The amygdala was more responsive to fearful (larger) eye whites than to happy (smaller) eye whites presented in a masking paradigm that mitigated subjects' awareness of their presence and aberrant nature. These data demonstrate that the amygdala is responsive to elements of.

In model-based functional magnetic resonance imaging (fMRI), signals derived from a computational model for a specific cognitive process are correlated against fMRI data from subjects performing a relevant task to determine brain regions showing a response profile consistent with that model. A key advantage of this technique over more conventional neuroimaging approaches is that model-based fMRI can provide insights into how a particular cognitive process is implemented in a specific brain area as opposed to merely identifying where a particular process is located. This review will briefly summarize the approach of model-based fMRI, with reference to the field of reward learning and decision making, where computational models have been used to probe the neural mechanisms underlying learning of reward associations, modifying action choice to obtain reward, as well as in encoding expected value signals that reflect the abstract structure of a decision problem. Finally, some of the limitations of this approach will be discussed.

Avoidance learning poses a challenge for reinforcement-based theories of instrumental conditioning, because once an aversive outcome is successfully avoided an individual may no longer experience extrinsic reinforcement for their behavior. One possible account for this is to propose that avoiding an aversive outcome is in itself a reward, and thus avoidance behavior is positively reinforced on each trial when the aversive outcome is successfully avoided. In the present study we aimed to test this possibility by determining whether avoidance of an aversive outcome recruits the same neural circuitry as that elicited by a reward itself. We scanned 16 human participants with functional MRI while they performed an instrumental choice task, in which on each trial they chose from one of two actions in order to either win money or else avoid losing money. Neural activity in a region previously implicated in encoding stimulus reward value, the medial orbitofrontal cortex, was found to increase, not only following receipt of reward, but also following successful avoidance of an aversive outcome. This neural signal may itself act as an intrinsic reward, thereby serving to reinforce actions during instrumental avoidance.

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We recently demonstrated a functional relationship between fMRI responses within the amygdala and the medial prefrontal cortex based upon whether subjects interpreted surprised facial expressions positively or negatively. In the present fMRI study, we sought to assess amygdala-medial prefrontal cortex responsivity when the interpretations of surprised faces were determined by contextual experimental stimuli, rather than subjective judgment. Subjects passively viewed individual presentations of surprised faces preceded by either a negatively or positively valenced contextual sentence (e. g., She just found $500 vs. She just lost $500). Negative and positive sentences were carefully matched in terms of length, situations described, and arousal level. Negatively cued surprised faces produced greater ventral amygdala activation compared to positively cued surprised faces. Responses to negative versus positive sentences were greater within the ventrolateral prefrontal cortex, whereas responses to positive versus negative sentences were greater within the ventromedial prefrontal cortex. The present study demonstrates that amygdala response to surprised facial expressions can be modulated by negatively versus positively valenced verbal contextual information. Connectivity analyses identified candidate cortical-subcortical systems subserving this modulation.

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Although much is known about the neural substrates of reward, the question of whether expectation of different types of reinforcers engage distinct or overlapping brain circuitry has not been addressed definitively. In the present study, human subjects, while being scanned with functional magnetic resonance imaging, performed a simple reward-based action selection task to obtain different magnitudes of either monetary outcomes (winning or losing money) or juice outcomes (pleasant apple juice or an unpleasant salt flavor). At the group level, we found partially overlapping value-related activity within ventromedial prefrontal cortex (vmPFC) during anticipation of juice and money reward outcomes. Analogous results were found in the right anterior insula, except that this region showed negative correlations as a function of increasing expected reward. These results indicate that vmPFC and anterior insula contain overlapping representations of anticipatory value, consistent with the existence of a common currency for the value of expected outcomes in these regions.

Despite the importance of valuing another person's welfare for prosocial behavior, currently we have only a limited understanding of how these values are represented in the brain and, more importantly, how they give rise to individual variability in prosociality. In the present study, participants underwent functional magnetic resonance imaging while performing a prosocial learning task in which they could choose to benefit themselves and/or another person. Choice behavior indicated that participants valued the welfare of another person, although less so than they valued their own welfare. Neural data revealed a spatial gradient in activity within the medial prefrontal cortex (MPFC), such that ventral parts predominantly represented self-regarding values and dorsal parts predominantly represented other-regarding values. Importantly, compared with selfish individuals, prosocial individuals showed a more gradual transition from selfregarding to other-regarding value signals in the MPFC and stronger MPFC-striatum coupling when they made choices for another person rather than for themselves. The present study provides evidence of neural markers reflecting individual differences in human prosociality.R anging from small acts of kindness in daily life to self-sacrificing altruism under life-threatening situations, we often observe large individual differences in how humans value another person's welfare. This differential valuation process seems to be the key to understanding various human prosocial behaviors, which are fundamental to the sustainability of human society (1). The underlying neural mechanisms and their relationship to individual differences in prosociality remain unclear, however.Perhaps the most powerful way of assessing how an outcome is valued is to use an instrumental learning paradigm that examines whether the occurrence of a response increases when it is followed by that outcome (2). The mechanisms underlying this type of learning have been described more formally with a computational model, known as the advantage learning model (3-5), which has been used successfully to reveal the neuroanatomical substrates of subjective valuation (3,4,6). Previous research has further refined the neurobiological model of reinforcement learning by emphasizing the specific roles played by the medial frontal cortex and the striatum; the medial frontal cortex computes the value of the chosen action, whereas the striatum processes reward prediction errors during reinforcement learning (4, 6-10).Unlike our current understanding of the valuation process for self-regarding choices (3, 6-12), it is much less clear whether learning also can be driven by other-regarding values, and whether this other-regarding valuation relies on the same mechanisms of reinforcement learning as those used for self. Moreover, despite the rapidly accumulating research on reward processing in social domains (13-19), the question remains of how neural representation of self-regarding vs. other-regarding values is related to individual differen...