The aims of the Reward Task Optimisation Consortium (RTOC) study (Bilderbeck et al., 2020) were to explore the validity, reliability, and feasibility of a battery of reward processing tasks for the development of new treatments for anhedonia. We report our findings from the Grip Strength Effort Task (GSET), an effort-based decision-making task in which participants chose to either perform easy trials that required less physical effort for low monetary reward or hard trials that required more effort for potentially larger rewards. Thirty-seven participants with schizophrenia (SZ), 40 with major depressive disorder (MDD), and 59 age- and sex-matched healthy controls were administered the task across four European sites. 19% of participants (8.5% HC, 27% SZ, 27.5% MDD) were 'inflexible responders' who always chose hard trials irrespective of the reward amount. MDD participants showed less willingness to exert physical effort for high reward than controls, when inflexible responders were excluded, but no statistically significant differences were observed between SZ participants and controls. Across all participants, willingness to exert effort for high reward negatively correlated with measures of anhedonia. Inflexible responders exhibited higher depressive symptoms and higher anticipation of punishment than other participants. Forty-three participants performed the GSET again after 3-5 weeks and moderate-to-high test-retest reliability was observed. Minimal site effects confirmed operational feasibility of the task in multi-site studies. We conclude that the GSET can provide objective behavioural biomarkers of reward processing dysfunction, but further investigation is needed to understand inflexible responding and its implications on the task's design and interpretation.

ObjectivesWhile neuropsychological effects of conventional antidepressants are well-documented, more research is needed for rapid-acting antidepressants. This study examines the effects of esketamine on emotion processing and cognitive functioning, both acutely and sub-chronically.MethodsEighteen treatment-resistant depression (TRD) patients received repeated intravenous esketamine infusions. Mood state was reported daily, and the Facial Expression Recognition Task was administered 1h before and 4h after each infusion. Other assessments included the Digit Symbol Substitution Task.Results66.7% participants who received at least five infusions (n = 12) showed significant improvement. Emotion recognition improved for all emotions except sadness, where accuracy decreased, particularly for low-intensity expressions (p = .007, d = -1.09). Misclassifications of other emotions as sad also decreased (p = .035, d = -0.79), indicating a reduced response bias towards sadness. This shift in bias emerged after the first infusion and then consolidated over time. In parallel, participants showed significant reductions in feelings of sadness (p = .015, d = -0.89) and irritability (p = .001, d = -1.35). Symptomatic improvement negatively correlated with accuracy for and misclassifications of sadness, and cognitive functioning also improved (p = .001, d = 1.62).ConclusionsImprovement of TRD by esketamine may involve shifts in emotion processing and cognition, with the acute mood-lifting effects of esketamine being discernible from longer-lasting antidepressant response, which consolidates after repeated administration.

Social dysfunction represents one of the most common signs of neuropsychiatric disorders, such as Schizophrenia (SZ) and Alzheimer's disease (AD). Perturbed socioaffective neural processing is crucially implicated in SZ/AD and generally linked to social dysfunction. Yet, transdiagnostic properties of social dysfunction and its neurobiological underpinnings remain unknown. As part of the European PRISM project, we examined whether social dysfunction maps onto shifts within socioaffective brain systems across SZ and AD patients. We probed coupling of social dysfunction with socioaffective neural processing, as indexed by an implicit facial emotional processing fMRI task, across SZ (N = 46), AD (N = 40) and two age-matched healthy control (HC) groups (N = 26 HC-younger and N = 27 HC-older). Behavioural (i.e., social withdrawal, interpersonal dysfunction, diminished prosocial or recreational activity) and subjective (i.e., feelings of loneliness) aspects of social dysfunction were assessed using the Social Functioning Scale and De Jong-Gierveld loneliness questionnaire, respectively. Across SZ/AD/HC participants, more severe behavioural social dysfunction related to hyperactivity within fronto-parieto-limbic brain systems in response to sad emotions (P = 0.0078), along with hypoactivity of these brain systems in response to happy emotions (P = 0.0418). Such relationships were not found for subjective experiences of social dysfunction. These effects were independent of diagnosis, and not confounded by clinical and sociodemographic factors. In conclusion, behavioural aspects of social dysfunction across SZ/AD/HC participants are associated with shifts within fronto-parieto-limbic brain systems. These findings pinpoint altered socioaffective neural processing as a putative marker for social dysfunction, and could aid personalized care initiatives grounded in social behaviour.

Despite progress in understanding the pathological mechanisms underlying psychiatric disorders, translation from animal models into clinical use remains a significant bottleneck. Preclinical studies have implicated the orexin neuropeptide system as a potential target for psychiatric disorders through its role in regulating emotional, cognitive, and behavioral processes. Clinical studies are investigating orexin modulation in addiction and mood disorders. Here we review performance-outcome measures (POMs) arising from experimental medicine research methods which may show promise as markers of efficacy of orexin receptor modulators in humans. POMs provide objective measures of brain function, complementing patient-reported or clinician-observed symptom evaluation, and aid the translation from preclinical to clinical research. Significant challenges include the development, validation, and operationalization of these measures. We suggest that collaborative networks comprising clinical practitioners, academics, individuals working in the pharmaceutical industry, drug regulators, patients, patient advocacy groups, and other relevant stakeholders may provide infrastructure to facilitate validation of experimental medicine approaches in translational research and in the implementation of these approaches in real-world clinical practice.

Abstract Objectives Social dysfunction is one of the most common signs of major neuropsychiatric disorders. The Default Mode Network (DMN) is crucially implicated in both psychopathology and social dysfunction, although the transdiagnostic properties of social dysfunction remains unknown. As part of the pan-European PRISM (Psychiatric Ratings using Intermediate Stratified Markers) project, we explored cross-disorder impact of social dysfunction on DMN connectivity. Methods We studied DMN intrinsic functional connectivity in relation to social dysfunction by applying Independent Component Analysis and Dual Regression on resting-state fMRI data, among schizophrenia (SZ; N  = 48), Alzheimer disease (AD; N  = 47) patients and healthy controls (HC; N  = 55). Social dysfunction was operationalised via the Social Functioning Scale (SFS) and De Jong-Gierveld Loneliness Scale (LON). Results Both SFS and LON were independently associated with diminished DMN connectional integrity within rostromedial prefrontal DMN subterritories (pcorrected range = 0.02–0.04). The combined effect of these indicators (Mean.SFS + LON) on diminished DMN connectivity was even more pronounced (both spatially and statistically), independent of diagnostic status, and not confounded by key clinical or sociodemographic effects, comprising large sections of rostromedial and dorsomedial prefrontal cortex (pcorrected =0.01). Conclusions These findings pinpoint DMN connectional alterations as putative transdiagnostic endophenotypes for social dysfunction and could aid personalised care initiatives grounded in social behaviour.

Background Social functioning is often impaired in schizophrenia (SZ) and Alzheimer’s disease (AD). However, commonalities and differences in social dysfunction among these patient groups remain elusive. Materials and methods Using data from the PRISM study, behavioral (all subscales and total score of the Social Functioning Scale) and affective (perceived social disability and loneliness) indicators of social functioning were measured in patients with SZ ( N = 56), probable AD ( N = 50) and age-matched healthy controls groups (HC, N = 29 and N = 28). We examined to what extent social functioning differed between disease and age-matched HC groups, as well as between patient groups. Furthermore, we examined how severity of disease and mood were correlated with social functioning, irrespective of diagnosis. Results As compared to HC, both behavioral and affective social functioning seemed impaired in SZ patients (Cohen’s d’s 0.81–1.69), whereas AD patients mainly showed impaired behavioral social function (Cohen’s d’s 0.65–1.14). While behavioral indices of social functioning were similar across patient groups, SZ patients reported more perceived social disability than AD patients (Cohen’s d’s 0.65). Across patient groups, positive mood, lower depression and anxiety levels were strong determinants of better social functioning (p’s <0.001), even more so than severity of disease. Conclusions AD and SZ patients both exhibit poor social functioning in comparison to age- and sex matched HC participants. Social dysfunction in SZ patients may be more severe than in AD patients, though this may be due to underreporting by AD patients. Across patients, social functioning appeared as more influenced by mood states than by severity of disease.

Background: Emotion recognition constitutes a pivotal process of social cognition. It involves decoding social cues (e.g., facial expressions) to maximise social adjustment. Current theoretical models posit the relationship between social withdrawal factors (social disengagement, lack of social interactions and loneliness) and emotion decoding. Objective: To investigate the role of social withdrawal in patients with schizophrenia (SZ) or probable Alzheimer's disease (AD), neuropsychiatric conditions associated with social dysfunction. Methods: A sample of 156 participants was recruited: schizophrenia patients (SZ; n = 53), Alzheimer's disease patients (AD; n = 46), and two age-matched control groups (SZc, n = 29; ADc, n = 28). All participants provided self-report measures of loneliness and social functioning, and completed a facial emotion detection task. Results: Neuropsychiatric patients (both groups) showed poorer performance in detecting both positive and negative emotions compared with their healthy counterparts (p < .01). Social withdrawal was associated with higher accuracy in negative emotion detection, across all groups. Additionally, neuropsychiatric patients with higher social withdrawal showed lower positive emotion misclassification. Conclusions: Our findings help to detail the similarities and differences in social function and facial emotion recognition in two disorders rarely studied in parallel, AD and SZ. Transdiagnostic patterns in these results suggest that social withdrawal is associated with heightened sensitivity to negative emotion expressions, potentially reflecting hypervigilance to social threat. Across the neuropsychiatric groups specifically, this hypervigilance associated with social withdrawal extended to positive emotion expressions, an emotionalcognitive bias that may impact social functioning in people with severe mental illness.

The presence of a change in a visual scene can influence brain activity and behavior, even in the absence of full conscious report. It may be possible for us to sense that such a change has occurred, even if we cannot specify exactly where or what it was. Despite existing evidence from electroencephalogram (EEG) and eye-tracking data, it is still unclear how this partial level of awareness relates to functional magnetic resonance imaging (fMRI) blood oxygen level dependent (BOLD) activation. Using EEG, fMRI, and a change blindness paradigm, we found multi-modal evidence to suggest that sensing a change is distinguishable from being blind to it. Specifically, trials during which participants could detect the presence of a colour change but not identify the location of the change (sense trials), were compared to those where participants could both detect and localise the change (localise or see trials), as well as change blind trials. In EEG, late parietal positivity and N2 amplitudes were larger for localised changes only, when compared to change blindness. However, ERP-informed fMRI analysis found no voxels with activation that significantly co-varied with fluctuations in single-trial late positivity amplitudes. In fMRI, a range of visual (BA17,18), parietal (BA7,40), and mid-brain (anterior cingulate, BA24) areas showed increased fMRI BOLD activation when a change was sensed, compared to change blindness. These visual and parietal areas are commonly implicated as the storage sites of visual working memory, and we therefore argue that sensing may not be explained by a lack of stored representation of the visual display. Both seeing and sensing a change were associated with an overlapping occipitoparietal network of activation when compared to blind trials, suggesting that the quality of the visual representation, rather than the lack of one, may result in partial awareness during the change blindness paradigm.

Aortic stenosis (AS) and renal dysfunction share risk factors and often occur simultaneously. The influence of renal dysfunction on the prognosis of patients with various grades of AS has not been extensively described. The present study aimed to assess the prognostic implications of renal dysfunction in a large cohort of patients with aortic sclerosis and patients with various grades of AS. Patients diagnosed with various grades of AS by transthoracic echocardiography were assessed and divided according to renal function by estimated glomerular filtration rate (eGFR). The occurrence of all-cause mortality (primary end point) and aortic valve replacement (AVR) was noted. Of 1,178 patients (mean age 70 ± 13 years, 60% male), 327 (28%) had aortic sclerosis, 86 (7%) had mild AS, 285 (24%) had moderate AS, and 480 (41%) had severe AS. Renal dysfunction (eGFR <60 ml/min/1.73 m2) was present in 440 (37%) patients, and moderate to severe AS was observed more often in these patients compared to patients without (70 vs 62%, respectively; p = 0.008). After a median follow-up of 95 [31 to 149] months, 626 (53%) patients underwent AVR and 549 (47%) patients died. Severely impaired renal function (eGFR <30 ml/min/1.73 m2) and AVR were independently associated with all-cause mortality after correcting for AS severity. In conclusion, renal dysfunction is highly prevalent in patients with various grades of AS. After correcting for AS severity and AVR, severely impaired renal function (eGFR <30 ml/min/1.73 m2) was independently associated with all-cause mortality. Independent of renal function, AVR was associated with improved survival.

Considering the stochastic Boussinesq equations in Td with the nonlinear multiplicative noises, we establish the local existence of pathwise solutions. Furthermore, we establish the global existence of pathwise solution when the noises are non-degenerate, which show that the non-degenerate multiplicative noises would provide a regularizing effect: the global existence of solution occurs with high probability if the initial data are sufficiently small, or if the noise coefficients are sufficiently large.

La robotique et l’intelligence artificielle envahissent nos lieux d’exercices et notamment le monde de la santé. Les progrès des processeurs et des algorithmes permettent aux automates de disposer d’une véritable autonomie décisionnelle grâce à une capacité d’apprentissage propre. Les enjeux éthiques sont majeurs et, parmi ceux-ci, les problématiques de responsabilité des automates en cas de dysfonctionnement, mauvaise utilisation ou d’accidents provoqués par leurs décisions. Nous proposons ici des réflexions sur ces aspects. Un article avait traité antérieurement les problématiques de responsabilité juridique des automates dépourvus de capacité d’apprentissage ainsi que de stockage des informations. Nous ne reprendrons pas ces éléments au sein du texte suivant, d’autant que les réponses juridiques y semblent plus claires.Robotics and artificial intelligence are invading our workplaces and especially the world of health. Advances in processors and algorithms allow PLCs to have real decision-making autonomy thanks to their learning ability. The ethical issues are major and among these, the problems of automata in case of malfunction, misuse or accident secondary to their decision. We propose here reflections on these aspects. An article has already been dealt with the legal elements of automatons without learning capacity and without information storage capacity. We will not repeat here, especially since the legal answers seem to be clearer.

Despite the large literature about non-additive value aggregation techniques, in the large majority of applied decision support processes, additive value aggregation functions are used. The main reasons for this may be the simplicity of the approach, minimum elicitation requirements, software availability, and the appeal of the underlying preference independence concepts that may be strengthened by an adequate choice of sub-objectives and attributes. However, in an applied decision support process, the decision maker(s) or the stakeholders decide on the sub-objectives and attributes to characterize the state of a system and they have to provide information that allows the decision analyst to express their preferences as a value function of these attributes. It is the task of the decision analyst to find the parameterization and parameter values of a value function that fits best the expressed preferences. We describe a value function elicitation process for the ideal morphological state of a lake shore, performed with stakeholders from federal and cantonal authorities and from environmental consulting companies in Switzerland. This process led to the elicitation of strongly non-additive and partly even non-concave value aggregation functions. The objective of this paper is to raise the awareness about the importance of carefully testing the assumptions underlying parameterized (often additive) value aggregation techniques during the preferences elicitation process and to be flexible regarding evaluating value functions that deviate from the often used additive aggregation scheme. This can lead to a higher confidence that additive aggregation is suitable for the specific decision problem or to the selection of alternative aggregation techniques that better represent the decision maker's preferences in case additivity is violated.

Previous studies of change blindness have suggested a distinction between detection and localisation of changes in a visual scene. Using a simple paradigm with an array of coloured squares, the present study aimed to further investigate differences in event-related potentials (ERPs) between trials in which participants could detect the presence of a colour change but not identify the location of the change (sense trials), versus those where participants could both detect and localise the change (localise trials). Individual differences in performance were controlled for by adjusting the difficulty of the task in real time. Behaviourally, reaction times for sense, blind, and false alarm trials were distinguishable when comparing across levels of participant certainty. In the EEG data, we found no significant differences in the visual awareness negativity ERP, contrary to previous findings. In the N2pc range, both awareness conditions (localise and sense) were significantly different to trials with no change detection (blind trials), suggesting that this ERP is not dependent on explicit awareness. Within the late positivity range, all conditions were significantly different. These results suggest that changes can be ‘sensed’ without knowledge of the location of the changing object, and that participant certainty scores can provide valuable information about the perception of changes in change blindness.

We report on a player evaluation of a pilot system for dynamic video game soundtrack generation. The system being evaluated generates music using an AI-based algorithmic composition technique to create score in real-time, in response to a continuously varying emotional trajectory dictated by gameplay cues. After a section of gameplay, players rated the system on a Likert scale according to emotional congruence with the narrative, and also according to their perceived immersion with the gameplay. The generated system showed a statistically meaningful and consistent improvement in ratings for emotional congruence, yet with a decrease in perceived immersion, which might be attributed to the marked difference in instrumentation between the generated music, voiced by a solo piano timbre, and the original, fully orchestrated soundtrack. Finally, players rated selected stimuli from the generated soundtrack dataset on a two-dimensional model reflecting perceived valence and arousal. These ratings were compared to the intended emotional descriptor in the meta-data accompanying specific gameplay events. Participant responses suggested strong agreement with the affective correlates, but also a significant amount of inter-participant variability. Individual calibration of the musical feature set, or further adjustment of the musical feature set are therefore suggested as useful avenues for further work.