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The dual-process theory of action control postulates that there are two competitive and complementary mechanisms that control our behavior: a goal-directed system that executes deliberate actions, explicitly aimed toward a particular outcome, and a habitual system that autonomously execute well-learned actions, typically following an encounter with a previously associated cue. In line with dual-process theory, animal studies have provided convincing evidence for dissociable neural mechanisms, mainly manifested in cortico-striatal regions, involved in goal-directed and habitual action control. While substantial progress has been made in characterizing the neural mechanism underlying habit learning in animals, we still lack knowledge on how habits are formed and maintained in the human brain. Thus far only one study, conducted more than a decade ago by Tricomi et al. (2009), has been able to induce habitual behavior in humans via extensive training. This study also implicated the posterior putamen in the process, using functional magnetic resonance imaging (fMRI). However, recent attempts to replicate the behavioral results of this study were not successful. This leaves the research of human habits, and particularly the research of their formation through extensive repetition, as well as their neural basis, limited and far behind the animal research in the field. This motivated us to (1) attempt to replicate the behavioral and imaging main findings of Tricomi et al., (2) identify further functional and microstructural neural modifications associated with habit formation and manifestation, and (3) investigate the relationships between functional and structural plasticity and individual differences in habit expression. To this end, in this registered report we used Tricomi et al.’s free-operant task along with multi-modal MRI methods in a well-powered sample (n=123). In this task participants’ sensitivity to outcome devaluation (an index of goal-directed/habitual action

Recent evidence suggests that both novelty and uncertainty act as potent features guiding exploration. However, these variables are often conflated with each other experimentally, and an understanding of how these attributes interact to regulate the balance between exploration and exploitation has proved elusive. Using a novel task designed to decouple stimulus novelty and estimation uncertainty, we identify separable behavioral and neural mechanisms by which exploration is colored. We show that uncertainty was avoided except when the information gained through exploration could be reliably exploited in the future. In contrast, and contrary to existing theory, novel options grew increasingly attractive relative to familiar counterparts irrespective of the opportunity to leverage their consequences and despite the uncertainty inherent to novel options. These findings led us to develop a formal computational framework in which uncertainty directed choice adapts to the prospective utility of exploration, while novel stimuli persistently draw favor as a result of inflated reward expectations biasing an exploitative strategy. Crucially, novelty is proposed to actively modulate uncertainty processing, effectively blunting the influence of uncertainty in shaping the subjective utility ascribed to novel stimuli. Both behavioral data and fMRI activity sampled from the ventromedial prefrontal cortex, frontopolar cortex and ventral striatum validate this model, thereby establishing a computational account that can not only explain behavior but also shed light on the functional contribution of these key brain regions to the exploration/exploitation trade-off. Our results point to multiple strategies and neural substrates charged with balancing the explore/exploit dilemma, with each targeting distinct aspects of the decision problem to foster a manageable decomposition of an otherwise intractable task.

Adaptive behavior in real-world environments demands that choices integrate over several variables, including the novelty of the options under consideration, their expected value, and uncertainty in value estimation. We recorded neurons from the human pre-supplementary motor area (preSMA), ventromedial prefrontal cortex (vmPFC) and dorsal anterior cingulate to probe how integration over decision variables occurs during decision-making. In contrast to the other areas, preSMA neurons not only represented separate pre-decision variables for each choice option, but also encoded an integrated utility signal and, subsequently, the decision itself. Conversely, post-decision related encoding of variables for the chosen option was more widely distributed and especially prominent in vmPFC. Our findings position the human preSMA as central to the implementation of value-based decisions.