Abnormal reward prediction-error signalling in antipsychotic naive individuals with first-episode psychosis or clinical risk for psychosis.

Ongoing research suggests preliminary, though not entirely consistent, evidence of neural abnormalities in signalling prediction errors in schizophrenia. Supporting theories suggest mechanistic links between the disruption of these processes and the generation of psychotic symptoms. However, it is unknown at what stage in the pathogenesis of psychosis these impairments in prediction-error signalling develop. One major confound in prior studies is the use of medicated patients with strongly varying disease durations. Our study aims to investigate the involvement of the meso-cortico-striatal circuitry during reward prediction-error signalling in earliest stages of psychosis. We studied patients with first-episode psychosis (FEP) and help-seeking individuals at-risk for psychosis due to sub-threshold prodromal psychotic symptoms. Patients with either FEP (n = 14), or at-risk for developing psychosis (n = 30), and healthy volunteers (n = 39) performed a reinforcement learning task during fMRI scanning. ANOVA revealed significant (p < 0.05 family-wise error corrected) prediction-error signalling differences between groups in the dopaminergic midbrain and right middle frontal gyrus (dorsolateral prefrontal cortex, DLPFC). FEP patients showed disrupted reward prediction-error signalling compared to controls in both regions. At-risk patients showed intermediate activation in the midbrain that significantly differed from controls and from FEP patients, but DLPFC activation that did not differ from controls. Our study confirms that FEP patients have abnormal meso-cortical signalling of reward-prediction errors, whereas reward-prediction-error dysfunction in the at-risk patients appears to show a more nuanced pattern of activation with a degree of midbrain impairment but preserved cortical function

Number of addictive substances used related to increased risk of unnatural death: A combined medico-legal and case-record study

<p>Abstract</p> <p>Background</p> <p>Substance use disorders have repeatedly been found to lead to premature death, i.e. drug-related death by disease, fatal intoxications, or trauma (accidents, suicide, undetermined suicide, and homicide). The present study examined the relationship between multi-drug substance use and natural and unnatural death.</p> <p>Methods</p> <p>All consecutive, autopsied patients who had been in contact with the Addiction Centre in Malmö University Hospital from 1993 to 1997 inclusive were investigated. Drug abuse was investigated blindly in the case records and related to the cause of death in 387 subjects.</p> <p>Results</p> <p>Every substance apart from alcohol used previously in life added to the risk of unnatural death in a linear way. There were independent increased risks of fatal heroin overdoses or undetermined suicide. Death by suicide and violent death were unrelated to additional abuse.</p> <p>Conclusion</p> <p>The number of drugs used was related to an increased risk of unnatural death by undetermined suicide (mainly fatal intoxications) and heroin overdose.</p

Disambiguating ventral striatum fMRI-related bold signal during reward prediction in schizophrenia

Reward detection, surprise detection and prediction-error signaling have all been proposed as roles for the ventral striatum (vStr). Previous neuroimaging studies of striatal function in schizophrenia have found attenuated neural responses to reward-related prediction errors; however, as prediction errors represent a discrepancy in mesolimbic neural activity between expected and actual events, it is critical to examine responses to both expected and unexpected rewards (URs) in conjunction with expected and UR omissions in order to clarify the nature of ventral striatal dysfunction in schizophrenia. In the present study, healthy adults and people with schizophrenia were tested with a reward-related prediction-error task during functional magnetic resonance imaging to determine whether schizophrenia is associated with altered neural responses in the vStr to rewards, surprise prediction errors or all three factors. In healthy adults, we found neural responses in the vStr were correlated more specifically with prediction errors than to surprising events or reward stimuli alone. People with schizophrenia did not display the normal differential activation between expected and URs, which was partially due to exaggerated ventral striatal responses to expected rewards (right vStr) but also included blunted responses to unexpected outcomes (left vStr). This finding shows that neural responses, which typically are elicited by surprise, can also occur to well-predicted events in schizophrenia and identifies aberrant activity in the vStr as a key node of dysfunction in the neural circuitry used to differentiate expected and unexpected feedback in schizophrenia

The relationship between subtypes of depression and cardiovascular disease: a systematic review of biological models

A compelling association has been observed between cardiovascular disease (CVD) and depression, suggesting individuals with depression to be at significantly higher risk for CVD and CVD-related mortality. Systemic immune activation, hypothalamic–pituitary–adrenal (HPA) axis hyperactivity, arterial stiffness and endothelial dysfunction have been frequently implicated in this relationship. Although a differential epidemiological association between CVD and depression subtypes is evident, it has not been determined if this indicates subtype specific biological mechanisms. A comprehensive systematic literature search was conducted using PubMed and PsycINFO databases yielding 147 articles for this review. A complex pattern of systemic immune activation, endothelial dysfunction and HPA axis hyperactivity is suggestive of the biological relationship between CVD and depression subtypes. The findings of this review suggest that diagnostic subtypes rather than a unifying model of depression should be considered when investigating the bidirectional biological relationship between CVD and depression. The suggested model of a subtype-specific biological relationship between depression and CVDs has implications for future research and possibly for diagnostic and therapeutic processes

Global health philanthropy and institutional relationships: how should conflicts of interest be addressed?

David Stuckler and colleagues examine five large private global health foundations and report on the scope of relationships between these tax-exempt foundations and for-profit corporations including major food and pharmaceutical companies

A web-based support system for biometeorological research

[EN] Data are the fundamental building blocks to conduct scientific studies that seek to understand natural phenomena in space and time. The notion of data processing is ubiquitous and nearly operates in any project that requires gaining insight from the data. The increasing availability of information sources, data formats and download services offered to the users, makes it difficult to reuse or exploit the potential of those new resources in multiple scientific fields. In this paper, we present a spatial extract-transform-load (spatial-ETL) approach for downloading atmospheric datasets in order to produce new biometeorological indices and expose them publicly for reuse in research studies. The technologies and processes involved in our work are clearly defined in a context where the GDAL library and the Python programming language are key elements for the development and implementation of the geoprocessing tools. 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