Deep brain stimulation for movement disorder treatment: exploring frequency-dependent efficacy in a computational network model

A large-scale computational model of the basal ganglia network and thalamus is proposed to describe movement disorders and treatment effects of deep brain stimulation (DBS). The model of this complex network considers three areas of the basal ganglia region: the subthalamic nucleus (STN) as target area of DBS, the globus pallidus, both pars externa and pars interna (GPe-GPi), and the thalamus. Parkinsonian conditions are simulated by assuming reduced dopaminergic input and corresponding pronounced inhibitory or disinhibited projections to GPe and GPi. Macroscopic quantities are derived which correlate closely to thalamic responses and hence motor programme fidelity. It can be demonstrated that depending on different levels of striatal projections to the GPe and GPi, the dynamics of these macroscopic quantities (synchronisation index, mean synaptic activity and response efficacy) switch from normal to Parkinsonian conditions. Simulating DBS of the STN affects the dynamics of the entire network, increasing the thalamic activity to levels close to normal, while differing from both normal and Parkinsonian dynamics. Using the mentioned macroscopic quantities, the model proposes optimal DBS frequency ranges above 130 Hz.

Mathematization of nature: how it is done

Natural phenomena can be quantitatively described by means of mathematics, which is actually the only way of doing so. Physics is a convincing example of the mathematization of nature. This paper gives an answer to the question of how mathematization of nature is done and illustrates the answer. Here nature is to be taken in a wide sense, being a substantial object of study in, among others, large domains of biology, such as epidemiology and neurobiology, chemistry, and physics, the most outspoken example. It is argued that mathematization of natural phenomena needs appropriate core concepts that are intimately connected with the phenomena one wants to describe and explain mathematically. Second, there is a scale on and not beyond which a specific description holds. Different scales allow for different conceptual and mathematical descriptions. This is the scaling hypothesis, which has meanwhile been confirmed on many occasions. Furthermore, a mathematical description can, as in physics, but need not be universally valid, as in biology. Finally, the history of science shows that only an intensive gauging of theory, i.e., mathematical description, by experiment leads to progress. That is, appropriate core concepts and appropriate scales are a necessary condition for mathematizing nature, and so is its verification by experiment.

Freshwater organisms potentially useful as biosensors and power-generation mediators in biohybrid robotics

Facing the threat of rapidly worsening water quality, there is an urgent need to develop novel approaches of monitoring its global supplies and early detection of environmental fluctuations. Global warming, urban growth and other factors have threatened not only the freshwater supply but also the well-being of many species inhabiting it. Traditionally, laboratory-based studies can be both time and money consuming and so, the development of a real-time, continuous monitoring method has proven necessary. The use of autonomous, self-actualizing entities became an efficient way of monitoring the environment. The Microbial Fuel Cells (MFC) will be investigated as an alternative energy source to allow for these entities to self-actualize. This concept has been improved with the use of various lifeforms in the role of biosensors in a structure called ”biohybrid” which we aim to develop further within the framework of project Robocoenosis relying on animal-robot interaction. We introduce a novel concept of a fully autonomous biohybrid agent with various lifeforms in the role of biosensors. Herein, we identify most promising organisms in the context of underwater robotics, among others Dreissena polymorpha, Anodonta cygnaea, Daphnia sp. and various algae. Special focus is placed on the ”ecosystem hacking” based on their interaction with the electronic parts. This project uses Austrian lakes of various trophic levels (Millstättersee, Hallstättersee and Neusiedlersee) as case studies and as a ”proof of concept”.