ERC FUNDED PROJECTS

The scientific goal of the proposal is to answer central questions related to diffeomorphism groups of manifolds of dimension 2 and 3, and to their deformation invariant analogs, the mapping class groups. While the classification of surfaces has been known for more than a century, their automorphism groups have yet to be fully understood. Even less is known about diffeomorphisms of 3-manifolds despite much interest, and the objects here have only been classified recently, by the breakthrough work of Perelman on the Poincar\'e and geometrization conjectures. In dimension 2, I will focus on the relationship between mapping class groups and topological conformal field theories, with applications to Hochschild homology. In dimension 3, I propose to compute the stable homology of classifying spaces of diffeomorphism groups and mapping class groups, as well as study the homotopy type of the space of diffeomorphisms. I propose moreover to establish homological stability theorems in the wider context of automorphism groups and more general families of groups. The project combines breakthrough methods from homotopy theory with methods from differential and geometric topology. The research team will consist of 3 PhD students, and 4 postdocs, which I will lead.

724 992 €

Start date: 2009-11-01, End date: 2014-10-31

This project presents a new concept for the detection, diagnosis and monitoring of cancer biomarker patterns in point-of-care. The device under development will make use of the selectivity of the plastic antibodies as sensing materials and the interference they will play on the normal operation of a photovoltaic cell. Plastic antibodies will be designed by surface imprinting procedures. Self-assembled monolayer and molecular imprinting techniques will be merged in this process because they allow the self-assembly of nanostructured materials on a “bottom-up” nanofabrication approach. A dye-sensitized solar cell will be used as photovoltaic cell. It includes a liquid interface in the cell circuit, which allows the introduction of the sample (also in liquid phase) without disturbing the normal cell operation. Furthermore, it works well with rather low cost materials and requires mild and easy processing conditions. The cell will be equipped with plasmonic structures to enhance light absorption and cell efficiency. The device under development will be easily operated by any clinician or patient. It will require ambient light and a regular multimeter. Eye detection will be also tried out.

998 584 €

Start date: 2013-02-01, End date: 2018-01-31

I intend to investigate what cognitive mechanisms give us combinatorial speech. Combinatorial speech is the ability to make new words using pre-existing speech sounds. Humans are the only apes that can do this, yet we do not know how our brains do it, nor how exactly we differ from other apes. Using new experimental techniques to study human behavior and new computational techniques to model human cognition, I will find out how we deal with combinatorial speech. The experimental part will study individual and cultural learning. Experimental cultural learning is a new technique that simulates cultural evolution in the laboratory. Two types of cultural learning will be used: iterated learning, which simulates language transfer across generations, and social coordination, which simulates emergence of norms in a language community. Using the two types of cultural learning together with individual learning experiments will help to zero in, from three angles, on how humans deal with combinatorial speech. In addition it will make a methodological contribution by comparing the strengths and weaknesses of the three methods. The computer modeling part will formalize hypotheses about how our brains deal with combinatorial speech. Two models will be built: a high-level model that will establish the basic algorithms with which combinatorial speech is learned and reproduced, and a neural model that will establish in more detail how the algorithms are implemented in the brain. In addition, the models, through increasing understanding of how humans deal with speech, will help bridge the performance gap between human and computer speech recognition. The project will advance science in four ways: it will provide insight into how our unique ability for using combinatorial speech works, it will tell us how this is implemented in the brain, it will extend the novel methodology of experimental cultural learning and it will create new computer models for dealing with human speech.

1 276 620 €

Start date: 2012-02-01, End date: 2017-01-31

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