Improving memory in elderly adults by instructing them in professional actors' learning strategies

This study examined a new type of cognitive intervention. For four weeks, participants (ages 65 to 82) were instructed in professional acting techniques, followed by rehearsal and performance of theatrical scenes. Although the training was not targeted in any way to the tasks used in pre- and post-testing, participants produced significantly higher recall and recognition scores after the intervention. It is suggested that the cognitive effort involved in analyzing and adopting theatrical characters' motivations (and then experiencing those characters' mental/emotional states during performance) is responsible for the observed improvement. A secondary strand of this study showed that participants who were given annotated scripts in which the implied goals of the characters were made explicit demonstrated significantly faster access to the stored material, as measured by a computer latency task.

Performance of undergraduate dental students on ICDAS clinical caries detection after different learning strategies

AIM This study aimed to evaluate the effect of a digital learning tool on undergraduate dental students' performance in detecting dental caries using ICDAS. METHODS An experimental digital learning tool (DLT) was created using digital photographs of sound and carious teeth. Thirty-nine students were divided into three groups (n = 13) and each assessed 12 randomly allocated patients before and after learning strategies: G1, ICDAS e-learning program; G2, ICDAS e-learning program plus DLT; G3, no learning strategy. Students (n = 32) reassessed patients 2 weeks after training. RESULTS Comparing before and after the learning strategies, any difference in the values of specificity and area under the ROC curve for all groups was found. Sensitivity was statistically significantly higher for G1 and G2. Comparing the groups, G2 showed a significant increase in sensitivity at the D2 and D3 thresholds. Spearman's correlations with the gold standard before and after the learning strategy were 0.60 and 0.61 for G1, 0.57 and 0.63 for G2, and 0.54 and 0.54 for G3, respectively. The Wilcoxon test showed a statistically significant difference between the values obtained before and after learning strategies for G1 and G2. CONCLUSIONS Use of the DLT after the ICDAS e-learning program tended to increase the sensitivity of ICDAS used by undergraduate dental students. The DLT appeared to improve dental students' ability to use ICDAS.

Building a soil spectral library for Tajikistan comparing local and global modeling approaches

Over the last ~20 years, soil spectral libraries storing near-infrared reflectance (NIR) spectra from diverse soil samples have been built for many places, since almost 10 years also for Tajikistan. Many calibration approaches have been reported and used for prediction from large and heterogeneous libraries, but most are hampered by the high diversity of the soils, where the mineral background is heavily influencing spectral features. In such cases, local learning strategies have the advantage of building locally adapted calibrations, which can deal better with nonlinearities. Therefore, it was our major aim to identify the most efficient approach to develop an accurate and stable locally weigthed calibration model using a spectral library compiled over the past years. Keywords: Tajikistan, Near-Infrared spectroscopy (NIRS), soil organic carbon, locally weighted regression, regional and local spectral library.

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.

Exploring the effectiveness of development research with a monitoring and learning approach

There is a growing demand for better understanding of the link between research, policy and practice in development. This article provides findings from a study that aimed to gain insights into how researchers engage with their non-academic partners. It draws on experiences from the National Centre of Competence in Research North-South programme, a development research network of Swiss, African, Asian and Latin American institutions. Conceptually, this study is concerned with research effectiveness as a means to identify knowledge useful for society. Research can be improved and adapted when monitoring the effects of interactions between researchers and non-academic partners. Therefore, a monitoring and learning approach was chosen. This study reveals researchers' strategies in engaging with non-academic partners and points to framing conditions considered decisive for soccessful interactions. It concludes that reserachrs need to systematically analyse the socio-political context in which they intervene. By providing insights from the ground and reflecting on them in the light of the latest theoretical concepts, this article contributes to the emerging literature founded on practice-based experience.

Spike-based decision learning of nash equilibria in two-player games

Humans and animals face decision tasks in an uncertain multi-agent environment where an agent's strategy may change in time due to the co-adaptation of others strategies. The neuronal substrate and the computational algorithms underlying such adaptive decision making, however, is largely unknown. We propose a population coding model of spiking neurons with a policy gradient procedure that successfully acquires optimal strategies for classical game-theoretical tasks. The suggested population reinforcement learning reproduces data from human behavioral experiments for the blackjack and the inspector game. It performs optimally according to a pure (deterministic) and mixed (stochastic) Nash equilibrium, respectively. In contrast, temporal-difference(TD)-learning, covariance-learning, and basic reinforcement learning fail to perform optimally for the stochastic strategy. Spike-based population reinforcement learning, shown to follow the stochastic reward gradient, is therefore a viable candidate to explain automated decision learning of a Nash equilibrium in two-player games.

Learning from failure--rationale and design for a study about discontinuation of randomized trials (DISCO study)

Background Randomized controlled trials (RCTs) may be discontinued because of apparent harm, benefit, or futility. Other RCTs are discontinued early because of insufficient recruitment. Trial discontinuation has ethical implications, because participants consent on the premise of contributing to new medical knowledge, Research Ethics Committees (RECs) spend considerable effort reviewing study protocols, and limited resources for conducting research are wasted. Currently, little is known regarding the frequency and characteristics of discontinued RCTs. Methods/Design Our aims are, first, to determine the prevalence of RCT discontinuation for specific reasons; second, to determine whether the risk of RCT discontinuation for specific reasons differs between investigator- and industry-initiated RCTs; third, to identify risk factors for RCT discontinuation due to insufficient recruitment; fourth, to determine at what stage RCTs are discontinued; and fifth, to examine the publication history of discontinued RCTs. We are currently assembling a multicenter cohort of RCTs based on protocols approved between 2000 and 2002/3 by 6 RECs in Switzerland, Germany, and Canada. We are extracting data on RCT characteristics and planned recruitment for all included protocols. Completion and publication status is determined using information from correspondence between investigators and RECs, publications identified through literature searches, or by contacting the investigators. We will use multivariable regression models to identify risk factors for trial discontinuation due to insufficient recruitment. We aim to include over 1000 RCTs of which an anticipated 150 will have been discontinued due to insufficient recruitment. Discussion Our study will provide insights into the prevalence and characteristics of RCTs that were discontinued. Effective recruitment strategies and the anticipation of problems are key issues in the planning and evaluation of trials by investigators, Clinical Trial Units, RECs and funding agencies. Identification and modification of barriers to successful study completion at an early stage could help to reduce the risk of trial discontinuation, save limited resources, and enable RCTs to better meet their ethical requirements.

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.

[In search of strategies for preventing brain damage as a sequela of bacterial meningitis]

Multiplication of bacteria within the central nervous system compartment triggers a host response with an overshooting inflammatory reaction which leads to brain parenchyma damage. Some of the inflammatory and neurotoxic mediators involved in the processes leading to neuronal injury during bacterial meningitis have been identified in recent years. As a result, the therapeutic approach to the disease has widened from eradication of the bacterial pathogen with antibiotics to attenuation of the detrimental effects of host defences. Corticosteroids represent an example of the adjuvant therapeutic strategies aimed at downmodulating excessive inflammation in the infected central nervous system. Pathophysiological concepts derived from an experimental rat model of bacterial meningitis revealed possible therapeutic strategies for prevention of brain damage. The insights gained led to the evaluation of new therapeutic modalities such as anticytokine agents, matrix metalloproteinase inhibitors, antioxidants, and antagonists of endothelin and glutamate. Bacterial meningitis is still associated with persistent neurological sequelae in approximately one third of surviving patients. Future research in the model will evaluate whether the neuroprotective agents identified so far have the potential to attenuate learning disabilities as a long-term consequence of bacterial meningitis.

Agrarian learning processes in Switzerland 1918–1939

This paper examines the social impacts of weather extremes and the processes of social and communicative learning a society undertakes to find alternative ways to deal with the consequences of a crisis. In the beginning of the 20th Century hunger seemed to be expelled from Europe. Switzerland – like many other European countries – was involved in a global interdependent trade system, which provided necessary goods. But at the end of World War I very cold and wet summers in 1916/17 (causing crop failure) and the difficulties in war-trade led to malnutrition and enormous price risings of general living-standards in Switzerland, which shocked the people and caused revolutionary uprisings in 1918. The experience of malnutrition during the last two years of war made clear that the traditional ways of food supply in Switzerland lacked crisis stability. Therefore various agents in the field of food production, distribution and consumption searched for alternative ways of food supply. In that sense politicians, industrialists, consumer-groups, left-wing communitarians and farmers developed several strategies for new ways in food production. Traditionally there were political conflicts in Switzerland between farmers and consumers regarding price policies, which led mainly to the conflict in 1918. Consumers accused famers of holding back food to control extortionate prices while the farmers pointed to the bad harvest causing the price rising. The collaboration of these groups in search for new forms of food-stability made social integration possible again. In addition to other crisis-factors, weather extremes can have disastrous impacts and destroy a society’s self-confidence to its core. But even such crisis can lead to processes of substantial learning that allows a regeneration of confidence and show positive influence on political stabilization. The paper focuses on the process of learning and the alternative methods of food production that were suggested by various agents working in the field during the Interwar period. To achieve that goal documents of the various associations are analyzed and newspapers have been taken into consideration. Through the method of discourse-analysis of food-production during the Interwar period, possible solutions that crossed the minds of the agents should be brought to light.

Russian language maintenance through bedtime story reading?: Linguistic strategies and language negotiation in Russian-French speaking families in Switzerland

This article proposes an interactional approach to the question of Russian language maintenance through the activity of bedtime story-reading in Russian-French bilingual families in French speaking Switzerland. Reading stories appears to be a language maintenance strategy commonly employed by the Russian speaking parent. The ritual and recreational moment of story-reading therefore becomes an opportunity for language learning. Drawing upon a language socialization perspective, this paper proposes an interactional analysis of the language use in the activity of story-reading. It shows how the language choice of the participants may be requested, negotiated and challenged during the interaction. The analysis further informs us about the language choice pattern and the bilingual competences in these families. We will gain insight into (Russian) language maintenance as a daily social and linguistic practice.

Envisioning sustainable water futures in a transdisciplinary learning process: combining normative, explorative, and participatory scenario approaches

Competing water demands for household consumption as well as the production of food, energy, and other uses pose challenges for water supply and sustainable development in many parts of the world. Designing creative strategies and learning processes for sustainable water governance is thus of prime importance. While this need is uncontested, suitable approaches still have to be found. In this article we present and evaluate a conceptual approach to scenario building aimed at transdisciplinary learning for sustainable water governance. The approach combines normative, explorative, and participatory scenario elements. This combination allows for adequate consideration of stakeholders’ and scientists’ systems, target, and transformation knowledge. Application of the approach in the MontanAqua project in the Swiss Alps confirmed its high potential for co-producing new knowledge and establishing a meaningful and deliberative dialogue between all actors involved. The iterative and combined approach ensured that stakeholders’ knowledge was adequately captured, fed into scientific analysis, and brought back to stakeholders in several cycles, thereby facilitating learning and co-production of new knowledge relevant for both stakeholders and scientists. However, the approach also revealed a number of constraints, including the enormous flexibility required of stakeholders and scientists in order for them to truly engage in the co-production of new knowledge. Overall, the study showed that shifts from strategic to communicative action are possible in an environment of mutual trust. This ultimately depends on creating conditions of interaction that place scientists’ and stakeholders’ knowledge on an equal footing.

Children's deliberate memory development: The contribution of strategies and metacognitive processes

This chapter focus is laid on the development of memory skills when children are confronted with a task or a situation in which learning or remembering certain target information is crucial. It presents important milestones toward self-regulated learning skills. The chapter discusses precursors of later strategic behaviors and metacognitive skills, the distinct research methods suitable to assessing early indicators of deliberate memory skills, as well as their importance for the emerging memory skills. It outlines the challenges arising from the application of deliberate memory skills in naturalistic, complex task contexts. The chapter adopted an explicit developmental perspective of memory strategies and metacognition in deliberate memory situations.