The impact of stress on financial decision-making varies as a function of depression and anxiety symptoms.

Stress can precipitate the onset of mood and anxiety disorders. This may occur, at least in part, via a modulatory effect of stress on decision-making. Some individuals are, however, more resilient to the effects of stress than others. The mechanisms underlying such vulnerability differences are nevertheless unknown. In this study we attempted to begin quantifying individual differences in vulnerability by exploring the effect of experimentally induced stress on decision-making. The threat of unpredictable shock was used to induce stress in healthy volunteers (N = 47) using a within-subjects, within-session design, and its impact on a financial decision-making task (the Iowa Gambling Task) was assessed alongside anxious and depressive symptomatology. As expected, participants learned to select advantageous decks and avoid disadvantageous decks. Importantly, we found that stress provoked a pattern of harm-avoidant behaviour (decreased selection of disadvantageous decks) in individuals with low levels of trait anxiety. By contrast, individuals with high trait anxiety demonstrated the opposite pattern: stress-induced risk-seeking (increased selection of disadvantageous decks). These contrasting influences of stress depending on mood and anxiety symptoms might provide insight into vulnerability to common mental illness. In particular, we speculate that those who adopt a more harm-avoidant strategy may be better able to regulate their exposure to further environmental stress, reducing their susceptibility to mood and anxiety disorders

The POOL Data Storage, Cache and Conversion Mechanism

The POOL data storage mechanism is intended to satisfy the needs of the LHC experiments to store and analyze the data from the detector response of particle collisions at the LHC proton-proton collider. Both the data rate and the data volumes will largely differ from the past experience. The POOL data storage mechanism is intended to be able to cope with the experiment's requirements applying a flexible multi technology data persistency mechanism. The developed technology independent approach is flexible enough to adopt new technologies, take advantage of existing schema evolution mechanisms and allows users to access data in a technology independent way. The framework consists of several components, which can be individually adopted and integrated into existing experiment frameworks.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 5 pages, PDF, 6 figures. PSN MOKT00

Event Data Definition in LHCb

We present the approach used for defining the event object model for the LHCb experiment. This approach is based on a high level modelling language, which is independent of the programming language used in the current implementation of the event data processing software. The different possibilities of object modelling languages are evaluated, and the advantages of a dedicated model based on XML over other possible candidates are shown. After a description of the language itself, we explain the benefits obtained by applying this approach in the description of the event model of an experiment such as LHCb. Examples of these benefits are uniform and coherent mapping of the object model to the implementation language across the experiment software development teams, easy maintenance of the event model, conformance to experiment coding rules, etc. The description of the object model is parsed by means of a so called front-end which allows to feed several back-ends. We give an introduction to the model itself and to the currently implemented back-ends which produce information like programming language specific implementations of event objects or meta information about these objects. Meta information can be used for introspection of objects at run-time which is essential for functionalities like object persistency or interactive analysis. This object introspection package for C++ has been adopted by the LCG project as the starting point for the LCG object dictionary that is going to be developed in common for the LHC experiments. The current status of the event object modelling and its usage in LHCb are presented and the prospects of further developments are discussed.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 7 pages, LaTeX, 2 eps figures. PSN MOJT00

Cognitive impairment in depression and its (non-)response to antidepressant treatment

ABSTRACT FROM: Shilyansky C, Williams LM, Gyurak A, et al. Effect of antidepressant treatment on cognitive impairments associated with depression: a randomised longitudinal study. Lancet Psychiatry 2016;3:425–35

Encoding of Marginal Utility across Time in the Human Brain

Marginal utility theory prescribes the relationship between the objective property of the magnitude of rewards and their subjective value. Despite its pervasive influence, however, there is remarkably little direct empirical evidence for such a theory of value, let alone of its neurobiological basis. We show that human preferences in an intertemporal choice task are best described by a model that integrates marginally diminishing utility with temporal discounting. Using functional magnetic resonance imaging, we show that activity in the dorsal striatum encodes both the marginal utility of rewards, over and above that which can be described by their magnitude alone, and the discounting associated with increasing time. In addition, our data show that dorsal striatum may be involved in integrating subjective valuation systems inherent to time and magnitude, thereby providing an overall metric of value used to guide choice behavior. Furthermore, during choice, we show that anterior cingulate activity correlates with the degree of difficulty associated with dissonance between value and time. Our data support an integrative architecture for decision making, revealing the neural representation of distinct subcomponents of value that may contribute to impulsivity and decisiveness

ON SOME PROBLEMS OF THE STATIC AND DYNAMIC ACCURACY OF LOGARITHMIC MULTIPLIERS

Apathy and anhedonia are common syndromes of motivation that are associated with a wide range of brain disorders and have no established therapies. Research using animal models suggests that a useful framework for understanding motivated behaviour lies in effort-based decision making for reward. The neurobiological mechanisms underpinning such decisions have now begun to be determined in individuals with apathy or anhedonia, providing an important foundation for developing new treatments. The findings suggest that there might be some shared mechanisms between both syndromes. A transdiagnostic approach that cuts across traditional disease boundaries provides a potentially useful means for understanding these conditions

Computational Psychiatry: towards a mathematically informed understanding of mental illness

Computational Psychiatry aims to describe the relationship between the brain's neurobiology, its environment and mental symptoms in computational terms. In so doing, it may improve psychiatric classification and the diagnosis and treatment of mental illness. It can unite many levels of description in a mechanistic and rigorous fashion, while avoiding biological reductionism and artificial categorisation. We describe how computational models of cognition can infer the current state of the environment and weigh up future actions, and how these models provide new perspectives on two example disorders, depression and schizophrenia. Reinforcement learning describes how the brain can choose and value courses of actions according to their long-term future value. Some depressive symptoms may result from aberrant valuations, which could arise from prior beliefs about the loss of agency ('helplessness'), or from an inability to inhibit the mental exploration of aversive events. Predictive coding explains how the brain might perform Bayesian inference about the state of its environment by combining sensory data with prior beliefs, each weighted according to their certainty (or precision). Several cortical abnormalities in schizophrenia might reduce precision at higher levels of the inferential hierarchy, biasing inference towards sensory data and away from prior beliefs. We discuss whether striatal hyperdopaminergia might have an adaptive function in this context, and also how reinforcement learning and incentive salience models may shed light on the disorder. Finally, we review some of Computational Psychiatry's applications to neurological disorders, such as Parkinson's disease, and some pitfalls to avoid when applying its methods

Threat of Shock and Aversive Inhibition: Induced Anxiety Modulates Pavlovian-Instrumental Interactions

Anxiety can be an adaptive response to potentially threatening situations. However, if experienced in inappropriate contexts, it can also lead to pathological and maladaptive anxiety disorders. Experimentally, anxiety can be induced in healthy individuals using the threat of shock (ToS) paradigm. Accumulating work with this paradigm suggests that anxiety promotes harm-avoidant mechanisms through enhanced inhibitory control. However, the specific cognitive mechanisms underlying anxiety-linked inhibitory control are unclear. Critically, behavioral inhibition can arise from at least 2 interacting valuation systems: instrumental (a goal-directed system) and Pavlovian (a "hardwired" reflexive system). The present study (N = 62) replicated a study showing improved response inhibition under ToS in healthy participants, and additionally examined the impact of ToS on aversive and appetitive Pavlovian-instrumental interactions in a reinforced go/no-go task. When Pavlovian and instrumental systems were in conflict, ToS increased inhibition to aversive events, while leaving appetitive interactions unperturbed. We argue that anxiety promotes avoidant behavior in potentially harmful situations by potentiating aversive Pavlovian reactions (i.e., promoting avoidance in the face of threats). Critically, such a mechanism would drive adaptive harm-avoidant behavior in threatening situations where Pavlovian and instrumental processes are aligned, but at the same time, result in maladaptive behaviors when misaligned and where instrumental control would be advantageous. This has important implications for our understanding of the mechanisms that underlie pathological anxiety. (PsycINFO Database Recor