Spatio-Temporal Credit Assignment in Neuronal Population Learning

n learning from trial and error, animals need to relate behavioral decisions to environmental reinforcement even though it may be difficult to assign credit to a particular decision when outcomes are uncertain or subject to delays. When considering the biophysical basis of learning, the credit-assignment problem is compounded because the behavioral decisions themselves result from the spatio-temporal aggregation of many synaptic releases. We present a model of plasticity induction for reinforcement learning in a population of leaky integrate and fire neurons which is based on a cascade of synaptic memory traces. Each synaptic cascade correlates presynaptic input first with postsynaptic events, next with the behavioral decisions and finally with external reinforcement. For operant conditioning, learning succeeds even when reinforcement is delivered with a delay so large that temporal contiguity between decision and pertinent reward is lost due to intervening decisions which are themselves subject to delayed reinforcement. This shows that the model provides a viable mechanism for temporal credit assignment. Further, learning speeds up with increasing population size, so the plasticity cascade simultaneously addresses the spatial problem of assigning credit to synapses in different population neurons. Simulations on other tasks, such as sequential decision making, serve to contrast the performance of the proposed scheme to that of temporal difference-based learning. We argue that, due to their comparative robustness, synaptic plasticity cascades are attractive basic models of reinforcement learning in the brain.

Towards Self-Learning Radio-Based Localization Systems

Location-awareness indoors will be an inseparable feature of mobile services/applications in future wireless networks. Its current ubiquitous availability is still obstructed by technological challenges and privacy issues. We propose an innovative approach towards the concept of indoor positioning with main goal to develop a system that is self-learning and able to adapt to various radio propagation environments. The approach combines estimation of propagation conditions, subsequent appropriate channel modelling and optimisation feedback to the used positioning algorithm. Main advantages of the proposal are decreased system set-up effort, automatic re-calibration and increased precision.

Functional neuroimaging of emotional learning and autonomic reactions

This article provides a selective overview of the functional neuroimaging literature with an emphasis on emotional activation processes. Emotions are fast and flexible response systems that provide basic tendencies for adaptive action. From the range of involved component functions, we first discuss selected automatic mechanisms that control basic adaptational changes. Second, we illustrate how neuroimaging work has contributed to the mapping of the network components associated with basic emotion families (fear, anger, disgust, happiness), and secondary dimensional concepts that organise the meaning space for subjective experience and verbal labels (emotional valence, activity/intensity, approach/withdrawal, etc.). Third, results and methodological difficulties are discussed in view of own neuroimaging experiments that investigated the component functions involved in emotional learning. The amygdala, prefrontal cortex, and striatum form a network of reciprocal connections that show topographically distinct patterns of activity as a correlate of up and down regulation processes during an emotional episode. Emotional modulations of other brain systems have attracted recent research interests. Emotional neuroimaging calls for more representative designs that highlight the modulatory influences of regulation strategies and socio-cultural factors responsible for inhibitory control and extinction. We conclude by emphasising the relevance of the temporal process dynamics of emotional activations that may provide improved prediction of individual differences in emotionality.

Radiation metabolomics. 3. Biomarker discovery in the urine of gamma-irradiated rats using a simplified metabolomics protocol of gas chromatography-mass spectrometry combined with random forests machine learning algorithm

Abstract Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas chromatography-mass spectrometry and open source software including random forests machine learning algorithm to uncover latent biomarkers of 3 Gy gamma radiation in rats. Urine was collected from six male Wistar rats and six sham-irradiated controls for 7 days, 4 prior to irradiation and 3 after irradiation. Water and food consumption, urine volume, body weight, and sodium, potassium, calcium, chloride, phosphate and urea excretion showed major effects from exposure to gamma radiation. The metabolomics protocol uncovered several urinary metabolites that were significantly up-regulated (glyoxylate, threonate, thymine, uracil, p-cresol) and down-regulated (citrate, 2-oxoglutarate, adipate, pimelate, suberate, azelaate) as a result of radiation exposure. Thymine and uracil were shown to derive largely from thymidine and 2'-deoxyuridine, which are known radiation biomarkers in the mouse. The radiation metabolomic phenotype in rats appeared to derive from oxidative stress and effects on kidney function. Gas chromatography-mass spectrometry is a promising platform on which to develop the field of radiation metabolomics further and to assist in the design of instrumentation for use in detecting biological consequences of environmental radiation release.

Livelihood and Community Development: LforS learning and simulation game

Up to 15 people can participate in the game, which is supervised by a moderator. Households consisting of 1-5 people discuss options for diversification of household strategies. Aim of the game: By devising appropriate strategies, households seek to stand up to various types of events while improving their economic and social situation and, at the same time, taking account of ecological conditions. The annual General Community Meeting (GCM) provides an opportunity for households to create a general set-up at the local level that is more or less favourable to the strategies they are pursuing. The development of a community investment strategy, to be implemented by the GCM, and successful coordination between households will allow players to optimise their investments at the household level. The household who owns the most assets at the end of the game wins. Players participate very actively, as the game stimulates lively and interesting discussions. They find themselves confronted with different types of decision-making related to the reality of their daily lives. They explore different ways to model their own household strategies and discuss risks and opportunities. Reflections on the course of the game continually refer to the real-life situations of the participants.

CONMICOM – conflict mitigation in communities: LforS learning and simulation game

Three extended families live around a lake. One family are rice farmers, the second family are vegetable farmers, and the third are a family of livestock herders. All of them depend on the use of lake water for their production, and all of them need large quantities of water. All are dependent on the use of the lake water to secure their livelihood. In the game, the families are represented by their councils of elders. Each of the councils has to find means and ways to increase production in order to keep up with the growth of its family and their demands. This puts more and more pressure on the water resources, increasing the risk of overuse. Conflicts over water are about to emerge between the families. Each council of elders must try to pursue its families interests, while at the same time preventing excessive pressure on the water resources. Once a council of elders is no longer able to meet the needs of its family, it is excluded from the game. Will the parties cooperate or compete? To face the challenge of balancing economic well-being, sustainable resource management, and individual and collective interests, the three parties have a set of options for action at hand. These include power play to safeguard their own interests, communication and cooperation to negotiate with neighbours, and searching for alternatives to reduce pressure on existing water resources. During the game the players can experience how tensions may arise, increase and finally escalate. They realise what impact power play has and how alliances form, and the importance of trust-building measures, consensus and cooperation. From the insights gained, important conflict prevention and mitigation measures are derived in a debriefing session. The game is facilitated by a moderator, and lasts for 3-4 hours. Aim of the game: Each family pursues the objective of serving its own interests and securing its position through appropriate strategies and skilful negotiation, while at the same time optimising use of the water resources in a way that prevents their degradation. The end of the game is open. While the game may end by one or two families dropping out because they can no longer secure their subsistence, it is also possible that the three families succeed in creating a situation that allows them to meet their own needs as well as the requirements for sustainable water use in the long term. Learning objectives The game demonstrates how tension builds up, increases, and finally escalates; it shows how power positions work and alliances are formed; and it enables the players to experience the great significance of mutual agreement and cooperation. During the game and particularly during the debriefing and evaluation session it is important to link experiences made during the game to the players’ real-life experiences, and to discuss these links in the group. The resulting insights will provide a basis for deducing important conflict prevention and transformation measures.

Taking up national safety alerts to improve patient safety in hospitals: The perspective of healthcare quality and risk managers.

BACKGROUND National safety alert systems publish relevant information to improve patient safety in hospitals. However, the information has to be transformed into local action to have an effect on patient safety. We studied three research questions: How do Swiss healthcare quality and risk managers (qm/rm(1)) see their own role in learning from safety alerts issued by the Swiss national voluntary reporting and analysis system? What are their attitudes towards and evaluations of the alerts, and which types of improvement actions were fostered by the safety alerts? METHODS A survey was developed and applied to Swiss healthcare risk and quality managers, with a response rate of 39 % (n=116). Descriptive statistics are presented. RESULTS The qm/rm disseminate and communicate with a broad variety of professional groups about the alerts. While most respondents felt that they should know the alerts and their contents, only a part of them felt responsible for driving organizational change based on the recommendations. However, most respondents used safety alerts to back up their own patient safety goals. The alerts were evaluated positively on various dimensions such as usefulness and were considered as standards of good practice by the majority of the respondents. A range of organizational responses was applied, with disseminating information being the most common. An active role is related to using safety alerts for backing up own patient safety goals. CONCLUSIONS To support an active role of qm/rm in their hospital's learning from safety alerts, appropriate organizational structures should be developed. Furthermore, they could be given special information or training to act as an information hub on the issues discussed in the alerts.