ERC FUNDED PROJECTS

The proposed work concerns the theoretical and numerical development of robust and adaptive methodologies for broadband imaging in clutter. The word clutter expresses our uncertainty on the wave speed of the propagation medium. Our results are expected to have a strong impact in a wide range of applications, including underwater acoustics, exploration geophysics and ultrasound non-destructive testing. Our machinery is coherent interferometry (CINT), a state-of-the-art statistically stable imaging methodology, highly suitable for the development of imaging methods in clutter. We aim to extend CINT along two complementary directions: novel types of applications, and further mathematical and numerical development so as to assess and extend its range of applicability. CINT is designed for imaging with partially coherent array data recorded in richly scattering media. It uses statistical smoothing techniques to obtain results that are independent of the clutter realization. Quantifying the amount of smoothing needed is difficult, especially when there is no a priori knowledge about the propagation medium. We intend to address this question by coupling the imaging process with the estimation of the medium's large scale features. Our algorithms rely on the residual coherence in the data. When the coherent signal is too weak, the CINT results are unsatisfactory. We propose two ways for enhancing the resolution of CINT: filter the data prior to imaging (noise reduction) and waveform design (optimize the source distribution). Finally, we propose to extend the applicability of our imaging-in-clutter methodologies by investigating the possibility of utilizing ambient noise sources to perform passive sensor imaging, as well as by studying the imaging problem in random waveguides.

690 000 €

Start date: 2010-06-01, End date: 2015-11-30

The project outlined here addresses the fundamental question how the brain encodes and controls behavior. While we have a reasonable understanding of the role of entire brain areas in such processes, and of mechanisms at the molecular and synaptic levels, there is a big gap in our knowledge of how behavior is controlled at the level of defined neuronal circuits. In natural environments, chances for survival depend on learning about possible aversive and appetitive outcomes and on the appropriate behavioral responses. Most studies addressing the underlying mechanisms at the level of neuronal circuits have focused on aversive learning, such as in Pavlovian fear conditioning. Understanding how activity in defined neuronal circuits mediates appetitive learning, as well as how these circuitries are shared and interact with aversive learning circuits, is a central question in the neuroscience of learning and memory and the focus of this grant application. Using a multidisciplinary approach in mice, combining behavioral, in vivo and in vitro electrophysiological, imaging, optogenetic and state-of-the-art viral circuit tracing techniques, we aim at dissecting the neuronal circuitry of appetitive Pavlovian conditioning with a focus on the amygdala, a key brain region important for both aversive and appetitive learning. Ultimately, elucidating these mechanisms at the level of defined neurons and circuits is fundamental not only for an understanding of memory processes in the brain in general, but also to inform a mechanistic approach to psychiatric conditions associated with amygdala dysfunction and dysregulated emotional responses including anxiety and mood disorders.

2 497 200 €

Start date: 2016-01-01, End date: 2020-12-31

Learning and memory are the basis of our behaviour and mental well-being. Understanding the mechanisms of structural and cellular plasticity in defined neuronal circuits in vivo will be crucial to elucidate principles of circuit-specific memory formation and their relation to changes in neuronal ensemble dynamics. Structural plasticity studies were technically limited to cortex, excluding deep brain areas like the amygdala, and mainly focussed on the input site (dendritic spines), whilst the plasticity of the axon initial segment (AIS), a neuron’s site of output generation, was so far not studied in vivo. Length and location of the AIS are plastic and strongly affects a neurons spike output. However, it remains unknown if AIS plasticity regulates neuronal activity upon learning in vivo. We will combine viral expression of AIS live markers and genetically-encoded Ca2+-sensors with novel deep brain imaging techniques via gradient index (GRIN) lenses to investigate how AIS location and length are regulated upon associative learning in amygdala circuits in vivo. Two-photon time-lapse imaging of the AIS of amygdala neurons upon fear conditioning will help us to track learning-driven AIS location dynamics. Next, we will combine miniature microscope imaging of neuronal activity in freely moving animals with two-photon imaging to link AIS location, length and plasticity to the intrinsic activity as well as learning-related response plasticity of amygdala neurons during fear learning and extinction in vivo. Finally, we will test if AIS plasticity is a general cellular plasticity mechanisms in brain areas afferent to the amygdala, e.g. thalamus. Using a combination of two-photon and miniature microscopy imaging to map structural dynamics of defined neural circuits in the amygdala and its thalamic input areas will provide fundamental insights into the cellular mechanisms underlying sensory processing upon learning and relate network level plasticity with the cellular level.

1 475 475 €

Start date: 2018-12-01, End date: 2023-11-30

My goal is to study several important open mathematical problems in non-equilibrium (NEQ) systems and to build a bridge between these problems and NEQ aspects of soft sciences, in particular biological questions. Traffic on this bridge is going to be two-way, the mathematics carrying a long history as a language of science towards the soft sciences, and the soft sciences fruitfully asking new questions and building new paradigms for mathematical research. Out-of-equilibrium systems pose several fascinating problems: The Fourier law which says that resistance of a wire is proportional to its length is still presenting hard problems for research, and even the existence and the convergence to a NEQ steady state are continuously posing new puzzles, as do questions of smoothness and correlations of such states. These will be addressed with stochastic differential equations, and with particlescatterer systems, both canonical and grand-canonical. The latter are extensions of the well-known Lorentz gas and the study of hyperbolic billiards. Another field where NEQ plays an important role is the study of glassy systems. They were studied with molecular dynamics (MD) but I have used a topological variant, which mimics astonishingly well what happens in MD simulations. The aim is to extend this to 3 dimensions, where new problems appear. Finally, I will apply the NEQ studies to biological systems: How a system copes with the varying environment,adapting in this way to a novel type of NEQ. I will study networks of communication among neurons,which are like random graphs with the additional property of being embedded, and the arrangement of genes on chromosomes in such a way as to optimize the adaptation to the different cell types which must be produced using the same genetic information. I will answer such questions with students and collaborators, who will specialize in the subprojects but will interact with my help across the common bridge.

2 135 385 €

Start date: 2012-04-01, End date: 2017-07-31