The online metacognitive control of decisions.

Difficult decisions typically involve mental effort, which scales with the deployment of cognitive (e.g., mnesic, attentional) resources engaged in processing decision-relevant information. But how does the brain regulate mental effort? A possibility is that the brain optimizes a resource allocation problem, whereby the amount of invested resources balances its expected cost (i.e. effort) and benefit. Our working assumption is that subjective decision confidence serves as the benefit term of the resource allocation problem, hence the "metacognitive" nature of decision control. Here, we present a computational model for the online metacognitive control of decisions or oMCD. Formally, oMCD is a Markov Decision Process that optimally solves the ensuing resource allocation problem under agnostic assumptions about the inner workings of the underlying decision system. We demonstrate how this makes oMCD a quasi-optimal control policy for a broad class of decision processes, including -but not limited to- progressive attribute integration. We disclose oMCD's main properties (in terms of choice, confidence and response time), and show that they reproduce most established empirical results in the field of value-based decision making. Finally, we discuss the possible connections between oMCD and most prominent neurocognitive theories about decision control and mental effort regulation.

Mood fluctuations shift cost-benefit tradeoffs in economic decisions.

Mood effects on economic choice seem blatantly irrational, but might rise from mechanisms adapted to natural environments. We have proposed a theory in which mood helps adapting the behaviour to statistical dependencies in the environment, by biasing the expected value of foraging actions (which involve taking risk, spending time and making effort to get more reward). Here, we tested the existence of this mechanism, using an established mood induction paradigm combined with independent economic choices that opposed small but uncostly rewards to larger but costly rewards (involving either risk, delay or effort). To maximise the sensitivity to mood fluctuations, we developed an algorithm ensuring that choice options were continuously adjusted to subjective indifference points. In 102 participants tested twice, we found that during episodes of positive mood (relative to negative mood), choices were biased towards better rewarded but costly options, irrespective of the cost type. Computational modelling confirmed that the incidental mood effect was best explained by a bias added to the expected value of costly options, prior to decision making. This bias is therefore automatically applied even in artificial environments where it is not adaptive, allowing mood to spill over many sorts of decisions and generate irrational behaviours.

Early effects predict trajectories of response to esketamine in treatment-resistant depression.

BACKGROUND: The efficacy of esketamine in treatment-resistant depression (TRD) has been confirmed. However, its administration is expensive and restrictive, with limited knowledge on how long the treatment should be continued. Predicting the treatment outcome would benefit patients and alleviate the global treatment cost. We aimed to define distinct trajectories of treatment response and assess their predictability. METHODS: In this longitudinal study, two independent samples of patients with unipolar or bipolar TRD were treated with esketamine in real-world settings. Depression severity was assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS) before each esketamine administration. Latent class analyses were used to define trajectories of response. RESULTS: In the original sample (N = 50), we identified two classes whose trajectories depicted response and non-response, respectively. The model was validated in the confirmatory sample (N = 55). Class membership was influenced by a few baseline characteristics such as concomitant benzodiazepine medication, number of depressive episodes or polarity. On the other hand, after only two esketamine administrations, the MADRS score predicted the 90-day trajectory of response with an accuracy of 80 %. LIMITATIONS: This observational study is not placebo-controlled. Therefore, its results and their generalizability need to be confirmed in experimental settings. CONCLUSIONS: After the first administrations of esketamine, the MADRS score has a good capacity to predict the most plausible trajectory of response. While thresholds and their predictive values need to be confirmed, this finding suggests that clinicians could base on MADRS scores their decision to discontinue treatment because of poor remaining chances of treatment response.

Reward and punishment learning deficits among bipolar disorder subtypes.

BACKGROUND: Reward sensitivity is an essential dimension related to mood fluctuations in bipolar disorder (BD), but there is currently a debate around hypersensitivity or hyposensitivity hypotheses to reward in BD during remission, probably related to a heterogeneous population within the BD spectrum and a lack of reward bias evaluation. Here, we examine reward maximization vs. punishment avoidance learning within the BD spectrum during remission. METHODS: Patients with BD-I (n = 45), BD-II (n = 34) and matched (n = 30) healthy controls (HC) were included. They performed an instrumental learning task designed to dissociate reward-based from punishment-based reinforcement learning. Computational modeling was used to identify the mechanisms underlying reinforcement learning performances. RESULTS: Behavioral results showed a significant reward learning deficit across BD subtypes compared to HC, captured at the computational level by a lower sensitivity to rewards compared to punishments in both BD subtypes. Computational modeling also revealed a higher choice randomness in BD-II compared to BD-I that reflected a tendency of BD-I to perform better during punishment avoidance learning than BD-II. LIMITATIONS: Our patients were not naive to antipsychotic treatment and were not euthymic (but in syndromic remission) according to the International Society for Bipolar Disorder definition. CONCLUSIONS: Our results are consistent with the reward hyposensitivity theory in BD. Computational modeling suggests distinct underlying mechanisms that produce similar observable behaviors, making it a useful tool for distinguishing how symptoms interact in BD versus other disorders. In the long run, a better understanding of these processes could contribute to better prevention and management of BD.

Origins and consequences of mood flexibility: a computational perspective.

A stable and neutral mood (euthymia) is commended by both economic and clinical perspectives, because it enables rational decisions and avoids mental illnesses. Here we suggest, on the contrary, that a flexible mood responsive to life events may be more adaptive for natural selection, because it can help adjust the behavior to fluctuations in the environment. In our model (dubbed MAGNETO), mood represents a global expected value that biases decisions to forage for a particular reward. When flexible, mood is updated every time an action is taken, by aggregating incurred costs and obtained rewards. Model simulations show that, across a large range of parameters, flexible agents outperform cold agents (with stable neutral mood), particularly when rewards and costs are correlated in time, as naturally occurring across seasons. However, with more extreme parameters, simulations generate short manic episodes marked by incessant foraging and lasting depressive episodes marked by persistent inaction. The MAGNETO model therefore accounts for both the function of mood fluctuations and the emergence of mood disorders.

Medical Students' Learning Process During Simulated Patient Consultations in Psychiatry: A Grounded Theory Study.

INTRODUCTION: Recent changes in psychiatric care and teaching, which limit patient contact for medical students, can be partially overcome by simulation-based education in psychiatry. The authors explored the learning processes of medical students during meetings with simulated patients to inform efforts to improve this teaching. METHODS: After recruiting 81 undergraduate medical students from 3 universities to participate in 6 simulation sessions in psychiatry, the authors purposively sampled 21 students to participate in face-to-face individual semistructured interviews analyzed with constructivist grounded theory. Integration of this analysis with those of the simulation consultation videotapes and the debriefing audiotapes improved the triangulation process. RESULTS: Three organizational themes were identified: developing and structuring representations of psychiatry; integrating subjectivity into learning; and refining and developing psychiatric praxis. Given the broad and in-depth learning that occurs, simulation in psychiatry should respect content validity of SP portrayals to ensure appropriate learning. However, psychological fidelity seems to provide adequate realism while retaining feasibility. Psychiatric simulation also requires the encouragement of student self-confidence and well-being. Within a reflective framework, simulation triggers cognitive reframing, which can alleviate fears and prejudice toward people with mental disorders. CONCLUSIONS: The holistic interactive learning process involved in simulation can address the complexity of the personal and interpersonal features needed in psychiatry.

Effort avoidance as a core mechanism of apathy in frontotemporal dementia.

Apathy is a core symptom in patients with behavioural variant frontotemporal dementia (bvFTD). It is defined by the observable reduction in goal-directed behaviour, but the underlying mechanisms are poorly understood. According to decision theory, engagement in goal-directed behaviour depends on a cost-benefit optimization trading off the estimated effort (related to the behaviour) against the expected reward (related to the goal). In this framework, apathy would thus result from either a decreased appetence for reward, or from an increased aversion to effort. Here, we phenotyped the motivational state of 21 patients with bvFTD and 40 matched healthy controls using computational analyses of behavioural responses in a comprehensive series of behavioural tasks, involving both expression of preference (comparing reward value and effort cost) and optimization of performance (adjusting effort production to the reward at stake). The primary finding was an elevated aversion to effort, consistent across preference and performance tasks in patients with bvFTD compared to controls. Within the bvFTD group, effort avoidance was correlated to cortical atrophy in the dorsal anterior cingulate cortex and to apathy score measured on a clinical scale. Thus, our results highlight elevated effort aversion (not reduced reward appetence) as a core dysfunction that might generate apathy in patients with bvFTD. More broadly, they provide novel behavioural tests and computational tools to identify the dysfunctional mechanisms producing motivation deficits in patients with brain damage.

Vagus nerve stimulation allows to cease maintenance electroconvulsive therapy in treatment-resistant depression: a retrospective monocentric case series.

Context: The use of vagus nerve stimulation (VNS) to reduce or stop electroconvulsive therapy (ECT) in treatment-resistant depression seems promising. The aim of this study was to investigate the efficacy of VNS on the reduction of ECT sessions and mood stabilization. Methods: We conducted a monocentric retrospective case series of patients who suffered from treatment-resistant depression, treated with ECT and referred to our center for VNS. We investigated the number and the frequency of ECT sessions before and after VNS implantation. Secondary criteria consisted in the Montgomery Åsberg Depression Rating Scale (MADRS) score, number of medical treatments, dosage of the main treatment and length of hospital stays before and after VNS. Additionally, we sent an anonymous survey to psychiatrists and other physicians in our institution to investigate their knowledge and perception of VNS therapy to treat treatment-resistant depression. Results: Seven patients benefited from VNS: six (86%) were female (mean age of 51.7 +/- 16.0 years at surgery), and five (71%) suffered from bipolar depression (three type I and two type II). All patients were followed up at least 2 years post-implantation (range: 27-68 months). Prior to VNS, six patients were treated by maintenance ECT. After VNS, three (43%) patients did not require maintenance ECT anymore, and three (43%) patients required less frequent ECT session with a mean 14.7 +/- 9.8 weeks between sessions after VNS vs. 2.9 +/- 0.8 weeks before VNS. At last follow-up, 4 (57%) patients had stopped ECT. Five (71%) patients implanted with VNS were good responders (50% decrease relative to baseline MADRS). According to the survey, psychiatrists had a significantly better perception and knowledge of ECT, but a worse perception and knowledge of VNS compared to other physicians. Conclusion: VNS is a good option for treatment-resistant depression requiring maintenance ECT dependence. Larger on-going studies will help broaden the implanted patients while strengthening psychiatrists' knowledge on this therapy.

Elevated Effort Cost Identified by Computational Modeling as a Distinctive Feature Explaining Multiple Behaviors in Patients With Depression.

BACKGROUND: Motivational deficit is a core clinical manifestation of depression and a strong predictor of treatment failure. However, the underlying mechanisms, which cannot be accessed through conventional questionnaire-based scoring, remain largely unknown. According to decision theory, apathy could result either from biased subjective estimates (of action costs or outcomes) or from dysfunctional processes (in making decisions or allocating resources). METHODS: Here, we combined a series of behavioral tasks with computational modeling to elucidate the motivational deficits of 35 patients with unipolar or bipolar depression under various treatments compared with 35 matched healthy control subjects. RESULTS: The most striking feature, which was observed independent of medication across preference tasks (likeability ratings and binary decisions), performance tasks (physical and mental effort exertion), and instrumental learning tasks (updating choices to maximize outcomes), was an elevated sensitivity to effort cost. By contrast, sensitivity to action outcomes (reward and punishment) and task-specific processes were relatively spared. CONCLUSIONS: These results highlight effort cost as a critical dimension that might explain multiple behavioral changes in patients with depression. More generally, they validate a test battery for computational phenotyping of motivational states, which could orientate toward specific medication or rehabilitation therapy, and thereby help pave the way for more personalized medicine in psychiatry.

Intracerebral mechanisms explaining the impact of incidental feedback on mood state and risky choice.

Identifying factors whose fluctuations are associated with choice inconsistency is a major issue for rational decision theory. Here, we investigated the neuro-computational mechanisms through which mood fluctuations may bias human choice behavior. Intracerebral EEG data were collected in a large group of subjects (n=30) while they were performing interleaved quiz and choice tasks that were designed to examine how a series of unrelated feedbacks affect decisions between safe and risky options. Neural baseline activity preceding choice onset was confronted first to mood level, estimated by a computational model integrating the feedbacks received in the quiz task, and then to the weighting of option attributes, in a computational model predicting risk attitude in the choice task. Results showed that (1) elevated broadband gamma activity (BGA) in the ventromedial prefrontal cortex (vmPFC) and dorsal anterior insula (daIns) was respectively signaling periods of high and low mood, (2) increased vmPFC and daIns BGA respectively promoted and tempered risk taking by overweighting gain vs. loss prospects. Thus, incidental feedbacks induce brain states that correspond to different moods and bias the evaluation of risky options. More generally, these findings might explain why people experiencing positive (or negative) outcome in some part of their life tend to expect success (or failure) in any other.