Posttraumatic stress disorder after implantation of a mechanical assist device followed by heart transplantation: evaluation of patients and partners

AIM: We sought to investigate the prevalence of posttraumatic stress disorder, anxiety, and depression in patients and their partners after implantation of a mechanical assist device as a bridge to heart transplantation. METHODS: This was a retrospective assessment of 41 patients (age 46.3 +/- 12.0 years; male-female ratio, 38:3; time since transplantation, 55.3 +/- 34.2 months [range, 7-122 months) and 27 partners (male-female ratio 2:25) by standardized instruments (Impact of Event Scale, Hospital Anxiety and Depression Scale), in 2 University Heart Transplant Centers (Vienna, Austria, Munster, Germany). The duration of the support systems (MicroMed DeBakey-VAD in 17 patients, Novacor in 10, Thoratec in 8, TCI HeartMate in 5, and Berlin Heart Incor in 1 patient) ranged from 28 to 711 (176 +/- 146) days. RESULTS: None of the patients, but 23% of the partners (n = 6), met the criteria for posttraumatic stress disorder (Maercker cutoff >0). The Impact of Event Scale (IES) sum scales differed significantly between the 2 groups (21.2 +/- 15.1, mean +/- SD) for the patients versus 38.1 +/- 27.8 for the partners, respectively; P = .001). Two percent of the patients, but 19% of the partners, showed mild to moderate depression; 4% of patients, but 23% of their partners, reported mild to moderate anxiety. None of the results were significantly influenced by the time since transplantation, patient age, diagnoses, type of assist device, or indication for heart transplantation. CONCLUSIONS: Despite patients being much closer to a life threat, their partners experience significantly more psychologic distress even in the long run. Our findings highlight the need for attention to the supporting persons.

Learning by the Dendritic Prediction of Somatic Spiking

Recent modeling of spike-timing-dependent plasticity indicates that plasticity involves as a third factor a local dendritic potential, besides pre- and postsynaptic firing times. We present a simple compartmental neuron model together with a non-Hebbian, biologically plausible learning rule for dendritic synapses where plasticity is modulated by these three factors. In functional terms, the rule seeks to minimize discrepancies between somatic firings and a local dendritic potential. Such prediction errors can arise in our model from stochastic fluctuations as well as from synaptic input, which directly targets the soma. Depending on the nature of this direct input, our plasticity rule subserves supervised or unsupervised learning. When a reward signal modulates the learning rate, reinforcement learning results. Hence a single plasticity rule supports diverse learning paradigms.

Learning by Not Doing: Subsidy Disciplines in Services Trade

This paper explores the hitherto futile quest for developing disciplines on the trade- and investment-distorting effects of services subsidies. It sheds light on the multiplicity of factors that have weighed on the conduct of negotiations on subsidy disciplines in a services trade context at both the global and preferential levels, and advances a few thoughts on what the future may hold for the adoption of such disciplines. The analysis suggests that it is rather unlikely that WTO Members will any time soon reach a consensus on the matter of subsidy disciplines for services beyond those that currently (and timidly) obtain in the GATS and in many preferential trade agreements. The main reason behind such a conclusion stems from a marked rise in the value of preserving policy space in a trading environment characterized by considerably greater global market contestability than two decades ago.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior. But behavioral decision making is likely to involve the integration of many synaptic events in space and time. So in using a single reinforcement signal to modulate synaptic plasticity a twofold problem arises. Different synapses will have contributed differently to the behavioral decision and, even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward but by a population feedback signal as well. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second one involves an action sequence which is itself extended in time and reward is only delivered at the last action, as is the case in any type of board-game. The third is the inspection game that has been studied in neuroeconomics. It only has a mixed Nash equilibrium and exemplifies that the model also copes with stochastic reward delivery and the learning of mixed strategies.

Learned irrelevance and associative learning is attenuated in individuals at risk for psychosis but not in asymptomatic first-degree relatives of schizophrenia patients: translational state markers of psychosis?

Learned irrelevance (LIrr) refers to a form of selective learning that develops as a result of prior noncorrelated exposures of the predicted and predictor stimuli. In learning situations that depend on the associative link between the predicted and predictor stimuli, LIrr is expressed as a retardation of learning. It represents a form of modulation of learning by selective attention. Given the relevance of selective attention impairment to both positive and cognitive schizophrenia symptoms, the question remains whether LIrr impairment represents a state (relating to symptom manifestation) or trait (relating to schizophrenia endophenotypes) marker of human psychosis. We examined this by evaluating the expression of LIrr in an associative learning paradigm in (1) asymptomatic first-degree relatives of schizophrenia patients (SZ-relatives) and in (2) individuals exhibiting prodromal signs of psychosis ("ultrahigh risk" [UHR] patients) in each case relative to demographically matched healthy control subjects. There was no evidence for aberrant LIrr in SZ-relatives, but LIrr as well as associative learning were attenuated in UHR patients. It is concluded that LIrr deficiency in conjunction with a learning impairment might be a useful state marker predictive of psychotic state but a relatively weak link to a potential schizophrenia endophenotype.

Mechanical circulatory support as a bridge to heart transplantation: what remains? Long-term emotional sequelae in patients and spouses

Implantation of a ventricular assist device (VAD) reduces short-term mortality and morbidity and provides patients with reasonable quality of life even though it may also be a long-lasting emotional burden. This study was conducted to analyze the long-time emotional consequences of VAD implantation, followed by heart transplantation in patients and spouses.

Learning software-maintenance tasks in offshoring projects: a cognitive-load perspective

Individual learning is central to the success of the transition phase in software mainte-nance offshoring projects. However, little is known on how learning activities, such as on-the-job training and formal presentations, are effectively combined during the tran-sition phase. In this study, we present and test propositions derived from cognitive load theory. The results of a multiple-case study suggest that learning effectiveness was highest when learning tasks such as authentic maintenance requests were used. Con-sistent with cognitive load theory, learning tasks were most effective when they imposed moderate cognitive load. Our data indicate that cognitive load was influenced by the expertise of the onsite coordinator, by intrinsic task complexity, by the degree of specifi-cation of tasks, and by supportive information. Cultural and semantic distances may in-fluence learning by inhibiting supportive information, specification, and the assignment of learning tasks.

Proteome analysis in cardiovascular pathophysiology using Dahl rat model

Dahl salt-sensitive (DS) and salt-resistant (DR) inbred rat strains represent a well established animal model for cardiovascular research. Upon prolonged administration of high-salt-containing diet, DS rats develop systemic hypertension, and as a consequence they develop left ventricular hypertrophy, followed by heart failure. The aim of this work was to explore whether this animal model is suitable to identify biomarkers that characterize defined stages of cardiac pathophysiological conditions. The work had to be performed in two stages: in the first part proteomic differences that are attributable to the two separate rat lines (DS and DR) had to be established, and in the second part the process of development of heart failure due to feeding the rats with high-salt-containing diet has to be monitored. This work describes the results of the first stage, with the outcome of protein expression profiles of left ventricular tissues of DS and DR rats kept under low salt diet. Substantial extent of quantitative and qualitative expression differences between both strains of Dahl rats in heart tissue was detected. Using Principal Component Analysis, Linear Discriminant Analysis and other statistical means we have established sets of differentially expressed proteins, candidates for further molecular analysis of the heart failure mechanisms.

Rationale, scope, and 20-year experience of vascular surgical training with lifelike pulsatile flow models

Vascular surgical training currently has to cope with various challenges, including restrictions on work hours, significant reduction of open surgical training cases in many countries, an increasing diversity of open and endovascular procedures, and distinct expectations by trainees. Even more important, patients and the public no longer accept a "learning by doing" training philosophy that leaves the learning curve on the patient's side. The Vascular International (VI) Foundation and School aims to overcome these obstacles by training conventional vascular and endovascular techniques before they are applied on patients. To achieve largely realistic training conditions, lifelike pulsatile models with exchangeable synthetic arterial inlays were created to practice carotid endarterectomy and patch plasty, open abdominal aortic aneurysm surgery, and peripheral bypass surgery, as well as for endovascular procedures, including endovascular aneurysm repair, thoracic endovascular aortic repair, peripheral balloon dilatation, and stenting. All models are equipped with a small pressure pump inside to create pulsatile flow conditions with variable peak pressures of ~90 mm Hg. The VI course schedule consists of a series of 2-hour modules teaching different open or endovascular procedures step-by-step in a standardized fashion. Trainees practice in pairs with continuous supervision and intensive advice provided by highly experienced vascular surgical trainers (trainer-to-trainee ratio is 1:4). Several evaluations of these courses show that tutor-assisted training on lifelike models in an educational-centered and motivated environment is associated with a significant increase of general and specific vascular surgical technical competence within a short period of time. Future studies should evaluate whether these benefits positively influence the future learning curve of vascular surgical trainees and clarify to what extent sophisticated models are useful to assess the level of technical skills of vascular surgical residents at national or international board examinations. This article gives an overview of our experiences of >20 years of practical training of beginners and advanced vascular surgeons using lifelike pulsatile vascular surgical training models.

Distance measures for image segmentation evaluation

The task considered in this paper is performance evaluation of region segmentation algorithms in the ground-truth-based paradigm. Given a machine segmentation and a ground-truth segmentation, performance measures are needed. We propose to consider the image segmentation problem as one of data clustering and, as a consequence, to use measures for comparing clusterings developed in statistics and machine learning. By doing so, we obtain a variety of performance measures which have not been used before in image processing. In particular, some of these measures have the highly desired property of being a metric. Experimental results are reported on both synthetic and real data to validate the measures and compare them with others.

Perceptual Training in Beach Volleyball Defence: Different Effects of Gaze-Path Cueing on Gaze and Decision-Making

For perceptual-cognitive skill training, a variety of intervention methods has been proposed, including the so-called “color-cueing method” which aims on superior gaze-path learning by applying visual markers. However, recent findings challenge this method, especially, with regards to its actual effects on gaze behavior. Consequently, after a preparatory study on the identification of appropriate visual cues for life-size displays, a perceptual-training experiment on decision-making in beach volleyball was conducted, contrasting two cueing interventions (functional vs. dysfunctional gaze path) with a conservative control condition (anticipation-related instructions). Gaze analyses revealed learning effects for the dysfunctional group only. Regarding decision-making, all groups showed enhanced performance with largest improvements for the control group followed by the functional and the dysfunctional group. Hence, the results confirm cueing effects on gaze behavior, but they also question its benefit for enhancing decision-making. However, before completely denying the method’s value, optimisations should be checked regarding, for instance, cueing-pattern characteristics and gaze-related feedback.