Comportamiento de riesgo, impulsividad y toma de decisiones ante eventos catastróficos. Bases neurobiológicas y conectividad efectiva como factores predictivos y de prevención

Laburpena

Decision-making is a complex process supported by multiple brain networks responsible for valuing action alternatives, controlling behavior, and evaluating outcomes to learn from experience. Neurobiological models of decision-making posit that the socioemotional or reward brain system plays a crucial role in assigning value to different behavioral options. During this process, potential outcomes are evaluated based on the expected benefits and costs, uncertainty associated with the decision, and the time elapsed between the action and the consequences. Due to this, and given their subjective nature, personality factors such as impulsivity and sensitivity to rewards and punishments also play a decisive role in the valuation of choice options. Once potential courses of action have been evaluated, the cognitive control system facilitates behavior implementation. However, not all decisions lead to adaptive actions, as occurs in risk behavior, which in any of its dimensions entails choosing an alternative that involves a high probability of negative consequences for the individual. Given the importance of such behaviors, various decision-making models have postulated the existence of a dual processing mechanism in their attempt to explain risk behavior. In essence, two brain networks have been hypothesized, one for cognitive control and the other for reward processing. Additionally, due to the complexity of this process, factors like social context, emotions, and personality traits fundamentally influence risky decisions. Once the action has been performed, its consequences are evaluated to assign it a value and learn from the experience. Brain areas responsible for processing rewards and punishments come into play during outcome exposure, showing anticipatory activity before obtaining the outcome. In fact, anticipation of future situations is a key element for adaptive behavior, especially in the face of unexpected outcomes with unpredictable consequences. Considering the above and given the influence of emotional states and personal characteristics throughout decision-making stages, it is not surprising that interventions designed to regulate these factors, such as mindfulness-based programs, are effective in improving adaptive behavior. Specifically, mindfulness practice has been shown to be effective in reducing risk behavior and enhancing emotional regulation skills, well-being, and overall psychological health. Despite the evidence regarding both contextual and personal factors that determine whether the choice of behavior is more or less functional, further research is needed to clarify how the neurocognitive and personality systems involved in the different stages of decision-making are configured. Additionally, understanding how changes in these systems allow anticipation and processing of unexpected outcomes, and prevent maladaptive behavior is crucial. The main aim of this thesis is to shed light on the aforementioned aspects using real and everyday risk contexts. A daily example of decision-making where risky behaviors can be observed with unpredictable and catastrophic outcomes may be provided by traffic environments. For this reason, and due to its high ecological validity and generalizability, driving is used to address the aims of the thesis studies. Study 1 explores the neuroanatomical bases of risky driving behavior in real-life situations and their relationship with cognitive impulsivity and sensitivity to rewards and punishments. The results indicate a trend towards lower total gray matter volume as the level of risk increases. It is also observed that risky drivers show a lower volume in regions that are part of the cognitive control and reward brain networks, such as the frontal, superior parietal and temporal cortices, parahippocampal and fusiform gyri, insula, cerebellum, and ventral striatum. On the other hand, we observe that even in the absence of differences in personality traits, impulsivity and sensitivity to rewards and punishments are differently related to the structures of the control and reward networks, depending on the level of risk in driving. In individuals with a higher propensity for risktaking, we find lower absolute correlations between brain volume and personality traits. Overall, results support the dual model of risk behavior and indicate that there is an alteration in the configuration of neural circuits involved in reward valuation, action implementation, and behavior regulation in risky individuals. Study 2 investigates the brain processing of catastrophic events. For this purpose, the periods before and after the occurrence of accidents in simulated driving contexts have been studied. Brain activity, estimated through high-density electroencephalography (EEG) recording, and the effective connectivity of the seven main brain networks (VN: visual network; SMN: somatomotor network; LN: limbic network, DAN: dorsal attention network; VAN: ventral attention network; FPN: frontoparietal network; DMN: default mode network) were analyzed during both periods. The results show that before the accident occurs, the inferior parietal and anterior cingulate cortices and the insula are activated. Additionally, causal activation flow or effective connectivity between nodes of the VAN and DAN, and within nodes of the limbic network occurs. On the other hand, immediately after the accident, the orbitofrontal, inferior parietal, and anterior cingulate cortices, and the superior and middle frontal gyri are activated. Greater effective connectivity between networks, from the VAN to the SMN, and within nodes, from nodes of the visual network, VAN, and DMN to nodes of the frontoparietal, attentional, and limbic networks, also occurs. These patterns of brain activity and effective connectivity suggest that the activation of salience and emotional processing enables the anticipation of catastrophic events such as accidents. Moreover, once an accident has occurred, control processes are initiated to adapt behavior to the new environmental demands. Study 3 explores the neuroanatomical effects of a mindfulness-based intervention and its relationship with dispositional mindfulness and impulsivity. Our results indicate that mindfulness training improves dispositional mindfulness. Additionally, the change in mindfulness skills after the intervention is related to changes in impulsivity levels. Furthermore, we observe that mindfulness training leads to a reduction in the caudate nucleus volume, which in turn is related to lower positive urgency. That is, mindfulness training improves the ability to observe one's own sensations and perceptions and the ability to let thoughts and emotions pass, without clinging or reacting to them. In addition, it produces changes in brain structure that are related to a decrease in impulsivity levels, reducing the tendency to act rashly in situations that generate positive emotions. Overall, our results show that cognitive control, emotional processing, and reward brain systems act interconnectedly in the different stages of decision-making, from preference formation and action selection to anticipation and valuation of outcomes and behavior regulation. Moreover, impulsivity, sensitivity to rewards and punishments, and dispositional mindfulness are also underpinned by these neurocognitive systems and influence the decision-making process and adaptive behavior.