Detailed Modelling of
Signal Processing in Neurons
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DMSPiN: Detailed Modelling of Signal Processing in Neurons

Neurons are the basic unit of information processing in the brain, controlling the dynamic processes. Thus, understanding signal processing in neurons is basic to understanding the brain. The aim of the present proposal for a Bernstein-Group is the understanding how spatial and temporal dynamics are controlled on the level of neurons and microcircuits. To that end, unsteady models with three dimensional space resolution of subcellular features will be created leading to large coupled systems of partial differential equations. These models have the potential to yield very accurate information about spatial and temporal dynamics and their interaction, forming the basis for the complex dynamics of the neural system. This work requires interdisciplinary cooperation connecting techniques from molecular biology, image processing, electro physiology, high resolution microscopy and tools from mathematical modeling, numerical solvers and large scale supercomputing. Our aim is to get insight into the basic principles by which interacting proteins, neurons and microcircuits process information, form structures and coordinate their dynamics.

Several visionary aims concerning applications and later impact are behind the objectives and project work in DMSPiN. Finally, this endeavor will result in innovations and advances related to our understanding of disease. Important human conditions like Parkinsons disease, epilepsy, chronic pain or depression result from disturbances in the homeostasis of cellular networks. A deepened insight into these complex relationships will identify novel therapeutic targets. The diseases investigated are a major factor in global burden of disease, and novel strategies for prevention and treatment will have enormous impact on public health and economy.

Modeling of Pharmacological Effects
A possible application of the detailed models developed by DMSPiN is to simulate the effects of changes in the extracellular milieu and of pharmacological compounds on single-cell and network activity. Such simulations can have a massive impact on understanding the pathophysiological basis of brain diseases that manifest themselves as altered network excitability such as for example epilepsy. Simulations of this kind necessarily require a detailed characterisation at the cellular level and have to be run on realistic configurations, both of which are major aims of our proposal.

Understanding the interplay between subcellular and cellular mechanisms and their influence on the dynamics of microcircuits. This is a very challenging topic containing the key to understanding organization and structure of microcircuits. Such a understanding requires a very precise mapping of the physico-chemical processes and the structure to mathematics, which meets the objectives of DMSPiN. Using our expertise in detailed and data-driven modelling and in large scale high-performance computing, we expect new insight into neuron and microcircuit dynamics.

Understanding and testing plasticity mechanisms. 
A large variety of local i.e. cellular plasticity mechanisms has been documented over the last decades. Once our mechanistic model is in effect, we are able to test these hypotheses on the basis of our models. This eventually may be applied to sensory and motor learning.

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