Information integration in perceptual and value-based decisions

Abstract

Research on the psychology and neuroscience of simple, evidence-based choices has \nled to an impressive progress in capturing the underlying mental processes as optimal \nmechanisms that make the fastest decision for a specified accuracy. The idea that \ndecision-making is an optimal process stands in contrast with findings in more complex, \nmotivation-based decisions, focussed on multiple goals with trade-offs. Here, \na number of paradoxical and puzzling choice behaviours have been revealed, posing \na serious challenge to the development of a unified theory of choice. These choice \nanomalies have been traditionally attributed to oddities at the representation of values \nand little is known about the role of the process under which information is integrated \ntowards a decision. In a series of experiments, by controlling the temporal distribution \nof the decision-relevant information (i.e., sensory evidence or value), I demonstrate \nthat the characteristics of this process cause many puzzling choice paradoxes, such as \ntemporal, risk and framing biases, as well as preference reversal. \nIn Chapter 3, I show that information integration is characterized by temporal biases \n(Experimental Studies 1-2, Computational Studies 1-3). In Chapter 4, I examine the \nway the integration process is affected by the immediate decision context (Experimental \nStudies 3-4, Computational Study 4), demonstrating that prior to integration, \nthe momentary ranking of a sample modifies its magnitude. This principle is further \nscrutinized in Chapter 5, where a rank-dependent accumulation model is developed \n(Computational Study 5). The rank-dependent model is shown to underlie preference \nreversal in multi-attribute choice problems and to predict that choice is sensitive, not \nonly to the mean strength of the information, but also to its variance, favouring riskier \noptions (Computational Study 6). This prediction is further confirmed in Chapter 6, in \na number of experiments (Experimental Studies 5-7) while the direction of risk preferences \nis found to be modulated by the cognitive perspective induced by the task \nframing (Experimental Study 8). I conclude that choice arises from a deliberative process \nwhich gathers samples of decision-relevant information, weighs them according \nto their salience and subsequently accumulates them. The salience of a sample is determined \nby i) its temporal order and ii) its local ranking in the decision context, while \nthe direction of the weighting is controlled by the task framing. The implications of \nthis simple, microprocess model are discussed with respect to choice optimality while \ndirections for future research, towards the development of a unified theory of choice, \nare suggested.

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