Thomas H. B. FitzGerald

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The human orbitofrontal cortex is strongly implicated in appetitive valuation. Whether its role extends to support comparative valuation necessary to explain probabilistic choice patterns for incommensurable goods is unknown. Using a binary choice paradigm, we derived the subjective values of different bundles of goods, under conditions of both gain and(More)
This paper considers agency in the setting of embodied or active inference. In brief, we associate a sense of agency with prior beliefs about action and ask what sorts of beliefs underlie optimal behavior. In particular, we consider prior beliefs that action minimizes the Kullback-Leibler (KL) divergence between desired states and attainable states in the(More)
Value-based choices are influenced both by risk in potential outcomes and by whether outcomes reflect potential gains or losses. These variables are held to be related in a specific fashion, manifest in risk aversion for gains and risk seeking for losses. Instead, we hypothesized that there are independent impacts of risk and loss on choice such that,(More)
Estimating the value of potential actions is crucial for learning and adaptive behavior. We know little about how the human brain represents action-specific value outside of motor areas. This is, in part, due to a difficulty in detecting the neural correlates of value using conventional (region of interest) functional magnetic resonance imaging (fMRI)(More)
In a recent article in TICS [1], Seth makes the compelling claim that interoceptive inference (i.e., the approximate Bayesian inference about internal bodily states) underlies body ownership and selfhood. In this letter, we argue that the significance of interoceptive inference extends beyond this. In particular, we emphasise the role of interoceptive(More)
Multiple features of the environment are often imbued with motivational significance, and the relative importance of these can change across contexts. The ability to flexibly adjust evaluative processes so that currently important features of the environment alone drive behavior is critical to adaptive routines. We know relatively little about the neural(More)
This paper considers goal-directed decision-making in terms of embodied or active inference. We associate bounded rationality with approximate Bayesian inference that optimizes a free energy bound on model evidence. Several constructs such as expected utility, exploration or novelty bonuses, softmax choice rules and optimism bias emerge as natural(More)
Postulating that the brain performs approximate Bayesian inference generates principled and empirically testable models of neuronal function-the subject of much current interest in neuroscience and related disciplines. Current formulations address inference and learning under some assumed and particular model. In reality, organisms are often faced with an(More)
Dopamine plays a key role in learning; however, its exact function in decision making and choice remains unclear. Recently, we proposed a generic model based on active (Bayesian) inference wherein dopamine encodes the precision of beliefs about optimal policies. Put simply, dopamine discharges reflect the confidence that a chosen policy will lead to desired(More)