Contributions in Merlin

We used functional magnetic resonance imaging (fMRI) to study neural correlates of a robust somatosensory illusion that can dissociate tactile perception from physical stimulation. Repeated rapid stimulation at the wrist, then near the elbow, can create the illusion of touches at intervening locations along the arm, as if a rabbit hopped along it. We examined brain activity in humans using fMRI, with improved spatial resolution, during this version of the classic cutaneous rabbit illusion. As compared with control stimulation at the same skin sites (but in a different order that did not induce the illusion), illusory sequences activated contralateral primary somatosensory cortex, at a somatotopic location corresponding to the filled-in illusory perception on the forearm. Moreover, the amplitude of this somatosensory activation was comparable to that for veridical stimulation including the intervening position on the arm. The illusion additionally activated areas of premotor and prefrontal cortex. These results provide direct evidence that illusory somatosensory percepts can affect primary somatosensory cortex in a manner that corresponds somatotopically to the illusory percept.

Lesion and functional imaging studies in humans have suggested that the dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), and intraparietal sulcus (IPS) are involved in orienting attention. A functional magnetic resonance imaging study supplemented by a behavioral experiment examined the effects of 5 Hz repetitive transcranial magnetic stimulation (rTMS) conditioning to the right and left DLPFC on reaction times and synaptic activity as indexed by changes in the blood oxygenation level-dependent (BOLD) signal during a cued choice reaction time task. Orienting precues were either correct (valid) or incorrect (invalid) with respect to the subsequent move cue. The effects of real and sham rTMS were compared for each site of stimulation. Invalid trials showed a significant increase in response times and increases in the BOLD signal in right frontal and parietal regions when compared with valid trials. Conditioning left DLPFC with rTMS led to decreased BOLD signal during performance of this reorienting task in areas including left VLPFC and left IPS. Comparing invalid to valid trials after right DLPFC conditioning revealed decreased BOLD signal in right VLPFC. Data from the behavioral study showed that right DLPFC rTMS selectively increases response times in invalid trials. This effect was only present in the first 10 min after rTMS conditioning. No effect was found in either validly or invalidly cued trials with left DLPFC conditioning. These results suggest that 5 Hz rTMS over right DLPFC exerts remote effects on the activity of areas that functionally interact with the DLPFC during attentional processes, particularly when the reorienting of attention is more demanding as in invalid trials.

In fear extinction, an animal learns that a conditioned stimulus (CS) no longer predicts a noxious stimulus [unconditioned stimulus (UCS)] to which it had previously been associated, leading to inhibition of the conditioned response (CR). Extinction creates a new CS-noUCS memory trace, competing with the initial fear (CS-UCS) memory. Recall of extinction memory and, hence, CR inhibition at later CS encounters is facilitated by contextual stimuli present during extinction training. In line with theoretical predictions derived from animal studies, we show that, after extinction, a CS-evoked engagement of human ventromedial prefrontal cortex (VMPFC) and hippocampus is context dependent, being expressed in an extinction, but not a conditioning, context. Likewise, a positive correlation between VMPFC and hippocampal activity is extinction context dependent. Thus, a VMPFC-hippocampal network provides for context-dependent recall of human extinction memory, consistent with a view that hippocampus confers context dependence on VMPFC.

Inferences about brain function, using functional neuroimaging data, require models of how the data were caused. A variety of models are used in practice that range from conceptual models of functional anatomy to nonlinear mathematical models of hemodynamic responses (e.g. as measured by functional magnetic resonance imaging, fMRI) and neuronal responses. In this review, we discuss the most important models used to analyse functional imaging data and demonstrate how they are interrelated. Initially, we briefly review the anatomical foundations of current theories of brain function on which all mathematical models rest. We then introduce some basic statistical models (e.g. the general linear model) used for making classical (i.e. frequentist) and Bayesian inferences about where neuronal responses are expressed. The more challenging question, how these responses are caused, is addressed by models that incorporate biophysical constraints (e.g. forward models from the neural to the hemodynamic level) and/or consider causal interactions between several regions, i.e. models of effective connectivity. Some of the most refined models to date are neuronal mass models of electroencephalographic (EEG) responses. These models enable mechanistic inferences about how evoked responses are caused, at the level of neuronal subpopulations and the coupling among them.

Current pathophysiological theories of schizophrenia highlight the role of altered brain connectivity. This dysconnectivity could manifest 1) anatomically, through structural changes of association fibers at the cellular level, and/or 2) functionally, through aberrant control of synaptic plasticity at the synaptic level. In this article, we review the evidence for these theories, focusing on the modulation of synaptic plasticity. In particular, we discuss how dysconnectivity, observed between brain regions in schizophrenic patients, could result from abnormal modulation of N-methyl-D-aspartate (NMDA)-dependent plasticity by other neurotransmitter systems. We focus on the implication of the dysconnection hypothesis for functional imaging at the systems level. In particular, we review recent advances in measuring plasticity in the human brain using functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) that can be used to address dysconnectivity in schizophrenia. Promising experimental paradigms include perceptual and reinforcement learning. We describe how theoretical and causal models of brain responses might contribute to a mechanistic understanding of synaptic plasticity in schizophrenia.

Traditionally the posterior parietal cortex was believed to be a sensory structure. More recently, however, its important role in sensory-motor integration has been recognized. One of its functions suggested in this context is the forming of intentions, i.e. high-level cognitive plans for movements. The selection and planning of a specific movement defines motor intention. In this study we used rapid event-related functional magnetic resonance imaging of healthy human subjects to investigate the involvement of posterior parietal cortex in motor intention in response to valid imperative cues. Subjects were provided with either neutral, motor or spatial cues. Neutral cues simply alerted, motor cues indicated which hand to use for response, and spatial cues indicated on which side the target would appear. Importantly, identical targets and responses followed these cues. Therefore any differential neural effects observed are independent from the actual movement performed. Differential blood oxygen level dependent signal changes for motor vs. neutral as well as motor vs. spatial cue trials were found in the left supramarginal gyrus, as hypothesized. The results demonstrate that neural activity in the left supramarginal gyrus underlies motor plans independent from the execution of the movement and thus extend previous neuropsychological and functional imaging data on the role of the left supramarginal gyrus in higher motor cognition.

Welche Faktoren entscheiden darüber, dass ein Kundenwert letztendlich so eingeführt werden kann, dass der Verkauf ihn als strategisches Verkaufs-Instrument erfolgswirksam zu nutzen vermag? Zu nennen sind vorausschauende Planung, systematische Bestimmung der Anforderungen und sorgfältige, auf die Anforderungen abgestimmte mathematische Formulierung der Berechnung. Weiter stellen der zielgerichtete Einbezug eines Data-Warehouses, eine akkurate statistische Modellierung, rasche und umsichtige Implementierung und vor allem eine detaillierte und fundierte Schulung des Außendienstes durch Marketingmitarbeiter wichtige Erfolgskriterien dar. Nach der ersten Implementierung ist es wichtig, das Projekt noch nicht als abgeschlossen zu betrachten, denn noch fehlt der Feinschliff. Dazu gehört die selbstkritische Überprüfung und nötigenfalls Verbesserung der Berechnung, sowie die Optimierung der Berechnungsperiodizität. Die kontinuierliche Schulung muss ebenfalls beibehalten werden, damit der Feedback generierende Kontakt zum Außendienst nicht abbricht. Aber auch gezielte Kommunikation bei den strategischen Organen des Unternehmens ist notwendig, um die Akzeptanz des Kundenwerts auf allen hierarchischen Stufen sicher zu stellen. Die konsequente Beachtung all dieser Prozessschritte war der Grund dafür, dass die vorliegende Case Study zur Erfolgsgeschichte wurde.

When requirements models are developed in an iterative and evolutionary way, requirements validation becomes a major problem. In order to detect and fix problems early, the specification should be validated as early as possible, and should also be revalidated after each evolutionary step. In this paper, we show how the ideas of continuous integration and automatic regression testing in the field of coding can be adapted for simulation-based, automatic revalidation of requirements models after each incremental step. While the basic idea is fairly obvious, we are confronted with a major obstacle: requirements models under development are incomplete and semi-formal most of the time, while classic simulation approaches require complete, formal models. We present how we can simulate incomplete, semi-formal models by interactively recording missing behavior or functionality. However, regression simulations must run automatically and do not permit interactivity. We therefore have developed a technique where the simulation engine automatically resorts to the interactively recorded behavior in those cases where it does not get enough information from the model during a regression simulation run. Finally, we demonstrate how the information gained from model evolution and regression simulation can be exploited for locating defects in the model.