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Anxiety disorders are among the most prevalent mental disorders. Present treatments such as cognitive behavior therapy and pharmacological treatments show only moderate success, which emphasizes the importance for the development of new treatment protocols. Non-invasive brain stimulation methods such as repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) have been probed as therapeutic option for anxiety disorders in recent years. Mechanistic information about their mode of action, and most efficient protocols is however limited. Here the fear extinction model can serve as a model of exposure therapies for studying therapeutic mechanisms, and development of appropriate intervention protocols. We systematically reviewed 30 research articles that investigated the impact of rTMS and tDCS on fear memory and extinction in animal models and humans, in clinical and healthy populations. The results of these studies suggest that tDCS and rTMS can be efficient methods to modulate fear memory and extinction. Furthermore, excitability-enhancing stimulation applied over the vmPFC showed the strongest potential to enhance fear extinction. We further discuss factors that determine the efficacy of rTMS and tDCS in the context of the fear extinction model and provide future directions to optimize parameters and protocols of stimulation for research and treatment.

To decide whether or not to participate in an upcoming activity, people can use their memories of intrinsically-motivating or non-intrinsically-motivating experiences during previous participations. To understand the underlying neural mechanism of intrinsic motivation memories, we used a block-design functional magnetic resonance imaging (fMRI) experiment to compare the neural activations during intrinsically-motivating memories versus during non-intrinsically-motivating memories. Results showed that both the ventromedial prefrontal cortex (VMPFC) and anterior cingulate cortex (ACC) were more activated during the recall of intrinsically-motivating memories rather than during the recall of non-intrinsically-motivating memories. Greater negative functional interactions between the VMPFC and ACC were also observed in the intrinsically-motivating situations. These findings suggest that the two complementary neural processes are employed to reconstruct intrinsically-motivating experiences: pleasure (reward related to VMPFC activity) and personal meaning (self-endorsement related to ACC activity).

The orbitofrontal cortex and amygdala are involved in emotion and in motivation, but the relationship between these functions performed by these brain structures is not clear. To address this, a unified theory of emotion and motivation is described in which motivational states are states in which instrumental goal-directed actions are performed to obtain rewards or avoid punishers, and emotional states are states that are elicited when the reward or punisher is or is not received. This greatly simplifies our understanding of emotion and motivation, for the same set of genes and associated brain systems can define the primary or unlearned rewards and punishers such as sweet taste or pain. Recent evidence on the connectivity of human brain systems involved in emotion and motivation indicates that the orbitofrontal cortex is involved in reward value and experienced emotion with outputs to cortical regions including those involved in language, and is a key brain region involved in depression and the associated changes in motivation. The amygdala has weak effective connectivity back to the cortex in humans, and is implicated in brainstem-mediated responses to stimuli such as freezing and autonomic activity, rather than in declarative emotion. The anterior cingulate cortex is involved in learning actions to obtain rewards, and with the orbitofrontal cortex and ventromedial prefrontal cortex in providing the goals for navigation and in reward-related effects on memory consolidation mediated partly via the cholinergic system.

Numerous experiments have recently sought to identify neural signals associated with the subjective value (SV) of choice alternatives. Theoretically, SV assessment is an intermediate computational step during decision making, in which alternatives are placed on a common scale to facilitate value-maximizing choice. Here we present a quantitative, coordinate-based meta-analysis of 206 published fMRI studies investigating neural correlates of SV. Our results identify two general patterns of SV-correlated brain responses. In one set of regions, both positive and negative effects of SV on BOLD are reported at above-chance rates across the literature. Areas exhibiting this pattern include anterior insula, dorsomedial prefrontal cortex, dorsal and posterior striatum, and thalamus. The mixture of positive and negative effects potentially reflects an underlying U-shaped function, indicative of signal related to arousal or salience. In a second set of areas, including ventromedial prefrontal cortex and anterior ventral striatum, positive effects predominate. Positive effects in the latter regions are seen both when a decision is confronted and when an outcome is delivered, as well as for both monetary and primary rewards. These regions appear to constitute a “valuation system,” carrying a domain-general SV signal and potentially contributing to value-based decision making. •Theories of decision making posit a domain-general subjective value signal.•Numerous fMRI studies have tested for correlates of such a signal.•We quantitatively meta-analyze findings from 206 studies.•We identify a “valuation system” in ventromedial PFC and ventral striatum.•Other regions show a mixture of positive and negative effects across experiments.

Nervous systems must encode information about the identity of expected outcomes to make adaptive decisions. However, the neural mechanisms underlying identity-specific value signaling remain poorly understood. By manipulating the value and identity of appetizing food odors in a pattern-based imaging paradigm of human classical conditioning, we were able to identify dissociable predictive representations of identity-specific reward in orbitofrontal cortex (OFC) and identity-general reward in ventromedial prefrontal cortex (vmPFC). Reward-related functional coupling between OFC and olfactory (piriform) cortex and between vmPFC and amygdala revealed parallel pathways that support identity-specific and -general predictive signaling. The demonstration of identity-specific value representations in OFC highlights a role for this region in model-based behavior and reveals mechanisms by which appetitive behavior can go awry. Significance To make adaptive choices based on reward-predicting stimuli, organisms must take into account information about both the value and the specific identity of the reward to be obtained. Using appetizing food odors and pattern-based functional magnetic resonance imaging, we show that the human orbitofrontal cortex encodes future rewards in the form of identity-specific value codes. That is, even if valued the same, different expected rewards, such as pizza and chocolate cake, are differently encoded in this region. We further show that identity-specific and -general value coding regions are functionally linked to distinct regions, providing a novel account for the neural circuitry that underlies integration of both sensory and affective information to guide reward-related behavior.

Recent work on the cognitive regulation of dietary decision-making suggests that regulation can alter both the choices that people make in the moment and longer-lasting preferences. However, it is unclear what mechanisms lead to temporary or lingering changes. To address this question, we used fMRI during a task employing the cognitive regulation of food choice and assessed changes in food preference from baseline to post-regulation. We found evidence that regulation may result in a temporary reconfiguration of the neural drivers of choice, de-emphasizing goal-inconsistent value-related computations in the ventromedial prefrontal cortex and resulting in more goal-consistent changes in value-related computations in the dorsolateral prefrontal cortex (dlPFC). Moreover, we find that the extent to which the dlPFC was recruited to represent different regulatory goals during the moment of choice negatively predicted the extent to which those regulatory goals produced lingering changes in preference. Our results suggest that the recruitment of the dlPFC in the service of regulation may have a downside: it is effective at changing behavior in the moment, but its effects on preferences are transient.

The importance of the amygdala as a salience detector and in emotional learning is now well accepted. The mechanisms that regulate and inhibit the amygdala, however, are less well understood. This review provides evidence from imaging and lesion studies to support the role of the ventromedial prefrontal cortex (vmPFC) as a moderator and inhibitor of the amygdala. The dual inhibition model centres on the broadly defined ventromedial prefrontal cortex (vmPFC) and the distinct role of two of its subcomponents, the rostral anterior cingulate cortex and orbitofrontal cortex. The dual inhibition model posits that these two regions, along with their associated inhibitory pathways, must interact for adequate inhibitory control of the amygdala and emotional regulation. Following a description of the model’s experimental support, it is then proposed as a neuropsychological mechanism for post-traumatic stress disorder (PTSD). Flashbacks, as a defining feature of PTSD, are described in terms of a subcortical orienting network. Finally, there is a discussion of how a neuropsychological understanding of post-traumatic stress disorder (PTSD) might inform a clinician’s approach to treatment and how the dual inhibition model might have a more general application to understanding emotional dysregulation.

Individuals can learn by interacting with the environment and experiencing a difference between predicted and obtained outcomes (prediction error). However, many species also learn by observing the actions and outcomes of others. In contrast to individual learning, observational learning cannot be based on directly experienced outcome prediction errors. Accordingly, the behavioral and neural mechanisms of learning through observation remain elusive. Here we propose that human observational learning can be explained by two previously uncharacterized forms of prediction error, observational action prediction errors (the actual minus the predicted choice of others) and observational outcome prediction errors (the actual minus predicted outcome received by others). In a functional MRI experiment, we found that brain activity in the dorsolateral prefrontal cortex and the ventromedial prefrontal cortex respectively corresponded to these two distinct observational learning signals.

The human mind is equally fluent in thoughts that involve self-generated mental content as it is with information in the immediate environment. Previous research has shown that neural systems linked to executive control (i.e. the dorsolateral prefrontal cortex) are recruited when perceptual and self-generated thoughts are balanced in line with the demands imposed by the external world. Contemporary theories (Smallwood and Schooler, 2015) assume that differentiable processes are important for self-generated mental content than for its regulation. The current study used functional magnetic resonance imaging in combination with multidimensional experience sampling to address this possibility. We used a task with minimal demands to maximise our power at identifying correlates of self-generated states. Principal component analysis showed consistent patterns of self-generated thought when participants performed the task in either the lab or in the scanner (ICC ranged from 0.68 to 0.86). In a whole brain analyses we found that neural activity in the ventromedial prefrontal cortex (vMPFC) increases when participants are engaged in experiences which emphasise episodic and socio-cognitive features. Our study suggests that neural activity in the vMPFC is linked to patterns of ongoing thought, particularly those with episodic or social features. •We identified neural regions associated with patterns of self-generated thought.•Ventromedial prefrontal cortex (vMPFC) activity during episodic social cognition.•VMPFC may play a role in episodic and social features of self-generated thought.