreases in Executive-Control Mechanisms with Gains and Losses

The brain has an interconnected network of brain regions that exert control over behavior. This network, including brain areas such as the dorsolateral prefrontal cortex (DLPFC), the ventrolateral prefrontal cortex (VLPFC), and lateral parietal cortices (Seeley, et al., 2007), is related to multiple controlling actions, ranging from inhibiting the execution of planed motor responses (Liddle, Kiehl, & Smith, 2001) to exerting self-control over dietary choices (Hare, Camerer, & Rangel, 2009).

Previous research in neuroeconomics indicates the relevance of this network for controlling risky choices. For instance, Campbell-Meiklejohn et al. (2008) report increased activity in the parietal cortices when people decide to stop the risky behavior of chasing previous losses, thus indicating the role of the control network for increasing risk aversion in behavior. Moreover, two recent experiments show the causal relation between the right DLPFC and decreasing risk appetite. Knoch et al. (2006) temporarily block brain activity in the right DLPFC by using magnetic

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field pulses (transcranial magnetic stimulation, TMS). This disruption in the activity of the right DLPFC leads to a decreasing number of safe choices in comparison to a control group with intact activity in the right DLPFC. Fecteau et al. (2007) enhance the activity in the right DLPFC by using direct current stimulation technique, which lead to an increasing amount of safe choices.

In line with the second part of our proposition, we ask whether gain and loss experiences are related to decreased level of deliberative processes relative to more neutral outcomes and whether this decrease in deliberate processes is related to stronger path dependence in risky choices. In other words, we expect to see more activity in the executive-control network after neutral outcomes than when gains and losses are experienced. Hence, we form the following hypotheses:

Hypothesis 2a: The deliberation-related, interconnected executive-control network, consisting of DLPFC, VLPFC, and lateral parietal cortices (including intraparietal lobule), has stronger activity related to neutral outcomes than when experiencing gains and losses.

Hypothesis 2b: The activity in the executive-control mechanisms correlates positively with safe choices.