ERC FUNDED PROJECTS

Serotonin (5-HT) is a central neuromodulator and a major target of therapeutic psychoactive drugs, but relatively little is known about how it modulates information processing in neural circuits. The theory of predictive coding postulates that the brain combines raw bottom-up sensory information with top-down information from internal models to make perceptual inferences about the world. We hypothesize, based on preliminary data and prior literature, that a role of 5-HT in this process is to report prediction errors and promote the suppression and weakening of erroneous internal models. We propose that it does this by inhibiting top-down relative to bottom-up cortical information flow. To test this hypothesis, we propose a set of experiments in mice performing olfactory perceptual tasks. Our specific aims are: (1) We will test whether 5-HT neurons encode sensory prediction errors. (2) We will test their causal role in using predictive cues to guide perceptual decisions. (3) We will characterize how 5-HT influences the encoding of sensory information by neuronal populations in the olfactory cortex and identify the underlying circuitry. (4) Finally, we will map the effects of 5-HT across the whole brain and use this information to target further causal manipulations to specific 5-HT projections. We accomplish these aims using state-of-the-art optogenetic, electrophysiological and imaging techniques (including 9.4T small-animal functional magnetic resonance imaging) as well as psychophysical tasks amenable to quantitative analysis and computational theory. Together, these experiments will tackle multiple facets of an important general computational question, bringing to bear an array of cutting-edge technologies to address with unprecedented mechanistic detail how 5-HT impacts neural coding and perceptual decision-making.

2 486 074 €

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

When faced with a threat, an animal must decide whether to freeze, reducing its chances of being noticed, or to flee to the safety of a refuge. Animals from fish to primates choose between these two alternatives when confronted by an attacking predator, a choice that largely depends on the context in which the threat occurs. Recent work has made strides identifying the pre-motor circuits, and their inputs, which control freezing behavior in rodents, but how contextual information is integrated to guide this choice is still far from understood. We recently found that fruit flies in response to visual looming stimuli, simulating a large object on collision course, make rapid freeze/flee choices that depend on the social and spatial environment, and the fly’s internal state. Further, identification of looming detector neurons was recently reported and we identified the descending command neurons, DNp09, responsible for freezing in the fly. Knowing the sensory input and descending output for looming-evoked freezing, two environmental factors that modulate its expression, and using a genetically tractable system affording the use of large sample sizes, places us in an unique position to understand how a information about a threat is integrated with cues from the environment to guide the choice of whether to freeze (our goal). To assess how social information impinges on the circuit for freezing, we will examine the sensory inputs and neuromodulators that mediate this process, mapping their connections to DNp09 neurons (Aim 1). We ask whether learning is required for the spatial modulation of freezing, which cues flies are using to discriminate different places and which brain circuits mediate this process (Aim 2). Finally, we will study how activity of DNp09 neurons drives freezing (Aim 3). This project will provide a comprehensive understanding of the mechanism of freezing and its modulation by the environment, from single neurons to behaviour.

1 969 750 €

Start date: 2019-02-01, End date: 2024-01-31

Despite considerable advances in drug discovery, resistance to anticancer chemotherapy confounds the effective treatment of patients. Cancer cells can acquire broad cross-resistance to mechanistically and structurally unrelated drugs. P-glycoprotein (Pgp) actively extrudes many types of drugs from cancer cells, thereby conferring resistance to those agents. The central tenet of my work is that Pgp, a universally accepted biomarker of drug resistance, should in addition be considered as a molecular target of multidrug-resistant (MDR) cancer cells. Successful targeting of MDR cells would reduce the tumor burden and would also enable the elimination of ABC transporter-overexpressing cancer stem cells that are responsible for the replenishment of tumors. The proposed project is based on the following observations: - First, by using a pharmacogenomic approach, I have revealed the hidden vulnerability of MDRcells (Szakács et al. 2004, Cancer Cell 6, 129-37); - Second, I have identified a series of MDR-selective compounds with increased toxicity toPgp-expressing cells (Turk et al.,Cancer Res, 2009. 69(21)); - Third, I have shown that MDR-selective compounds can be used to prevent theemergence of MDR (Ludwig, Szakács et al. 2006, Cancer Res 66, 4808-15); - Fourth, we have generated initial pharmacophore models for cytotoxicity and MDR-selectivity (Hall et al. 2009, J Med Chem 52, 3191-3204). I propose a comprehensive series of studies that will address thefollowing critical questions: - First, what is the scope of MDR-selective compounds? - Second, what is their mechanism of action? - Third, what is the optimal therapeutic modality? Extensive biological, pharmacological and bioinformatic analyses will be utilized to address four major specific aims. These aims address basic questions concerning the physiology of MDR ABC transporters in determining the mechanism of action of MDR-selective compounds, setting the stage for a fresh therapeutic approach that may eventually translate into improved patient care.

1 499 640 €

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

The amazing rate of progress in the computer technologies and telecommunications presents many new challenges for Optimization Theory. New problems are usually very big in size, very special in structure and possibly have a distributed data support. This makes them unsolvable by the standard optimization methods. In these situations, old theoretical models, based on the hidden Black-Box information, cannot work. New theoretical and algorithmic solutions are urgently needed. In this project we will concentrate on development of fast optimization methods for problems of big and very big size. All the new methods will be endowed with provable efficiency guarantees for large classes of optimization problems, arising in practical applications. Our main tool is the acceleration technique developed for the standard Black-Box methods as applied to smooth convex functions. However, we will have to adapt it to deal with different situations. The first line of development will be based on the smoothing technique as applied to a non-smooth functions. We propose to substantially extend this approach to generate approximate solutions in relative scale. The second line of research will be related to applying acceleration techniques to the second-order methods minimizing functions with sparse Hessians. Finally, we aim to develop fast gradient methods for huge-scale problems. The size of these problems is so big that even the usual vector operations are extremely expensive. Thus, we propose to develop new methods with sublinear iteration costs. In our approach, the main source for achieving improvements will be the proper use of problem structure. Our overall aim is to be able to solve in a routine way many important problems, which currently look unsolvable. Moreover, the theoretical development of Convex Optimization will reach the state, when there is no gap between theory and practice: the theoretically most efficient methods will definitely outperform any homebred heuristics.

2 090 038 €

Start date: 2018-09-01, End date: 2023-08-31

The brain evolves, develops, and operates in the context of animal movements. As a consequence, fundamental brain functions such as spatial perception and motor control critically depend on the precise knowledge of the ongoing body motion. An accurate internal estimate of self-movement is thought to emerge from sensorimotor integration; nonetheless, which circuits perform this internal estimation, and exactly how motor-sensory coordination is implemented within these circuits are basic questions that remain to be poorly understood. There is growing evidence suggesting that, during locomotion, motor-related and visual signals interact at early stages of visual processing. In mammals, however, it is not clear what the function of this interaction is. Recently, we have shown that a population of Drosophila optic-flow processing neurons —neurons that are sensitive to self-generated visual flow, receives convergent visual and walking-related signals to form a faithful representation of the fly’s walking movements. Leveraging from these results, and combining quantitative analysis of behavior with physiology, optogenetics, and modelling, we propose to investigate circuit mechanisms of self-movement estimation during walking. We will:1) use cell specific manipulations to identify what cells are necessary to generate the motor-related activity in the population of visual neurons, 2) record from the identified neurons and correlate their activity with specific locomotor parameters, and 3) perturb the activity of different cell-types within the identified circuits to test their role in the dynamics of the visual neurons, and on the fly’s walking behavior. These experiments will establish unprecedented causal relationships among neural activity, the formation of an internal representation, and locomotor control. The identified sensorimotor principles will establish a framework that can be tested in other scenarios or animal systems with implications both in health and disease.

1 500 000 €

Start date: 2017-11-01, End date: 2022-10-31

Cytokinesis completes cell division by partitioning the contents of the mother cell to the two daughter cells. This process is accomplished through the assembly and constriction of a contractile ring, a complex actomyosin network that remains poorly understood on the molecular level. Research in cytokinesis has overwhelmingly focused on signaling mechanisms that dictate when and where the contractile ring is assembled. By contrast, the research I propose here addresses fundamental questions about the structural and functional properties of the contractile ring itself. We will use the nematode C. elegans to exploit the power of quantitative live imaging assays in an experimentally tractable metazoan organism. The early C. elegans embryo is uniquely suited to the study of the contractile ring, as cells dividing perpendicularly to the imaging plane provide a full end-on view of the contractile ring throughout constriction. This greatly facilitates accurate measurements of constriction kinetics, ring width and thickness, and levels as well as dynamics of fluorescently-tagged contractile ring components. Combining image-based assays with powerful molecular replacement technology for structure-function studies, we will 1) determine the contribution of branched and non-branched actin filament populations to contractile ring formation; 2) explore its ultra-structural organization in collaboration with a world expert in electron microcopy; 3) investigate how the contractile ring network is dynamically remodeled during constriction with the help of a novel laser microsurgery assay that has uncovered a remarkably robust ring repair mechanism; and 4) use a targeted RNAi screen and phenotype profiling to identify new components of actomyosin contractile networks. The results from this interdisciplinary project will significantly enhance our mechanistic understanding of cytokinesis and other cellular processes that involve actomyosin-based contractility.

1 499 989 €

Start date: 2015-07-01, End date: 2020-06-30

Adaptive optics, the technology to dynamically program the phase of optical waves has sparked an avalanche of scientific discoveries and innovations in light optics applications. Nowadays, the phase of optical waves can be dynamically programmed providing research on exotic optical beams and unprecedented control over the performance of optical instruments. Although electron waves carry many similarities in comparison to their optical counterparts, a generic programmable phase plate for electrons is still missing. This project aims at developing a prototype of a programmable electrostatic phase plate that allows the user to freely change the phase of electron waves and demonstrate it to potential licensees for further upscaling and introduction to the market. The target of this POC project is the realization of a tunable easy-to-use 5x5-pixel prototype that will demonstrate the potential of adaptive optics in electron microscopy. Its realization will be based on lithographic technology to allow for future upscaling. It is expected that such a phase plate can dramatically increase the information obtained at a given electron dose, limiting the detrimental effects of beam damage that currently hinders the use of electron microscopy in e.g. life sciences. As such, it has the potential to disrupt the electron microscopy market with novel applications while at the same time reducing cost and complexity and increasing the potential for fully automated instruments.

148 500 €

Start date: 2018-03-01, End date: 2019-08-31

Space exploration is one of boldest and most exciting endeavors that humanity has undertaken, and it holds enormous promise for the future. Our next challenges for the spatial conquest include bringing back samples to Earth by means of robotic missions and continuing the manned exploration program, which aims at sending human beings to Mars and bring them home safely. Inaccurate prediction of the heat-flux to the surface of the spacecraft heat shield can be fatal for the crew or the success of a robotic mission. This quantity is estimated during the design phase. An accurate prediction is a particularly complex task, regarding modelling of the following phenomena that are potential “mission killers:” 1) Radiation of the plasma in the shock layer, 2) Complex surface chemistry on the thermal protection material, 3) Flow transition from laminar to turbulent. Our poor understanding of the coupled mechanisms of radiation, ablation, and transition leads to the difficulties in flux prediction. To avoid failure and ensure safety of the astronauts and payload, engineers resort to “safety factors” to determine the thickness of the heat shield, at the expense of the mass of embarked payload. Thinking out of the box and basic research are thus necessary for advancements of the models that will better define the environment and requirements for the design and safe operation of tomorrow’s space vehicles and planetary probes for the manned space exploration. The three basic ingredients for predictive science are: 1) Physico-chemical models, 2) Computational methods, 3) Experimental data. We propose to follow a complementary approach for prediction. The proposed research aims at: “Integrating new advanced physico-chemical models and computational methods, based on a multidisciplinary approach developed together with physicists, chemists, and applied mathematicians, to create a top-notch multiphysics and multiscale numerical platform for simulations of planetary atmosphere entries, crucial to the new challenges of the manned space exploration program. Experimental data will also be used for validation, following state-of-the-art uncertainty quantification methods.”

1 494 892 €

Start date: 2010-09-01, End date: 2015-08-31

This proposal wishes to fundamentally improve our understanding of the role of tropical freshwater ecosystems in carbon (C) cycling on the catchment scale. It uses an unprecedented combination of state-of-the-art proxies such as stable isotope, 14C and biomarker signatures to characterize organic matter, radiogenic isotope signatures to determine particle residence times, as well as field measurements of relevant biogeochemical processes. We focus on tropical systems since there is a striking lack of data on such systems, even though riverine C transport is thought to be disproportionately high in tropical areas. Furthermore, the presence of landscape-scale contrasts in vegetation (in particular, C3 vs. C4 plants) are an important asset in the use of stable isotopes as natural tracers of C cycling processes on this scale. Freshwater ecosystems are an important component in the global C cycle, and the primary link between terrestrial and marine ecosystems. Recent estimates indicate that ~2 Pg C y-1 (Pg=Petagram) enter freshwater systems, i.e., about twice the estimated global terrestrial C sink. More than half of this is thought to be remineralized before it reaches the coastal zone, and for the Amazon basin this has even been suggested to be ~90% of the lateral C inputs. The question how general these patterns are is a matter of debate, and assessing the mechanisms determining the degree of processing versus transport of organic carbon in lakes and river systems is critical to further constrain their role in the global C cycle. This proposal provides an interdisciplinary approach to describe and quantify catchment-scale C transport and cycling in tropical river basins. Besides conceptual and methodological advances, and a significant expansion of our dataset on C processes in such systems, new data gathered in this project are likely to provide exciting and novel hypotheses on the functioning of freshwater systems and their linkage to the terrestrial C budget.

1 745 262 €

Start date: 2009-10-01, End date: 2014-09-30