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

In a typical learning problem one tries to approximate an unknown function by a function from a given class using random data, sampled according to an unknown measure. In this project we will be interested in parameters that govern the complexity of a learning problem. It turns out that this complexity is determined by the geometry of certain sets in high dimension that are connected to the given class (random coordinate projections of the class). Thus, one has to understand the structure of these sets as a function of the dimension - which is given by the cardinality of the random sample. The resulting analysis leads to many theoretical questions in Asymptotic Geometric Analysis, Probability (most notably, Empirical Processes Theory) and Combinatorics, which are of independent interest beyond the application to Learning Theory. Our main goal is to describe the role of various complexity parameters involved in a learning problem, to analyze the connections between them and to investigate the way they determine the geometry of the relevant high dimensional sets. Some of the questions we intend to tackle are well known open problems and making progress towards their solution will have a significant theoretical impact. Moreover, this project should lead to a more complete theory of learning and is likely to have some practical impact, for example, in the design of more efficient learning algorithms.

750 000 €

Start date: 2009-03-01, End date: 2014-02-28

Since their discovery, Quantum Hall Effects have unfolded intriguing avenues of research, exhibiting a multitude of unexpected exotic states: accurate quantized conductance states; particle-like and hole-conjugate fractional states; counter-propagating charge and neutral edge modes; and fractionally charged quasiparticles - abelian and (predicted) non-abelian. Since the sought-after anyonic statistics of fractional states is yet to be verified, I propose to launch a thorough search for it employing new means. I believe that our studies will serve the expanding field of the emerging family of topological materials. Our on-going attempts to observe quasiparticles (qp’s) interference, in order to uncover their exchange statistics (under ERC), taught us that spontaneous, non-topological, ‘neutral edge modes’ are the main culprit responsible for qp’s dephasing. In an effort to quench the neutral modes, we plan to develop a new class of micro-size interferometers, based on synthetically engineered fractional modes. Flowing away from the fixed physical edge, their local environment can be controlled, making it less hospitable for the neutral modes. Having at hand our synthetized helical-type fractional modes, it is highly tempting to employ them to form localize para-fermions, which will extend the family of exotic states. This can be done by proximitizing them to a superconductor, or gapping them via inter-mode coupling. The less familiar thermal conductance measurements, which we recently developed (under ERC), will be applied throughout our work to identify ‘topological orders’ of exotic states; namely, distinguishing between abelian and non-abelian fractional states. The proposal is based on an intensive and continuous MBE effort, aimed at developing extremely high purity, GaAs based, structures. Among them, structures that support our new synthetic modes that are amenable to manipulation, and others that host rare exotic states, such as v=5/2, 12/5, 19/8, and 35/16.

1 801 094 €

Start date: 2019-05-01, End date: 2024-04-30

Axon growth potential declines during development, contributing to the lack of effective regeneration in the adult central nervous system. What determines the intrinsic growth potential of neurites, and how such growth is regulated during development, disease and following injury is a fundamental question in neuroscience. Although multiple lines of evidence indicate that intrinsic growth capability is genetically encoded, its nature remains poorly defined. Neuronal remodeling of the Drosophila mushroom body offers a unique opportunity to study the mechanisms of various types of axon degeneration and growth. We have recently demonstrated that regrowth of axons following developmental pruning is not only distinct from initial outgrowth but also shares molecular similarities with regeneration following injury. In this proposal we combine state of the art tools from genomics, functional genetics and microscopy to perform a comprehensive study of the mechanisms underlying axon growth during development and following injury. First, we will combine genetic, biochemical and genomic studies to gain a mechanistic understanding of the developmental regrowth program. Next, we will perform extensive transcriptomic analyses and comparisons aimed at defining the genetic programs involved in initial axon growth, developmental regrowth, and regeneration following injury. Finally, we will harness the genetic power of Drosophila to perform a comprehensive functional analysis of genes and pathways, those previously known and new ones that we will discover, in various neurite growth paradigms. Importantly, these functional assays will be performed in the same organism, allowing us to use identical genetic mutations across our analyses. To this end, our identification of a new genetic program regulating developmental axon regrowth, together with emerging tools in genomics, places us in a unique position to gain a broad understanding of axon growth during development and following injury.

2 000 000 €

Start date: 2014-03-01, End date: 2019-02-28