Theory of mind impairment and its clinical correlates in patients with schizophrenia, major depressive disorder and bipolar disorder.

BACKGROUND: Although Theory of Mind (ToM) impairment has been observed in patients with a wide range of mental disorders, the similarity and uniqueness of these deficits across diagnostic groups has not been thoroughly investigated. METHODS: We recruited 35 participants with schizophrenia (SCZ), 35 with bipolar disorder (BD), 35 with major depressive disorder (MDD), and 35 healthy controls in this study. All participants were matched in age, gender proportion and IQ estimates. The Yoni task, capturing both the cognitive and affective components of ToM at the first- and second-order level was administered. Repeated-measure ANOVA and MANOVA were conducted to compare the group differences in ToM performance. A network was then constructed with ToM performances, psychotic and depressive symptoms, and executive function as nodes exploring the clinical correlates of ToM. RESULTS: Overall, ToM impairments were observed in all patient groups compared with healthy controls, with patients with SCZ performing worse than those with BD. In second-order conditions, patients with SCZ and MDD showed deficits in both cognitive and affective conditions, while patients with BD performed significantly poorer in cognitive conditions. Network analysis showed that second-order affective ToM performance was associated with psychotic and depressive symptoms as well as executive dysfunction, while second-order affective ToM performance and negative symptoms showed relatively high centrality in the network. CONCLUSIONS: Patients with SCZ, MDD and BD exhibited different types and severity of impairments in ToM sub-components. Impairment in higher-order affective ToM appears to be closely related to clinical symptoms in both psychotic and affective disorders

An empirical model for probabilistic decadal prediction: global attribution and regional hindcasts

Empirical models, designed to predict surface variables over seasons to decades ahead, provide useful benchmarks for comparison against the performance of dynamical forecast systems; they may also be employable as predictive tools for use by climate services in their own right. A new global empirical decadal prediction system is presented, based on a multiple linear regression approach designed to produce probabilistic output for comparison against dynamical models. A global attribution is performed initially to identify the important forcing and predictor components of the model . Ensemble hindcasts of surface air temperature anomaly fields are then generated, based on the forcings and predictors identified as important, under a series of different prediction ‘modes’ and their performance is evaluated. The modes include a real-time setting, a scenario in which future volcanic forcings are prescribed during the hindcasts, and an approach which exploits knowledge of the forced trend. A two-tier prediction system, which uses knowledge of future sea surface temperatures in the Pacific and Atlantic Oceans, is also tested, but within a perfect knowledge framework. Each mode is designed to identify sources of predictability and uncertainty, as well as investigate different approaches to the design of decadal prediction systems for operational use. It is found that the empirical model shows skill above that of persistence hindcasts for annual means at lead times of up to 10 years ahead in all of the prediction modes investigated. It is suggested that hindcasts which exploit full knowledge of the forced trend due to increasing greenhouse gases throughout the hindcast period can provide more robust estimates of model bias for the calibration of the empirical model in an operational setting. The two-tier system shows potential for improved real-time prediction, given the assumption that skilful predictions of large-scale modes of variability are available. The empirical model framework has been designed with enough flexibility to facilitate further developments, including the prediction of other surface variables and the ability to incorporate additional predictors within the model that are shown to contribute significantly to variability at the local scale. It is also semi-operational in the sense that forecasts have been produced for the coming decade and can be updated when additional data becomes available

Tales of future weather

Society is vulnerable to extreme weather events and, by extension, to human impacts on future events. As climate changes weather patterns will change. The search is on for more effective methodologies to aid decision-makers both in mitigation to avoid climate change and in adaptation to changes. The traditional approach uses ensembles of climate model simulations, statistical bias correction, downscaling to the spatial and temporal scales relevant to decision-makers, and then translation into quantities of interest. The veracity of this approach cannot be tested, and it faces in-principle challenges. Alternatively, numerical weather prediction models in a hypothetical climate setting can provide tailored narratives for high-resolution simulations of high-impact weather in a future climate. This 'tales of future weather' approach will aid in the interpretation of lower-resolution simulations. Arguably, it potentially provides complementary, more realistic and more physically consistent pictures of what future weather might look like

Theory of mind impairment and its clinical correlates in patients with schizophrenia, major depressive disorder and bipolar disorder

BACKGROUND: Although Theory of Mind (ToM) impairment has been observed in patients with a wide range of mental disorders, the similarity and uniqueness of these deficits across diagnostic groups has not been thoroughly investigated. METHODS: We recruited 35 participants with schizophrenia (SCZ), 35 with bipolar disorder (BD), 35 with major depressive disorder (MDD), and 35 healthy controls in this study. All participants were matched in age, gender proportion and IQ estimates. The Yoni task, capturing both the cognitive and affective components of ToM at the first- and second-order level was administered. Repeated-measure ANOVA and MANOVA were conducted to compare the group differences in ToM performance. A network was then constructed with ToM performances, psychotic and depressive symptoms, and executive function as nodes exploring the clinical correlates of ToM. RESULTS: Overall, ToM impairments were observed in all patient groups compared with healthy controls, with patients with SCZ performing worse than those with BD. In second-order conditions, patients with SCZ and MDD showed deficits in both cognitive and affective conditions, while patients with BD performed significantly poorer in cognitive conditions. Network analysis showed that second-order affective ToM performance was associated with psychotic and depressive symptoms as well as executive dysfunction, while second-order affective ToM performance and negative symptoms showed relatively high centrality in the network. CONCLUSIONS: Patients with SCZ, MDD and BD exhibited different types and severity of impairments in ToM sub-components. Impairment in higher-order affective ToM appears to be closely related to clinical symptoms in both psychotic and affective disorders. Copyright &copy; 2017. Published by Elsevier B.V.</p