Metacognition and the effect of incentive motivation in two compulsive disorders: Gambling disorder and obsessive-compulsive disorder.

AIMS: Compulsivity is a common phenotype among psychiatric disorders, such as obsessive-compulsive disorder (OCD) and gambling disorder (GD). Deficiencies in metacognition, such as the inability to estimate one's performance via confidence judgments could contribute to pathological decision-making. Earlier research has shown that patients with OCD exhibit underconfidence, while patients with GD exhibit overconfidence. Moreover, it is known that motivational states (e.g. monetary incentives) influence metacognition, with gain (respectively loss) prospects increasing (respectively decreasing) confidence. Here, we reasoned that OCD and GD symptoms might correspond to an exacerbation of this interaction between metacognition and motivation. METHODS: We hypothesized GD's overconfidence to be exaggerated during gain prospects, while OCD's underconfidence to be worsened in loss context, which we expected to see represented in ventromedial prefrontal cortex (VMPFC) blood-oxygen-level-dependent activity. We tested those hypotheses in a task-based functional magnetic resonance imaging (fMRI) design (27 patients with GD, 28 patients with OCD, 55 controls). The trial is registered in the Dutch Trial Register (NL6171). RESULTS: We showed increased confidence for patients with GD versus patients with OCD, which could partly be explained by sex and IQ. Although our primary analyses did not support the hypothesized interaction between incentives and groups, exploratory analyses did show increased confidence in patients with GD specifically in gain context. fMRI analyses confirmed a central role for VMPFC in the processing of confidence and incentives, but no differences between the groups. CONCLUSION: Patients with OCD and those with GD reside at opposite ends of the confidence spectrum, while no interaction with incentives was found, nor group differences in neuronal processing of confidence.

Using network models in person-centered care in psychiatry: How perspectivism could help to draw boundaries.

In this paper, we explore the conceptual problems that arise when using network analysis in person-centered care (PCC) in psychiatry. Personalized network models are potentially helpful tools for PCC, but we argue that using them in psychiatric practice raises boundary problems, i.e., problems in demarcating what should and should not be included in the model, which may limit their ability to provide clinically-relevant knowledge. Models can have explanatory and representational boundaries, among others. We argue that perspectival reasoning can make more explicit what questions personalized network models can address in PCC, given their boundaries.

Motivational signals disrupt metacognitive signals in the human ventromedial prefrontal cortex.

A growing body of evidence suggests that, during decision-making, BOLD signal in the ventromedial prefrontal cortex (VMPFC) correlates both with motivational variables - such as incentives and expected values - and metacognitive variables - such as confidence judgments - which reflect the subjective probability of being correct. At the behavioral level, we recently demonstrated that the value of monetary stakes bias confidence judgments, with gain (respectively loss) prospects increasing (respectively decreasing) confidence judgments, even for similar levels of difficulty and performance. If and how this value-confidence interaction is reflected in the VMPFC remains unknown. Here, we used an incentivized perceptual decision-making fMRI task that dissociates key decision-making variables, thereby allowing to test several hypotheses about the role of the VMPFC in the value-confidence interaction. While our initial analyses seemingly indicate that the VMPFC combines incentives and confidence to form an expected value signal, we falsified this conclusion with a meticulous dissection of qualitative activation patterns. Rather, our results show that strong VMPFC confidence signals observed in trials with gain prospects are disrupted in trials with no - or negative (loss) - monetary prospects. Deciphering how decision variables are represented and interact at finer scales seems necessary to better understand biased (meta)cognition.

The Network Theory of Psychiatric Disorders: A Critical Assessment of the Inclusion of Environmental Factors.

Borsboom and colleagues have recently proposed a "network theory" of psychiatric disorders that conceptualizes psychiatric disorders as relatively stable networks of causally interacting symptoms. They have also claimed that the network theory should include non-symptom variables such as environmental factors. How are environmental factors incorporated in the network theory, and what kind of explanations of psychiatric disorders can such an "extended" network theory provide? The aim of this article is to critically examine what explanatory strategies the network theory that includes both symptoms and environmental factors can accommodate. We first analyze how proponents of the network theory conceptualize the relations between symptoms and between symptoms and environmental factors. Their claims suggest that the network theory could provide insight into the causal mechanisms underlying psychiatric disorders. We assess these claims in light of network analysis, Woodward's interventionist theory, and mechanistic explanation, and show that they can only be satisfied with additional assumptions and requirements. Then, we examine their claim that network characteristics may explain the dynamics of psychiatric disorders by means of a topological explanatory strategy. We argue that the network theory could accommodate topological explanations of symptom networks, but we also point out that this poses some difficulties. Finally, we suggest that a multilayer network account of psychiatric disorders might allow for the integration of symptoms and non-symptom factors related to psychiatric disorders and could accommodate both causal/mechanistic and topological explanations.

The effect of non-invasive brain stimulation on executive functioning in healthy controls: A systematic review and meta-analysis.

In recent years, there has been a heightened interest in the effect of non-invasive brain stimulation on executive functioning. However, there is no comprehensive overview of its effects on different executive functioning domains in healthy individuals. Here, we assessed the state of the field by conducting a systematic review and meta-analysis on the effectiveness of non-invasive brain stimulation (i.e. repetitive transcranial magnetic stimulation and transcranial direct current stimulation) over prefrontal regions on tasks assessing working memory, inhibition, flexibility, planning and initiation performance. Our search yielded 63 studies (n = 1537), and the effectiveness of excitatory and inhibitory non-invasive brain stimulation were assessed per executive functioning task. Our analyses showed that excitatory non-invasive brain stimulation had a small but positive effect on Stop Signal Task and Go/No-Go Task performance, and that inhibitory stimulation had a small negative effect on Flanker Task performance. Non-invasive brain stimulation did not affect performance on working memory and flexibility tasks, and effects on planning tasks were inconclusive.