Contributions in Merlin

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Dienstleistungen basierend auf IP werden im Internet mit zunehmender Vielfalt angeboten. Das wachsende Dienstangebot wird durch die verstärkte Verbreitung von IP getragen und in einigen Jahren zu All-IP führen. Aus dieser All-IP-Perspektive ergeben sich an Verrechnungssysteme von IP-Dienstleistungen zusätzliche Anforderungen. Eine dieser ist die Unterstützung der in den mobilen Telekommunikationsnetzen weit verbreiteten Prepaid-Verrechnung.

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When making decisions between different options, we often consider two basic properties of these options, how risky they are and when they will occur. For example, we may choose to gamble or to wait for a larger reward. Decisions under risk refer to decisions among known probabilistic options, inter-temporal decisions refer to choices between options that will be realized at known future timepoints. Risky and inter-temporal decisions have been captured theoretically primarily by Ecology and Microeconomics but findings from Behavioral Economics, Psychology and Neuroscience often contradicted theoretical predictions. As a consequence, a wealth of more descriptive models has emerged to explain the findings. A subset of these models has stressed the similarities between risky and inter-temporal decisions. In this chapter we review both core theoretical approaches and empirical findings. We discuss possible explanations for discrepancies and identify key behavioral experiments.

Grasping an object requires processing visuospatial information about the extrinsic features (spatial location) and intrinsic features (size, shape, orientation) of the object. Accordingly, manual prehension has been subdivided into a reach component, guiding the hand toward the object on the basis of its extrinsic features, and a grasp component, preshaping the fingers around the center of mass of the object on the basis of its intrinsic features. In neural terms, this distinction has been linked to a dedicated dorsomedial "reaching" circuit and a dorsolateral "grasping" circuit that process extrinsic and intrinsic features, linking occipital areas via parietal regions with the dorsal and ventral premotor cortex, respectively. We have tested an alternative possibility, namely that the relative contribution of the two circuits is related to the degree of on-line control required by the prehension movement. We used dynamic causal modeling of functional magnetic resonance imaging time series to assess how parieto-frontal connectivity is modulated by planning and executing prehension movements toward objects of different size and width. This experimental manipulation evoked different movements, with different planning and execution phases for the different objects. Crucially, grasping large objects increased inter-regional couplings within the dorsomedial circuit, whereas grasping small objects increased the effective connectivity of a mainly dorsolateral circuit, with a degree of overlap between these circuits. These results argue against the presence of dedicated cerebral circuits for reaching and grasping, suggesting that the contributions of the dorsolateral and the dorsomedial circuits are a function of the degree of on-line control required by the movement.

When deciding between different options, individuals are guided by the expected (mean) value of the different outcomes and by the associated degrees of uncertainty. We used functional magnetic resonance imaging to identify brain activations coding the key decision parameters of expected value (magnitude and probability) separately from uncertainty (statistical variance) of monetary rewards. Participants discriminated behaviorally between stimuli associated with different expected values and uncertainty. Stimuli associated with higher expected values elicited monotonically increasing activations in distinct regions of the striatum, irrespective of different combinations of magnitude and probability. Stimuli associated with higher uncertainty (variance) elicited increasing activations in the lateral orbitofrontal cortex. Uncertainty-related activations covaried with individual risk aversion in lateral orbitofrontal regions and risk-seeking in more medial areas. Furthermore, activations in expected value-coding regions in prefrontal cortex covaried differentially with uncertainty depending on risk attitudes of individual participants, suggesting that separate prefrontal regions are involved in risk aversion and seeking. These data demonstrate the distinct coding in key reward structures of the two basic and crucial decision parameters, expected value, and uncertainty.

This study examined whether ventral frontostriatal regions differentially code expected and unexpected reward outcomes. We parametrically manipulated the probability of reward and examined the neural response to reward and nonreward for each probability condition in the ventral striatum and the orbitofrontal cortex (OFC). By late trials of the experiment, subjects showed slower behavioral responses for the condition with the lowest probability of reward, relative to the condition with the highest probability of reward. At the neural level, both the nucleus accumbens (NAcc) and OFC showed greater activation to rewarded relative to nonrewarded trials, but the accumbens appeared to be most sensitive to violations in expected reward outcomes. These data suggest distinct roles for frontostriatal circuitry in reward prediction and in responding to violations in expectations.

We present a neural mass model of steady-state membrane potentials measured with local field potentials or electroencephalography in the frequency domain. This model is an extended version of previous dynamic causal models for investigating event-related potentials in the time-domain. In this paper, we augment the previous formulation with parameters that mediate spike-rate adaptation and recurrent intrinsic inhibitory connections. We then use linear systems analysis to show how the model's spectral response changes with its neurophysiological parameters. We demonstrate that much of the interesting behaviour depends on the non-linearity which couples mean membrane potential to mean spiking rate. This non-linearity is analogous, at the population level, to the firing rate-input curves often used to characterize single-cell responses. This function depends on the model's gain and adaptation currents which, neurobiologically, are influenced by the activity of modulatory neurotransmitters. The key contribution of this paper is to show how neuromodulatory effects can be modelled by adding adaptation currents to a simple phenomenological model of EEG. Critically, we show that these effects are expressed in a systematic way in the spectral density of EEG recordings. Inversion of the model, given such non-invasive recordings, should allow one to quantify pharmacologically induced changes in adaptation currents. In short, this work establishes a forward or generative model of electrophysiological recordings for psychopharmacological studies.