ERC FUNDED PROJECTS

A persistent challenge in unravelling mechanisms that regulate memory function is how to bridge the gap between inter-molecular dynamics of single proteins, activity of individual synapses and emerging properties of neuronal circuits. The prototype condition of disintegrating neuronal circuits is Alzheimer’s Disease (AD). Since the early time of Alois Alzheimer at the turn of the 20th century, scientists have been searching for a molecular entity that is in the roots of the cognitive deficits. Although diverse lines of evidence suggest that the amyloid-beta peptide (Abeta) plays a central role in synaptic dysfunctions of AD, several key questions remain unresolved. First, endogenous Abeta peptides are secreted by neurons throughout life, but their physiological functions are largely unknown. Second, experience-dependent physiological mechanisms that initiate the changes in Abeta composition in sporadic, the most frequent form of AD, are unidentified. And finally, molecular mechanisms that trigger Abeta-induced synaptic failure and memory decline remain elusive. To target these questions, I propose to develop an integrative approach to correlate structure and function at the level of single synapses in hippocampal circuits. State-of-the-art techniques will enable the simultaneous real-time visualization of inter-molecular dynamics within signalling complexes and functional synaptic modifications. Utilizing FRET spectroscopy, high-resolution optical imaging, electrophysiology, molecular biology and biochemistry we will determine the casual relationship between ongoing neuronal activity, temporo-spatial dynamics and molecular composition of Abeta, structural rearrangements within the Abeta signalling complexes and plasticity of single synapses and whole networks. The proposed research will elucidate fundamental principles of neuronal circuits function and identify critical steps that initiate primary synaptic dysfunctions at the very early stages of sporadic AD.

2 000 000 €

Start date: 2011-12-01, End date: 2017-09-30

Applied mathematics is concerned with developing models with predictive capability, and with probing those models to obtain qualitative and quantitative insight into the phenomena being modelled. Statistics is data-driven and is aimed at the development of methodologies to optimize the information derived from data. The increasing complexity of phenomena that scientists and engineers wish to model, together with our increased ability to gather, store and interrogate data, mean that the subjects of applied mathematics and statistics are increasingly required to work in conjunction. This research proposal is concerned with a research program at the interface between these two disciplines, aimed at problems in differential equations where profusion of data and the sophisticated model combine to produce the mathematical problem of obtaining information from a probability measure on function space. Applications are far-reaching and include the atmospheric sciences, geophysics, chemistry, econometrics and signal processing. The objectives of the research are: (i) to create the systematic foundations for a range of problems at the applied mathematics and statistics interface which share the common mathematical structure underpinning the range of applications described above; (ii) to exploit this common mathematical structure to design effecient algorithms to sample probability measures on function space; (iii) to apply these algorithms to attack a range of significant problems arising in molecular dynamics and in the atmospheric sciences.

1 693 501 €

Start date: 2008-12-01, End date: 2014-11-30

The proposal consists of an extensive research program to advance the understanding of singular integral operators of Harmonic Analysis in various situations on the borderline of the existing theory. This is to be achieved by a creative combination of techniques from Analysis and Probability. On top of the standard arsenal of modern Harmonic Analysis, the main probabilistic tools are the martingale transform inequalities of Burkholder, and random geometric constructions in the spirit of the random dyadic cubes introduced to Nonhomogeneous Analysis by Nazarov, Treil and Volberg. The problems to be addressed fall under the following subtitles, with many interconnections and overlap: (i) sharp weighted inequalities; (ii) nonhomogeneous singular integrals on metric spaces; (iii) local Tb theorems with borderline assumptions; (iv) functional calculus of rough differential operators; and (v) vector-valued singular integrals. Topic (i) is a part of Classical Analysis, where new methods have led to substantial recent progress, culminating in my solution in July 2010 of a celebrated problem on the linear dependence of the weighted operator norm on the Muckenhoupt norm of the weight. The proof should be extendible to several related questions, and the aim is to also address some outstanding open problems in the area. Topics (ii) and (v) deal with extensions of the theory of singular integrals to functions with more general domain and range spaces, allowing them to be abstract metric and Banach spaces, respectively. In case (ii), I have recently been able to relax the requirements on the space compared to the established theories, opening a new research direction here. Topics (iii) and (iv) are concerned with weakening the assumptions on singular integrals in the usual Euclidean space, to allow certain applications in the theory of Partial Differential Equations. The goal is to maintain a close contact and exchange of ideas between such abstract and concrete questions.

1 100 000 €

Start date: 2011-11-01, End date: 2016-10-31

Brain consists of two basic cell types – neurons and glia. However, the study of glia in brain function has traditionally been neglected in favor of their more “illustrious” counter-parts – neurons that are classed as the computational units of the brain. Glia have usually been classed as “brain glue” - a supportive matrix on which neurons grow and function. However, recent evidence suggests that glia are more than passive “glue” and actually modulate neuronal function. This has lead to the proposal of a “tripartite synapse”, which recognizes pre- and postsynaptic neuronal elements and glia as a unit. However, what is still lacking is rudimentary information on how these cells actually function in situ. Here we propose taking a “bottom-up” approach, by identifying the molecules (and interactions) that control glial function in situ. This is complicated by the fact that glia show profound changes when placed into culture. To circumvent this, we will use recently developed cell sorting techniques, to rapidly isolate genetically marked glial cells from brain – which can then be analyzed using advanced biochemical and physiological techniques. The long-term aim is to identify proteins that can be “tagged” using transgenic technologies to allow protein function to be studied in real-time in vivo, using sophisticated imaging techniques. Given the number of proteins that may be identified we envisage developing new methods of generating transgenic animals that provide an attractive alternative to current “state-of-the art” technology. The importance of studying glial function is given by the fact that every major brain pathology shows reactive gliosis. In the time it takes to read this abstract, 5 people in the EU will have suffered a stroke – not to mention those who suffer other forms of neurotrauma. Thus, understanding glial function is not only critical to understanding normal brain function, but also for relieving the burden of severe neurological injury and disease

1 490 168 €

Start date: 2012-01-01, End date: 2016-12-31