Metacognition supports reflection upon and control of other cognitive processes. Despite metacognition occupying a central role in human psychology, its neural substrates remain underdetermined, partly due to study-specific differences in task domain and type of metacognitive judgement under study. It is also unclear how metacognition relates to other apparently similar abilities that depend on recursive thought such as theory of mind or mentalising. Now that neuroimaging studies of metacognition are more prevalent, we have an opportunity to characterise consistencies in neural substrates identified across different analysis types and domains. Here we used quantitative activation likelihood estimation methods to synthesise findings from 47 neuroimaging studies on metacognition, divided into categories based on the target of metacognitive evaluation (memory and decision-making), analysis type (judgement-related activation, confidence-related activation, and predictors of metacognitive sensitivity), and, for metamemory judgements, temporal focus (prospective and retrospective). A domain-general network, including medial and lateral prefrontal cortex, precuneus, and insula was associated with the level of confidence in self-performance in both decision-making and memory tasks. We found preferential engagement of right anterior dorsolateral prefrontal cortex in metadecision experiments and bilateral parahippocampal cortex in metamemory experiments. Results on metacognitive sensitivity were inconclusive, likely due to fewer studies reporting this contrast. Finally, by comparing our results to meta-analyses of mentalising, we obtain evidence for common engagement of the ventromedial and anterior dorsomedial prefrontal cortex in both metacognition and mentalising, suggesting that these regions may support second-order representations for thinking about the thoughts of oneself and others.

Ambivalent affective states, such as bittersweetness, nostalgia, and longing, which are felt as having both positive and negative aspects, are an important component of human experience but have received little attention. The most influential theoretical frameworks in affective neuroscience focus largely on univalenced states. As a result, it is not known whether ambivalent affect corresponds to a simultaneously positive and negative valenced state or whether it results from a rapid vacillation between positive and negative states. Here we hypothesize that ambivalent affect involves both mechanisms, that is, rapid vacillation and simultaneity of positive and negative affect, albeit at different neurobiological levels. Rapidly vacillating univalent emotions could give rise to an ambivalent feeling, a mechanism that depends on brainstem nuclei that facilitate rapid action programs of emotional behavior while inhibiting opposing behaviors. This reciprocal inhibition prevents organisms from simultaneously implementing responses to conflicting emotions but also allows for rapid switching between emotions triggered by counterfactual thinking and rapid reappraisal of situations. We propose that as these transitions occur and respective interoceptive information reaches the insular cortex, further processing of this “emotional moment” would allow separate emotional events to be experienced as one “mixed” and integrated feeling.

Engaging with narratives involves a complex array of cognitive and affective processes. These processes make stories persuasive in ways that standard arguments are not, though the underlying reasons for this remain unclear. Transportation theory proposes a potential explanation for this: narratives are processed in a way which makes individuals feel immersed in the world of a story, which in turn leads people to resonate emotionally with the events of the story. Recent fMRI studies have shown that the posterior medial cortex (PMC) and anterior insula (AI) play important roles in understanding the meaning of stories and experiencing the feelings they produce. In this study, we aimed to explore the AI’s and PMC’s role in narrative processing by measuring their functional connectivity with the rest of the brain during story listening, and how connectivity changes as a function of narrative transportation and the persuasiveness of the story. We analyzed data from 36 right-handed subjects who listened to two stories, obtained from podcasts, inside the fMRI scanner. After the scan, subjects were asked a series of questions, including a measure of how transported into the story they felt, how likely they would be to donate to causes related to the messages of the stories. We used searchlight multivariate pattern analysis (MVPA) to classify functional connectivity maps using seeds in both the AI and PMC and to compare these maps between participants who differed in transportation and prosocial intention. We found that connectivity to various regions successfully distinguished between high and low ratings on each of these behavioral measures with accuracies over 75%. However, only one pattern of connectivity was consistent across both stories: PMC-inferior frontal gyrus connectivity successfully distinguished high and low ratings of narrative transportation in both stories. All other findings were not consistent across stories. Instead, we found that patterns of connectivity may relate more to the specific content of the story rather than to a universal way in which narratives are processed.

Video gaming and Internet use have become a part of the everyday lives of many individuals, especially during adolescence. Given the health concerns related to problematic gaming behaviors, gaming disorder (GD) has been included in the version of the 11th edition of The International Classification of Diseases (ICD-11) ratified by the secretariat of the World Health Organization. Given these considerations and others (including debate regarding the most appropriate classification of GD and how best to prevent and treat the condition), there is a need for further research into GD. Specifically, we suggest that researching intermediate phenotypes focusing on cognitive and neurobiological function may help clarify GD’s relationships to other addictive disorders and more accurately define their relationships with core and associated features of GD. Overlaps in neural activity, cognitive functioning, and other features suggest that GD shares similarities with gambling and substance-use disorders and may best be classified as an addictive disorder. Individuals with GD differ from those with regular game use (RGU) on neurocognitive levels. However, concerns have been raised with respect to the differences between GD and substance-use disorders in certain dimensional features, such as tolerance. Additionally, it has been argued that differences between GD and RGU may not be fully captured by nomenclature systems like the ICD-11. Nonetheless, individuals seek treatment for help with GD, despite the limited data available for effective treatments. As more data are gathered from investigations of GD, they should be translated into refining criteria for GD and optimizing interventions.