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.

Contemplating a ‘public service navigator’: In search of new (and better) functioning public service media

This is a paper contemplating a tool of public editorial intelligence, so that key media policy objectives can be attained in the complex and multi-faceted environment of digital media. The paper is meant to be an article of a special issue of the International Journal of Communication on "Public Media and Exposure Diversity", co-edited by Natali Helberger and Mira Burri.

Interactional behaviour as a marker for screening patients with environment-related complaints

BACKGROUND: Adequate assessment of symptoms of patients suffering from environmental illnesses requires appropriate procedures such as psychological and psychiatric diagnostics, medical screening and a thorough analysis of noxious environmental factors. The Basel pilot research project established a multi-methodological assessment procedure that meets these criteria. However, an exhaustive three-fold analysis is very costly in terms of both equipment and personnel, and hence the need for a heuristic approach and pre-screening persists. METHOD: The three-fold diagnostic approach was preceded by a structured psychodynamic interview; the findings were used to construct a new profile of the patient's interactional behaviour (IB) in conjunction with the interviewer's countertransference. The extent to which this new profile could predict the results of the multi-method assessment was then assessed. RESULTS: A low level of IB on the part of the patient significantly predicted the degree of stress and the extent of the psychiatric diagnosis, including personality disorders. A negative IB was associated with negative personality traits. Furthermore, a high level of IB implied more medical, but not more environmental, findings which could plausibly be related to the patient's complaints. CONCLUSIONS: Assessment of patients' IB in conjunction with one's own countertransference is very helpful as a preliminary heuristic approach and may lead to consequences for treatment and therapy. Therefore, the training provided for experts who deal with patients suffering from environment-related complaints should place more specific emphasis on assessing patients' behaviour and on incorporating information gathered from countertransference. Nevertheless, an interdisciplinary assessment including medical, psychological/psychiatric, and environmental expertise remains mandatory for adequate and satisfactory diagnosis of patients with environment-related complaints.

Virtual Cilicia Project. How to use Google Earth as a visualization environment in an archaeological context

Over the past few years, archaeology has experienced a rapid development in geophysical prospection and remote sensing techniques. At the same time, the focus of archaeological research has shifted to landscape evelopment and human interaction. To impart the results, new methods and techniques are necessary. Virtual globes such as Google Earth offer fascinating methods of giving interested amateurs the possibility to interactively explore ancient cities and landscapes. Thanks to the increasing usage of GIS in cultural heritage, the implementation of interactive three dimensional learning opportunities becomes less and less tedious, but the non-linear narrative story telling medium demands for a special adaption of the content. This paper summarizes the experience gained during the realization of the “Virtual Cilicia Project” and outlines the future potential of virtual globes in the field of cultural heritage.

Environment and climate of the last 51,000 years – new insights from the Potrok Aike maar lake Sediment Archive Drilling prOject (PASADO)

In this introductory paper we summarize the history and achievements of the Potrok Aike maar lake Sediment Archive Drilling prOject (PASADO), an interdisciplinary project embedded in the International Continental Scientific Drilling Program (ICDP). The stringent multiproxy approach adopted in this research combined with radiocarbon and luminescence dating provided the opportunity to synthesize a large body of hydrologically relevant data from Laguna Potrok Aike (southern Patagonia, Argentina). At this site, lake level was high from 51 ka until the early Holocene when the Southern Hemisphere Westerlies (SHW) were located further to the north. At 9.3 ka cal. BP the SHW moved southward and over the latitude of the study area (52 degrees S) causing a pronounced negative water balance with a lake level decrease of more than 50 m. Two millennia later, the SHW diminished in intensity and lake level rose to a subsequent maximum during the Little Ice Age. Since the 20th century, a strengthening of the SHW increased the evaporative stress resulting in a more negative water balance. A comparison of our data with other hydrological fluctuations at a regional scale in south-eastern Patagonia, provides new insights and also calls for better chronologies and high-resolution records of climate variability.

Multi-Environment Model Estimation for Motility Analysis of Caernorhabditis elegans

The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.