We conclude that existing literature on decision under risk can safely be applied to the problem of compliance with internet scams. Participants’ decisions were highly similar in the two situations, and in both cases were congruent with those of the participants in Kahneman and Tversky’s original paper-based study. Both modified questionnaires were delivered over the internet but one specified the decision outcomes in terms of concrete money, closely mimicking Kahneman and Tversky’s questions, while the other specified the decision outcomes in terms of internet-specific currency. 84 participants answered two different questionnaires, both modified from the one Kahneman and Tversky used to establish the core facts underlying prospect theory. This article aims to uncover whether we approach virtual risky situations differently to concrete ones and through that infer whether we need to consider differences in approaches to Internet and concrete scams. There is a copious literature about risky decisions, but little of it has been explicitly applied to decisions taken on the Internet. One way of looking at scam compliance is to treat it as the result of as a decision under risk, and some scam victims indeed report that they treated the scam as, essentially, a long-odds gamble. Taken together, I present a body of work in this thesis that demonstrates the utility of moving beyond simple tests of value in order to resolve the computational complexity of decision making. The second half of the thesis demonstrates a potential biomarker to target as a circuit-computation-specific therapeutic intervention tailored to those types of decision-making dysfunctions. Furthermore, I developed a novel plasticity measurement tool that is assayed at the neuronal population ensemble level and reveals individual differences in separable decision processes. I demonstrate how plasticity alterations in projections between the infralimbic cortex and the nucleus accumbens are capable of giving rise to long-lasting disruptions of self-control related decision processes in a foraging valuation algorithm independent of and separate from a deliberative valuation algorithm measured within the same trial. Finally, I take a neuromodulation approach and directly alter the strength of synaptic transmission in a circuit-specific manner using optogenetics in mice tested in this neuroeconomic framework. These discoveries can aid in resolving neuropsychiatric disease heterogeneity by moving beyond simple tests of value where complex behaviors that are measured can more accurately reflect the neurally distinct computations that underlie those behaviors. In doing so, I demonstrate how different forms of addiction give rise to unique, lasting vulnerabilities in fundamentally distinct decision-making computations. If multiple, parallel decision-making processes are thought to be intimately related to the heterogeneous ways in which information can be stored in separable neural circuits, I examine how addiction – a disease which is thought to be a disorder of the neurobiological mechanisms of learning and memory – might alter how stored information is processed in separable decision-making systems uniquely using a mouse model of two different forms of addiction. In the second half of this thesis, I demonstrate the utility of behavioral economics in disease-relevant and circuit-based studies. I then translate this approach between human and non-human rodent animal models in order to reveal how multiple, parallel decision-making systems are conserved across species over evolution. In the first half of this thesis, I demonstrate how complex behavioral computations can resolve fundamentally distinct valuation algorithms thought to reside in separable neural circuits. TIME SINK FALLACY SERIESIn this thesis, I present a body of work that takes a neuroeconomics approach through a series of experiments that reveal the complexities of multiple, parallel decision-making systems through complex behaviors by moving beyond simple tests of value. Such is the framework of recent theories in neuroeconomics, which suggest that decisions are multi-faceted and action-selection processes can arise from fundamentally distinct circuit-specific neural computations. The decision-making processes that access those different bits of stored information are not singular and occupy separable neural circuits, each of which can operate in parallel with one another, and each of which can confer different information processing properties based on the neural constraints within which a given computation resides. Distinct neural circuits are capable of storing information in many different ways that are better suited for different situations. How the brain processes information when making decisions depends on how that information is stored.
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