ERC FUNDED PROJECTS

We propose to develop truly two-dimensional continuous materials and two-dimensional monolayer films composed of individual nanocrystals by the comparatively fast, inexpensive, and scalable colloidal synthesis method. The materials’ properties will be studied in detail, especially regarding their (photo-) electrical transport. This will allow developing new types of device structures, such as Coulomb blockade and field enhancement based transistors. Recently, we demonstrated the possibility to synthesize in a controlled manner truly two-dimensional colloidal nanostructures. We will investigate their formation mechanism, synthesize further materials as “nanosheets”, develop methodologies to tune their geometrical properties, and study their (photo-) electrical properties. Furthermore, we will use the Langmuir-Blodgett method to deposit highly ordered monolayers of monodisperse nanoparticles. Such structures show interesting transport properties governed by Coulomb blockade effects known from individual nanoparticles. This leads to semiconductor-like behavior in metal nanoparticle films. The understanding of the electric transport in such “multi-tunnel devices” is still very limited. Thus, we will investigate this concept in detail and take it to its limits. Beside improvement of quality and exchange of material we will tune the nanoparticles’ size and shape in order to gain a deeper understanding of the electrical properties of supercrystallographic assemblies. Furthermore, we will develop device concepts for diode and transistor structures which take into account the novel properties of the low-dimensional assemblies. Nanosheets and monolayers of nanoparticles truly follow the principle of building devices by the bottom-up approach and allow electric transport measurements in a 2D regime. Highly ordered nanomaterial systems possess easy and reliably to manipulate electronic properties what make them interesting for future (inexpensive) electronic devices.

1 497 200 €

Start date: 2013-02-01, End date: 2019-01-31

Parkinson’s disease (PD) is the second most common neurodegenerative disorder primarily caused by the progressive loss of dopaminergic (DA) neurons in the substantia nigra (SN). Despite the advances in gene discovery associated with PD, the knowledge of the PD pathogenesis is largely limited to the involvement of these genes in the generic cell death pathways, and why degeneration is specific to DA neurons and why the degeneration is progressive remain enigmatic. Broad goal of our work is therefore to elucidate the mechanisms underlying specific and progressive DA neuron degeneration in PD. Our new Drosophila model of PD ⎯Fer2 gene loss-of-function mutation⎯ is unusually well suited to address these questions. Fer2 mutants exhibit specific and progressive death of brain DA neurons as well as severe locomotor defects and short life span. Strikingly, the death of DA neuron is initiated in a small cluster of Fer2-expressing DA neurons and subsequently propagates to Fer2-negative DA neurons. We therefore propose a novel two-step model of the neurodegeneration in PD: primary cell death occurs in a specific subset of dopamindegic neurons that are genetically defined, and subsequently the failure of the neuronal connectivity triggers and propagates secondary cell death to remaining DA neurons. In this research, we will test this hypothesis and investigate the underlying molecular mechanisms. This will be the first study to examine circuit-dependency in DA neuron degeneration. Our approach will use a combination of non-biased genomic techniques and candidate-based screening, in addition to the powerful Drosophila genetic toolbox. Furthermore, to test this hypothesis beyond the Drosophila model, we will establish new mouse models of PD that exhibit progressive DA neuron degeneration. Outcome of this research will likely revolutionize the understanding of PD pathogenesis and open an avenue toward the discovery of effective therapy strategies against PD.

1 518 960 €

Start date: 2013-06-01, End date: 2018-05-31

It was early predicted by M. Green and coeval colleagues that dividing the solar spectrum into narrow ranges of colours is the most efficient manner to convert solar energy into electrical power. Multijunction solar cells are the current solution to this challenge, which have reached over 30% conversion efficiencies by stacking 3 junctions together. However, the large fabrication costs and time hinders their use in everyday life. It has been shown that highly mismatched alloy (HMA) materials provide a powerful playground to achieve at least 3 different colour absorption regions that enable optimised energy conversion with just one junction. Combining HMA-based junctions with standard Silicon solar cells will rocket solar conversion efficiency at a reduced price. To turn this ambition into marketable devices, several efforts are still needed and few challenges must be overcome. 4SUNS is a revolutionary approach for the development of HMA materials on Silicon technology, which will bring highly efficient multi-colour solar cells costs below current multijunction devices. The project will develop the technology of HMA materials on Silicon via material synthesis opening a new technology for the future. The understanding and optimization of highly mismatched alloy materials-using GaAsNP alloy- will provide building blocks for the fabrication of laboratory-size 4-colours/2-junctions solar cells. Using a molecular beam epitaxy system, 4SUNS will grow 4-colours/2-junctions structure as well as it will manufacture the final devices. Structural and optoelectronic characterizations will carry out to determine the quality of the materials and the solar cells characteristic to obtain a competitive product. These new solar cells are competitive products to breakthrough on the solar energy sector solar cells and allowing Europe to take leadership on high efficiency solar cells.

1 499 719 €

Start date: 2018-02-01, End date: 2023-01-31

Crucial processes within cells depend on specific non-covalent interactions which mediate the assembly of proteins and other biomolecules. Deriving structural information to understand the function of these complex systems is the primary goal of Structural Biology. In this application, the recently developed LILBID method (Laser Induced Liquid Bead Ion Desorption) will be optimized for investigation of macromolecular complexes with a mass accuracy two orders of magnitude better than in 1st generation spectrometers. Controlled disassembly of the multiprotein complexes in the mass spectrometric analysis while keeping the 3D structure intact, will allow for the determination of complex stoichiometry and connectivity of the constituting proteins. Methods for such controlled disassembly will be developed in two separate units of the proposed LILBID spectrometer, in a collision chamber and in a laser dissociation chamber, enabling gas phase dissociation of protein complexes and removal of excess water/buffer molecules. As a third unit, a chamber allowing determination of ion mobility (IM) will be integrated to determine collisional cross sections (CCS). From CCS, unique information regarding the spatial arrangement of proteins in complexes or subcomplexes will then be obtainable from LILBID. The proposed design of the new spectrometer will offer fundamentally new possibilities for the investigation of non-covalent RNA, soluble and membrane protein complexes, as well as broadening the applicability of non-covalent MS towards supercomplexes.

1 264 477 €

Start date: 2014-02-01, End date: 2019-01-31

The Tera-Hertz portion of the spectrum presents unique potentials for advanced applications. Currently the THz spectrum is revealing the mechanisms at the origin of our universe and provides the means to monitor the health of our planet via satellite based sensing of critical gases. Potentially time domain sensing of the THz spectrum will be the ideal tool for a vast variety of medical and security applications. Presently, systems in the THz regime are extremely expensive and consequently the THz spectrum is still the domain of only niche (expensive) scientific applications. The main problems are the lack of power and sensitivity. The wide unused THz spectral bandwidth is, herself, the only widely available resource that in the future can compensate for these problems. But, so far, when scientists try to really use the bandwidth, they run into an insurmountable physical limit: antenna dispersion. Antenna dispersion modifies the signal’s spectrum in a wavelength dependent manner in all types of radiation, but is particularly deleterious to THz signals because the spectrum is too wide and with foreseeable technology it cannot be digitized. The goal of this proposal is to introduce break-through antenna technology that will eliminate the dispersion bottle neck and revolutionize Time Domain sensing and Spectroscopic Space Science. Achieving these goals the project will pole vault THz imaging technology into the 21-th century and develop critically important enabling technologies which will satisfy the electrical engineering needs of the next 30 years and in the long run will enable multi Tera-bit wireless communications. In order to achieve these goals, I will first build upon two major breakthrough radiation mechanisms that I pioneered: Leaky Lenses and Connected Arrays. Eventually, ultra wide band imaging arrays constituted by thousands of components will be designed on the bases of the new theoretical findings and demonstrated.

1 499 487 €

Start date: 2011-11-01, End date: 2017-10-31

The emergence of life is one of the most fascinating and yet largely unsolved questions in the natural sciences, and thus a significant challenge for scientists from many disciplines. There is growing evidence that ribonucleic acid (RNA) polymers, which are capable of genetic information storage and self-catalysis, were involved in the early forms of life. But despite recent progress, RNA synthesis without biological machineries is very challenging. The current project aims at understanding how to synthesize RNA in abiotic conditions. I will solve problems associated with three critical aspects of RNA formation that I will rationalize at a molecular level: (i) accumulation of precursors, (ii) formation of a chemical bond between RNA monomers, and (iii) tolerance for alternative backbone sugars or linkages. Because I will study problems ranging from the formation of chemical bonds up to the stability of large biopolymers, I propose an original computational multi-scale approach combining techniques that range from quantum calculations to large-scale all-atom simulations, employed together with efficient enhanced-sampling algorithms, forcefield improvement, cutting-edge analysis methods and model development. My objectives are the following: 1 • To explain why the poorly-understood thermally-driven process of thermophoresis can contribute to the accumulation of dilute precursors. 2 • To understand why linking RNA monomers with phosphoester bonds is so difficult, to understand the molecular mechanism of possible catalysts and to suggest key improvements. 3 • To rationalize the molecular basis for RNA tolerance for alternative backbone sugars or linkages that have probably been incorporated in abiotic conditions. This unique in-silico laboratory setup should significantly impact our comprehension of life’s origin by overcoming major obstacles to RNA abiotic formation, and in addition will reveal significant orthogonal outcomes for (bio)technological applications.

1 497 031 €

Start date: 2018-02-01, End date: 2023-01-31

"How are actions initiated by the human brain when there is no external sensory cue or other immediate imperative? How do subtle ongoing interactions within the brain and between the brain, body, and sensory context influence the spontaneous initiation of action? How should we approach the problem of trying to identify the neural events that cause spontaneous voluntary action? Much is understood about how the brain decides between competing alternatives, leading to different behavioral responses. But far less is known about how the brain decides "when" to perform an action, or "whether" to perform an action in the first place, especially in a context where there is no sensory cue to act such as during foraging. This project seeks to open a new chapter in the study of spontaneous voluntary action building on a novel hypothesis recently introduced by the applicant (Schurger et al, PNAS 2012) concerning the role of ongoing neural activity in action initiation. We introduce brain-behavior forecasting, the converse of movement-locked averaging, as an approach to identifying the neurodynamic states that commit the motor system to performing an action "now", and will apply it in the context of information foraging. Spontaneous action remains a profound mystery in the brain basis of behavior, in humans and other animals, and is also central to the problem of asynchronous intention-detection in brain-computer interfaces (BCIs). A BCI must not only interpret what the user intends, but also must detect "when" the user intends to act, and not respond otherwise. This remains the biggest challenge in the development of high-performance BCIs, whether invasive or non-invasive. This project will take a systematic and collaborative approach to the study of spontaneous self-initiated action, incorporating computational modeling, neuroimaging, and machine learning techniques towards a deeper understanding of voluntary behavior and the robust asynchronous detection of decisions-to-act."

1 338 130 €

Start date: 2015-10-01, End date: 2020-09-30

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

Our affective and motivational state is important for our decisions, actions and quality of life. Many pathological conditions affect this state. For example, addictive drugs are hyperactivating the reward system and trigger a strong motivation for continued drug intake, whereas many somatic and psychiatric diseases lead to an aversive state, characterized by loss of motivation. I will study specific neural circuits and mechanisms underlying reward and aversion, and how pathological signaling in these systems can trigger relapse in drug addiction. Given the important role of the dopaminergic neurons in the midbrain for many aspects of reward signaling, I will study how synaptic plasticity in these cells, and in their target neurons in the striatum, contribute to relapse in drug seeking. I will also study the circuits underlying aversion. Little is known about these circuits, but my hypothesis is that an important component of aversion is signaled by a specific neuronal population in the brainstem parabrachial nucleus, projecting to the central amygdala. We will test this hypothesis and also determine how this aversion circuit contributes to the persistence of addiction and to relapse. To dissect this complicated system, I am developing new genetic methods for manipulating and visualizing specific functional circuits in the mouse brain. My unique combination of state-of-the-art competence in transgenics and cutting edge knowledge in the anatomy and functional organization of the circuits behind reward and aversion should allow me to decode these systems, linking discrete circuits to behavior. Collectively, the results will indicate how signals encoding aversion and reward are integrated to control addictive behavior and they may identify novel avenues for treatment of drug addiction as well as aversion-related symptoms affecting patients with chronic inflammatory conditions and cancer.

1 500 000 €

Start date: 2010-10-01, End date: 2015-09-30

Within a 12 month period, 20% of adults will meet criteria for one or more clinical anxiety disorders (ADs). These disorders are hugely disruptive, placing an emotional burden on individuals and their families. While both cognitive behavioural therapy and pharmacological treatment are widely viewed as effective strategies for managing ADs, systematic review of the literature reveals that only 30–45% of patients demonstrate a marked response to treatment (anxiety levels being reduced into the nonaffected range). In addition, a significant proportion of initial responders relapse after treatment is discontinued. There is hence a real and marked need to improve upon current approaches to AD treatment. One possible avenue for improving response rates is through optimizing initial treatment selection. Specifically, it is possible that certain individuals might respond better to cognitive interventions while others might respond better to pharmacological treatment. Recently it has been suggested that there may be two or more distinct biological pathways disrupted in anxiety. If this is the case, then specification of these pathways may be an important step in predicting which individuals are likely to respond to which treatment. Few studies have focused upon this issue and, in particular, upon identifying neural markers that might predict response to cognitive (as opposed to pharmacological) intervention. The proposed research aims to address this. Specifically, it tests the hypothesis that there are at least two mechanisms disrupted in ADs, one entailing amygdala hyper-responsivity to cues that signal threat, the other impoverished recruitment of frontal regions that support cognitive and emotional regulation. Two series of functional magnetic resonance imaging experiments will be conducted. These will investigate differences in amygdala and frontal function during (a) attentional processing and (b) fear conditioning. Initial clinical experiments will investigate whether Generalised Anxiety Disorder and Specific Phobia involve differing degrees of disruption to frontal versus amygdala function during these tasks. This work will feed into training studies, the goal being to characterize AD patient subgroups that benefit from cognitive training.

1 708 407 €

Start date: 2011-04-01, End date: 2016-08-31

Linear Parameter-Varying (LPV) systems are flexible mathematical models capable of representing Nonlinear (NL)/Time-Varying (TV) dynamical behaviors of complex physical systems (e.g., wafer scanners, car engines, chemical reactors), often encountered in engineering, via a linear structure. The LPV framework provides computationally efficient and robust approaches to synthesize digital controllers that can ensure desired operation of such systems - making it attractive to (i) high-tech mechatronic, (ii) automotive and (iii) chemical-process applications. Such a framework is important to meet with the increasing operational demands of systems in these industrial sectors and to realize future technological targets. However, recent studies have shown that, to fully exploit the potential of the LPV framework, a number of limiting factors of the underlying theory ask a for serious innovation, as currently it is not understood how to (1) automate exact and low-complexity LPV modeling of real-world applications and how to refine uncertain aspects of these models efficiently by the help of measured data, (2) incorporate control objectives directly into modeling and to develop model reduction approaches for control, and (3) how to see modeling & control synthesis as a unified, closed-loop system synthesis approach directly oriented for the underlying NL/TV system. Furthermore, due to the increasingly cyber-physical nature of applications, (4) control synthesis is needed in a plug & play fashion, where if sub-systems are modified or exchanged, then the control design and the model of the whole system are only incrementally updated. This project aims to surmount Challenges (1)-(4) by establishing an innovative revolution of the LPV framework supported by a software suite and extensive empirical studies on real-world industrial applications; with a potential to ensure a leading role of technological innovation of the EU in the high-impact industrial sectors (i)-(iii).

1 493 561 €

Start date: 2017-09-01, End date: 2022-08-31

Novel sophisticated technologies that exploit the laws of quantum physics form a cornerstone for the future well-being, economic growth and security of Europe. Here photonic devices have gained a prominent position because the absorption, emission, propagation or storage of a photon is a process that can be harnessed at a fundamental level and render more practical ways to use light for such applications. However, the interaction of light with single quantum systems under ambient conditions is typically very weak and difficult to control. Furthermore, there are quantum phenomena occurring in matter at nanometer length scales that are currently not well understood. These deficiencies have a direct and severe impact on creating a bridge between quantum physics and photonic device technologies. aQUARiUM, precisely address the issue of controlling and enhancing the interaction between few photons and rolled-up nanostructures with ability to be deployed in practical applications. With aQUARiUM, we will take epsilon (permittivity)-near-zero (ENZ) metamaterials into quantum nanophotonics. To this end, we will integrate quantum emitters with rolled-up waveguides, that act as ENZ metamaterial, to expand and redefine the range of light-matter interactions. We will explore the electromagnetic design freedom enabled by the extended modes of ENZ medium, which “stretches” the effective wavelength inside the structure. Specifically, aQUARiUM is built around the following two objectives: (i) Enhancing light-matter interactions with single emitters (Enhance) independent of emitter position. (ii) Enabling collective excitations in dense emitter ensembles (Collect) coherently connect emitters on nanophotonic devices to obtain coherent emission. aQUARiUM aims to create novel light-sources and long-term entanglement generation and beyond. The envisioned outcome of aQUARiUM is a wholly new photonic platform applicable across a diverse range of areas.

1 499 431 €

Start date: 2019-01-01, End date: 2023-12-31

Despite considerable efforts aimed at prevention and treatment, the prevalence of obesity and type 2 diabetes has increased at an alarming rate worldwide over recent decades. Given the urgent need to develop safe and efficient anti-obesity drugs, the scientific community has to intensify efforts to better understand the mechanisms involved in the pathogenesis of obesity. Based on human genome-wide association studies and targeted mouse mutagenesis models, it has recently emerged that the brain controls most aspects of systemic metabolism and that obesity may be a brain disease. I have recently shown that like neurons, astrocytes also respond to circulating nutrients, and they cooperate with neurons to efficiently regulate energy metabolism. So far, the study of brain circuits controlling energy balance has focused on neurons, ignoring the presence and role of astrocytes. Importantly, our studies were the first to describe that exposure to a high-fat, highsugar (HFHS) diet triggers hypothalamic astrogliosis prior to significant body weight gain, indicating a potentially important role in promoting obesity. Overall, my recent findings suggest a novel model in which astrocytes are actively involved in the central nervous system (CNS) control of metabolism, likely including active crosstalk between astrocytes and neurons. To test this hypothetical model, I propose to develop a functional understanding of astroglia-neuronal communication in the CNS control of metabolism focusing on: 1) dissecting the ability of astrocytes to release gliotransmitters to neurons, 2) assessing how astrocytes respond to neuronal activity, and 3) determining if HFHS-induced astrogliosis interrupts this crosstalk and contributes to the development of obesity and type 2 diabetes. These studies aim to uncover the molecular underpinnings of astrocyte-neuron inputs regulating metabolism in health and disease so as to inspire and enable novel therapeutic strategies to fight diabetes and obesity.

1 499 938 €

Start date: 2018-01-01, End date: 2022-12-31

The goal of ATOMICAR is to achieve the ultimate sensitivity limit in heterogeneous catalysis: Quantitative measurement of chemical turnover on a single catalytic nanoparticle. Most heterogeneous catalysis occurs on metal nanoparticle in the size range of 3 nm - 10 nm. Model studies have established that there is often a strong coupling between nanoparticle size & shape - and catalytic activity. The strong structure-activity coupling renders it probable that “super-active” nanoparticles exist. However, since there is no way to measure catalytic activity of less than ca 1 million nanoparticles at a time, any super-activity will always be hidden by “ensemble smearing” since one million nanoparticles of exactly identical size and shape cannot be made. The state-of-the-art in catalysis benchmarking is microfabricated flow reactors with mass-spectrometric detection, but the sensitivity of this approach cannot be incrementally improved by six orders of magnitude. This calls for a new measurement paradigm where the activity of a single nanoparticle can be benchmarked – the ultimate limit for catalytic measurement. A tiny batch reactor is the solution, but there are three key problems: How to seal it; how to track catalytic turnover inside it; and how to see the nanoparticle inside it? Graphene solves all three problems: A microfabricated cavity with a thin SixNy bottom window, a single catalytic nanoparticle inside, and a graphene seal forms a gas tight batch reactor since graphene has zero gas permeability. Catalysis is then tracked as an internal pressure change via the stress & deflection of the graphene seal. Crucially, the electron-transparency of graphene and SixNy enables subsequent transmission electron microscope access with atomic resolution so that active nanoparticles can be studied in full detail. ATOMICAR will re-define the experimental limits of catalyst benchmarking and lift the field of basic catalysis research into the single-nanoparticle age.

1 496 000 €

Start date: 2018-02-01, End date: 2023-01-31

"The goal of the present proposal is to realize measurements of electronic dynamics in polyatomic molecules with attosecond temporal resolution (1 as = 10^-18s). We propose to study electronic rearrangements following photoexcitation, charge migration in a molecular chain induced by ionization and non-adiabatic multi-electron dynamics in an intense laser field. The grand question addressed by this research is the characterization of electron correlations which control the shape, properties and function of molecules. In all three proposed projects, a time-domain approach appears to be the most suitable since it reduces complex molecular dynamics to the purely electronic dynamics by exploiting the hierarchy of motional time scales. Experimentally, we propose to realize an innovative experimental setup. A few-cycle infrared (IR) pulse will be used to generate attosecond pulses in the extreme-ultraviolet (XUV) by high-harmonic generation. The IR pulse will be separated from the XUV by means of an innovative interferometer. Additionally, it will permit the introduction of a controlled attosecond delay between the two pulses. We propose to use the attosecond pulses as a tool to look inside individual IR- or UV-field cycles to better understand light-matter interactions. Time-resolved pump-probe experiments will be carried out on polyatomic molecules by detecting the energy and angular distribution of photoelectrons in a velocity-map imaging spectrometer. These experiments are expected to provide new insights into the dynamics of multi-electron systems along with new results for the validation and improvement of theoretical models. Multi-electron dynamics is indeed a very complex subject on its own and even more so in the presence of strong laser fields. The proposed experiments directly address theses challenges and are expected to provide new insights that will be beneficial to a wide range of scientific research areas."

1 999 992 €

Start date: 2012-09-01, End date: 2017-08-31

Long-term studies of free-living vertebrate populations have proved a rich resource for understanding evolutionary and ecological processes, because individuals’ life histories can be measured by tracking them from birth/hatching through to death. In recent years the ‘animal model’ has been applied to pedigreed long-term study populations with great success, dramatically advancing our understanding of quantitative genetic parameters such as heritabilities, genetic correlations and plasticities of traits that are relevant to microevolutionary responses to environmental change. Unfortunately, quantitative genetic approaches have one major drawback – they cannot identify the actual genes responsible for genetic variation. Therefore, it is impossible to link evolutionary responses to a changing environment to molecular genetic variation, making our picture of the process incomplete. Many of the best long-term studies have been conducted in passerine birds. Unfortunately genomics resources are only available for two model avian species, and are absent for bird species that are studied in the wild. I will fill this gap by exploiting recent advances in genomics technology to sequence the entire transcriptome of the longest running study of wild birds – the great tit population in Wytham Woods, Oxford. Having identified most of the sequence variation in the great tit transcriptome, I will then genotype all birds for whom phenotype records and blood samples are available This will be, by far, the largest phenotype-genotype dataset of any free-living vertebrate population. I will then use gene mapping techniques to identify genes and genomic regions responsible for variation in a number of key traits such as lifetime recruitment, clutch size and breeding/laying date. This will result in a greater understanding, at the molecular level, how microevolutionary change can arise (or be constrained).

1 560 770 €

Start date: 2008-10-01, End date: 2014-06-30

The objective of the BEACON project is to (re-)introduce analog communications into the design of modern wireless networks. We argue that the extreme energy and latency constraints imposed by the emerging Internet of Everything (IoE) paradigm can only be met within a hybrid digital-analog communications framework. Current network architectures separate source and channel coding, orthogonalize users, and employ long block-length digital source and channel codes, which are either suboptimal or not applicable under the aforementioned constraints. BEACON questions these well-established design principles, and proposes to replace them with a hybrid digital-analog communications framework, which will meet the required energy and latency constraints while simplifying the encoding and decoding processes. BEACON pushes the performance of the IoE to its theoretical limits by i) exploiting signal correlations that are abundant in IoE applications, given the foreseen density of deployed sensing devices, ii) taking into account the limited and stochastic nature of energy availability due to, for example, energy harvesting capabilities, iii) using feedback resources to improve the end-to-end signal distortion, and iv) deriving novel converse results to identify fundamental performance benchmarks. The results of BEACON will not only shed light on the fundamental limits on the performance any coding scheme can achieve, but will also lead to the development of unconventional codes and communication protocols that can approach these limits, combining digital and analog communication techniques. The ultimate challenge for this project is to exploit the developed hybrid digital-analog networking theory for a complete overhaul of the physical layer design for emerging IoE applications, such as smart grids, tele-robotics and smart homes. For this purpose, a proof-of-concept implementation test-bed will also be built using software defined radios and sensor nodes.

1 496 350 €

Start date: 2016-10-01, End date: 2021-09-30

BetterSense aims to solve the two main problems in current gas sensor technologies: the high power consumption and the poor selectivity. For the former, we propose a radically new approach: to integrate the sensing components and the energy sources intimately, at the nanoscale, in order to achieve a new kind of sensor concept featuring zero power consumption. For the latter, we will mimic the biological receptors designing a kit of gas-specific molecular organic functionalizations to reach ultra-high gas selectivity figures, comparable to those of biological processes. Both cutting-edge concepts will be developed in parallel an integrated together to render a totally new gas sensing technology that surpasses the state-of-the-art. As a matter of fact, the project will enable, for the first time, the integration of gas detectors in energetically autonomous sensors networks. Additionally, BetterSense will provide an integral solution to the gas sensing challenge by producing a full set of gas-specific sensors over the same platform to ease their integration in multi-analyte systems. Moreover, the project approach will certainly open opportunities in adjacent fields in which power consumption, specificity and nano/micro integration are a concern, such as liquid chemical and biological sensing. In spite of the promising evidences that demonstrate the feasibility of this proposal, there are still many scientific and technological issues to solve, most of them in the edge of what is known and what is possible today in nano-fabrication and nano/micro integration. For this reason, BetterSense also aims to contribute to the global challenge of making nanodevices compatible with scalable, cost-effective, microelectronic technologies. For all this, addressing this challenging proposal in full requires a funding scheme compatible with a high-risk/high-gain vision to finance the full dedication of a highly motivated research team with multidisciplinary skill

1 498 452 €

Start date: 2014-02-01, End date: 2019-01-31

The use of renewable feedstocks by the chemical industry is fundamental due to both the depletion of fossil resources and the increasing pressure of environmental concerns. Biomass can act as a sustainable source of organic industrial chemicals; however, the establishment of a renewable chemical industry that is economically competitive with the present oil-based one requires the development of new processes to convert biomass-derived compounds into useful industrial materials following the principles of green chemistry. To achieve these goals, developments in several fields including heterogeneous catalysis are needed. One of the ways to accelerate the discovery of new potentially active, selective and stable catalysts is the massive use of computational chemistry. Recent advances have demonstrated that Density Functional Theory coupled to ab initio thermodynamics, transition state theory and microkinetic analysis can provide a full view of the catalytic phenomena. The aim of the present project is thus to employ these well-tested computational techniques to the development of a theoretical framework that can accelerate the identification of new catalysts for the conversion of biomass derived target compounds into useful chemicals. Since compared to petroleum-based materials-biomass derived ones are multifuncionalized, the search for new catalytic materials and processes has a strong requirement in the selectivity of the chemical transformations. The main challenges in the project are related to the high functionalization of the molecules, their liquid nature and the large number of potentially competitive reaction paths. The requirements of specificity and selectivity in the chemical transformations while keeping a reasonably flexible framework constitute a major objective. The work will be divided in three main work packages, one devoted to the properties of small molecules or fragments containing a single functional group; the second addresses competition in multiple functionalized molecules; and third is dedicated to the specific transformations of two molecules that have already been identified as potential platform generators. The goal is to identify suitable candidates that could be synthetized and tested in the Institute facilities.

1 496 200 €

Start date: 2010-10-01, End date: 2015-09-30

The overall objective of the proposal is to develop enabling chemical technologies to address two important problems in biology: detect in a nondestructive fashion gene expression or microRNA sequences in vivo and, secondly, study the role of multivalency and spatial organization in carbohydrate recognition. Both of these projects exploit the programmable pre-organization of peptide nucleic acid (PNA) to induce a chemical reaction in the first case or modulate a ligand-receptor interaction in the second case. For nucleic acid detection, a DNA or RNA fragment will be utilized to bring two PNA fragments bearing reactive functionalities in close proximity thereby promoting a reaction. Two types of reactions are proposed, the first one to release a fluorophore for imaging purposes and the second one to release a drug as an “intelligent” therapeutic. If affinities are programmed such that hybridization is reversible, the template can work catalytically leading to large amplifications. As a proof of concept, this method will be used to measure the transcription level of genes implicated in stem cell differentiation and detect mutations in oncogenes. For the purpose of studying multivalent carbohydrate ligand architectures, the challenge of chemical synthesis has been a limiting factor. A supramolecular approach is proposed herein where different arrangements of carbohydrates can be displayed in a well organized fashion by hybridizing PNA-tagged carbohydrates to DNA templates. This will be used not only to control the distance between multiple ligands or to create combinatorial arrangements of hetero ligands but also to access more complex architectures such as Hollyday junctions. The oligosaccharide units will be prepared using de novo organoctalytic reactions. This technology will be first applied to probe the recognition events between HIV and dendritic cells which promote HIV infection.

1 249 980 €

Start date: 2008-07-01, End date: 2013-06-30

Recent intensive research on the laser spectroscopy of neutral gas-phase biomolecules has yielded a detailed picture of their structures and conformational preferences away from the complications of the bulk environment. In contrast, work on ionic systems has been sparse despite the fact that many important molecular groups are charged under physiological conditions. To address this probelm, we have developed a custom-built laser spectrometer, which incorporates a distincitive electrospray ionisation (ESI) cluster ion source, dedicated to producing biological anions (ATP,oligonucleotides) and their microsolvated clusters for structural characterization. Many previous laser spectrometers with ESI sources have suffered from producing "hot" congested spectra as the ions were produced at ambient temperatures. This is a particularly serious limitation for spectroscopic studies of biomolecules, since these systems can possess high internal energies due tothe presence of numerous low frequency modes. Our spectrometer overcomes this problem by exploiting the newly developed physics technique of "buffer gas cooling" to produce cold ESI molecular ions. In this proposal, we now seek to exploit the new laser-spectrometer to perform detailed spectroscopic interrogations of ESI generated biomolecular anions and clusters. In addition to traditional ion-dissociation spectroscopies, we propose to develop two new laser spectroscopy techniques (Two-color tuneable IR spectroscopy and Dipole-bound excited state spectroscopy) to give the broadest possible structural characterizations of the systems of interest. Studies will focus on ATP/GTP-anions, olignonucleotides, and sulphated and carboxylated sugars. These methodologies will provide a general approach for performing temperature-controlled spectroscopic characterizations of isolated biological ions, with measurements on the corresponding micro-solvated clusters providing details of how the molecules are perturbed by solvent.

1 250 000 €

Start date: 2008-10-01, End date: 2015-06-30

We are largely unaware of our own motives. Understanding our motives can be reduced to knowing how we form goals and these goals translate into behavior. Goals can be defined as pleasurable situations that we particularly value and that we intend to reach. Recent investigation in the emerging field of neuro-economics has put forward a neuronal network constituting a brain valuation system (BVS). We wish to build a more comprehensive account of motivational processes, investigating not only valuation and choice but also effort (how much energy we would spend to attain a goal). More specifically, our aims are to better describe 1) how the brain assigns values to various objects and actions, 2) how values depend on parameters such as reward magnitude, probability, delay and cost, 3) how values are affected by social contexts, 4) how values are modified through learning and 5) how values influence the brain systems (perceptual, cognitive and motor) that underpin behavioral performance. To these aims, we would combine three approaches: 1) human cognitive neuroscience, which is central as we ultimately wish to understand ourselves, as well as human pathological conditions where motivation is either deficient (apathy) or out of control (compulsion), 2) primate neurophysiology, which is essential to describe information processing at the single-unit level and to derive causality by observing behavioral consequences of brain manipulations, 3) computational modeling, which is mandatory to link quantitatively the different descriptions levels (single-unit recordings, local field potentials, regional BOLD signal, vegetative manifestations and motor outputs). A bayesian framework will be developed to infer from experimental measures the subjects prior beliefs and value functions. We believe that our team, bringing together three complementary perspectives on motivation within a clinical environment, would represent a unique education and research center in Europe.

1 346 000 €

Start date: 2011-03-01, End date: 2016-08-31

Primary energy conversion in nature is powered by highly efficient enzymes that capture chemical or light energy and transduce it into other energy forms. These processes are catalyzed by coupled transfers of protons and electrons (PCET), but their fundamental mechanistic principles are not well understood. In order to obtain a molecular-level understanding of the functional elements powering biological energy conversion processes, we will study the catalytic machinery of one of the largest and most intricate enzymes in mitochondria and bacteria, the respiratory complex I. This gigantic redox-driven proton-pump functions as the entry point for electrons into aerobic respiratory chains, and it employs the energy released from a chemical reduction process to transport protons up to 200 Å away from its active site. Its molecular structure from bacteria and eukaryotes was recently resolved, but the origin of this remarkable action-at-a-distance effect still remains unclear. We employ and develop multi-scale quantum and classical molecular simulation techniques in combination with de novo-protein design methodology to identify and isolate the functional elements that catalyze the long-range PCET reactions in complex I. To fully understand the natural PCET-elements, we will further engineer central parts of this machinery into artificial protein frameworks, with the goal of designing modules for redox-driven proton pumps from first principles. The project aims to establish a fundamental understanding of nature's toolbox of catalytic elements, to elucidate how the complex biochemical environment contributes to the catalytic effects, and to provide blueprints that can guide the design of man-made enzymes for sustainable energy technology.

1 494 368 €

Start date: 2017-02-01, End date: 2022-01-31

Over the past decades, silicon became the most used material for electronic, however its indirect band gap limits its use for optics and optoelectronics. As a result alternatives semiconductor such as III-V and II-VI materials are used to address a broad range of complementary application such as LED, laser diode and photodiode. However in the infrared (IR), the material challenge becomes far more complex. New IR applications, such as flame detection or night car driving assistance are emerging and request low cost detectors. Current technologies, based on epitaxially grown semiconductors are unlikely to bring a cost disruption and organic electronics, often viewed as the alternative to silicon based materials is ineffective in the mid-IR. The blackQD project aims at transforming colloidal quantum dots (CQD) into the next generation of active material for IR detection. CQD are attracting a high interest because of their size tunable optical features and next challenges is their integration in optoelectronic devices and in particular for IR features. The project requires a combination of material knowledge, with clean room nanofabrication and IR photoconduction which is unique in Europe. I organize blackQD in three mains parts. The first part relates to the growth of mercury chalcogenides nanocrystals with unique tunable properties in the mid and far-IR. To design devices with enhanced properties, more needs to be known on the electronic structure of these nanomaterials. In part II, I propose to develop original methods to probe static and dynamic aspects of the electronic structure. Finally the main task of the project relates to the design of a new generation of transistors and IR detectors. I propose several geometries of demonstrator which for the first time integrate from the beginning the colloidal nature of the CQD and constrain of IR photodetection. The project more generally aims to develop a tool box for the design of the next generation of low cost IR.

1 499 903 €

Start date: 2018-02-01, End date: 2023-01-31

Brain-Computer Interfaces (BCIs) are communication systems that enable users to send commands to computers through brain signals only, by measuring and processing these signals. Making computer control possible without any physical activity, BCIs have promised to revolutionize many application areas, notably assistive technologies, e.g., for wheelchair control, and human-machine interaction. Despite this promising potential, BCIs are still barely used outside laboratories, due to their current poor reliability. For instance, BCIs only using two imagined hand movements as mental commands decode, on average, less than 80% of these commands correctly, while 10 to 30% of users cannot control a BCI at all. A BCI should be considered a co-adaptive communication system: its users learn to encode commands in their brain signals (with mental imagery) that the machine learns to decode using signal processing. Most research efforts so far have been dedicated to decoding the commands. However, BCI control is a skill that users have to learn too. Unfortunately how BCI users learn to encode the commands is essential but is barely studied, i.e., fundamental knowledge about how users learn BCI control is lacking. Moreover standard training approaches are only based on heuristics, without satisfying human learning principles. Thus, poor BCI reliability is probably largely due to highly suboptimal user training. In order to obtain a truly reliable BCI we need to completely redefine user training approaches. To do so, I propose to study and statistically model how users learn to encode BCI commands. Then, based on human learning principles and this model, I propose to create a new generation of BCIs which ensure that users learn how to successfully encode commands with high signal-to-noise ratio in their brain signals, hence making BCIs dramatically more reliable. Such a reliable BCI could positively change human-machine interaction as BCIs have promised but failed to do so far.

1 498 751 €

Start date: 2017-07-01, End date: 2022-06-30

The core function of all brains is to compute the current state of the world, compare it to the desired state of the world and select motor programs that drive behavior minimizing any mismatch. The circuits underlying these functions are the key to understand brains in general, but so far they are completely unknown. Three problems have hindered progress: 1) The animal’s desired state of the world is rarely known. 2) Most studies in simple models have focused on sensory driven, reflex-like processes, and not considered self-initiated behavior. 3) The circuits underlying complex behaviors in vertebrates are widely distributed, containing millions of neurons. With this proposal I aim at overcoming these problems using insects, whose tiny brains solve the same basic problems as our brains but with 100,000 times fewer cells. Moreover, the central complex, a single conserved brain region consisting of only a few thousand neurons, is crucial for sensory integration, motor control and state-dependent modulation, essentially being a ‘brain in the brain’. To simplify the problem further I will focus on navigation behavior. Here, the desired and actual states of the world are equal to the desired and current headings of the animal, with mismatches resulting in compensatory steering. I have previously shown how the central complex encodes the animal’s current heading. Now I will use behavioral training to generate animals with highly defined desired headings, and correlate neural activity with the animal’s ‘intentions’ and actions - at the level of identified neurons. To establish the involved conserved core circuitry valid across insects I will compare species with distinct lifestyles. Secondly, I will reveal how these circuits have evolved to account for each species’ unique ecology. The proposed work will provide a coherent framework to study key concepts of fundamental brain functions in unprecedented detail - using a single, conserved, but flexible neural circuit.

1 500 000 €

Start date: 2017-01-01, End date: 2021-12-31

We are currently witnessing a paradigm shift in our understanding of human brain function, moving towards a clearer description of cortical processing. Sensory systems are no longer considered as 'passively recording' but rather as dynamically anticipating and adapting to the rapidly changing environment. These new ideas are encompassed in the predictive coding framework, and indeed in a unifying theory of the brain (Friston, 2010). In terms of brain computation, a predictive model is created in higher cortical areas and communicated to lower sensory areas through feedback connections. Based on my pioneering research I propose experiments that are capable of ‘brain-reading’ cortical feedback– which would contribute invaluable data to theoretical frameworks. The proposed research project will advance our understanding of ongoing brain activity, contextual processing, and cortical feedback - contributing to what is known about general cortical functions. By providing new insights as to the information content of cortical feedback, the proposal will fill one of the most important gaps in today’s knowledge about brain function. Friston’s unifying theory of the brain (Friston, 2010) and contemporary models of the predictive-coding framework (Hawkins and Blakeslee, 2004;Mumford, 1992;Rao and Ballard, 1999) assign feedback processing an essential role in cortical processing. Compared to feedforward information processing, our knowledge about feedback processing is in its infancy. The proposal introduces parametric and explorative brain reading designs to investigate this feedback processing. The chief goal of my proposal will be precision measures of cortical feedback, and a more ambitious objective is to read mental images and inner thoughts.

1 494 714 €

Start date: 2012-12-01, End date: 2017-11-30

Our ability to think, to memorize and focus our thoughts depends on acetylcholine signaling in the brain. The loss of cholinergic signalling in for instance Alzheimer’s disease strongly compromises these cognitive abilities. The traditional view on the role of cholinergic input to the neocortex is that slowly changing levels of extracellular acetylcholine (ACh) mediate different arousal states. This view has been challenged by recent studies demonstrating that rapid phasic changes in ACh levels at the scale of seconds are correlated with focus of attention, suggesting that these signals may mediate defined cognitive operations. Despite a wealth of anatomical data on the organization of the cholinergic system, very little understanding exists on its functional organization. How the relatively sparse input of cholinergic transmission in the prefrontal cortex elicits such a profound and specific control over attention is unknown. The main objective of this proposal is to develop a causal understanding of how cellular mechanisms of fast acetylcholine signalling are orchestrated during cognitive behaviour. In a series of studies, I have identified several synaptic and cellular mechanisms by which the cholinergic system can alter neuronal circuitry function, both in cortical and subcortical areas. I have used a combination of behavioral, physiological and genetic methods in which I manipulated cholinergic receptor functionality in prefrontal cortex in a subunit specific manner and found that ACh receptors in the prefrontal cortex control attention performance. Recent advances in optogenetic and electrochemical methods now allow to rapidly manipulate and measure acetylcholine levels in freely moving, behaving animals. Using these techniques, I aim to uncover which cholinergic neurons are involved in fast cholinergic signaling during cognition and uncover the underlying neuronal mechanisms that alter prefrontal cortical network function.

1 499 242 €

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

My lab's work ranges from basic science, querying brain plasticity and sensory integration, to technological developments, allowing the blind to be more independent and even “see” using sounds and touch similar to bats and dolphins (a.k.a. Sensory Substitution Devices, SSDs), and back to applying these devices in research. We propose that, with proper training, any brain area or network can change the type of sensory input it uses to retrieve behaviorally task-relevant information within a matter of days. If this is true, it can have far reaching implications also for clinical rehabilitation. To achieve this, we are developing several innovative SSDs which encode the most crucial aspects of vision and increase their accessibility the blind, along with targeted, structured training protocols both in virtual environments and in real life. For instance, the “EyeMusic”, encodes colored complex images using pleasant musical scales and instruments, and the “EyeCane”, a palm-size cane, which encodes distance and depth in several directions accurately and efficiently. We provide preliminary but compelling evidence that following such training, SSDs can enable almost blind to recognize daily objects, colors, faces and facial expressions, read street signs, and aiding mobility and navigation. SSDs can also be used in conjunction with (any) invasive approach for visual rehabilitation. We are developing a novel hybrid Visual Rehabilitation Device which combines SSD and bionic eyes. In this set up, the SSDs is used in training the brain to “see” prior to surgery, in providing explanatory signal after surgery and in augmenting the capabilities of the bionic-eyes using information arriving from the same image. We will chart the dynamics of the plastic changes in the brain by performing unprecedented longitudinal Neuroimaging, Electrophysiological and Neurodisruptive approaches while individuals learn to ‘see’ using each of the visual rehabilitation approaches suggested here.

1 499 900 €

Start date: 2013-09-01, End date: 2018-08-31

The Smart Building Networks (BuildNet) program will develop optimizing controllers capable of coordinating the flow of power to and from large networks of smart buildings in order to offer critical services to the power grid. The network will make use of the thermal storage of the structures and on-site micro generation capabilities of next-generation buildings, as well as the electrical capacity of attached electric vehicles in order to intelligently control the interaction between the network of buildings and the grid. The wide range of electric utility applications, such as wind capacity firming or congestion relief, that will be possible as a result of this coordinated control will in turn allow a significant increase in the percentage of European power generated from destabilizing renewable sources. Technologically, BuildNet will be built around optimization-based or model predictive control (MPC), a paradigm that is ideally suited to the task of incorporating the current network state and forward-looking information into an optimal decision-making process. The project team will develop novel distributed MPC controllers that utilize the flexibility in the consumption, storage and generation of a distributed network of buildings by exploiting the extensive experience of the PI in optimization-based control and MPC for energy efficient buildings. Because of its theoretically grounded optimization-based control approach, holistic view of building systems and connected networks, as well as a future-looking technological scope, BuildNet's outputs will deliver impact and be relevant to researchers and practitioners alike.

1 460 232 €

Start date: 2012-12-01, End date: 2017-11-30

Combinatorial Computational Chemistry is developed as a standard tool to tackle complex problems in chemistry and materials science. The method employs a series of state-of-the-art methods, ranging from empirical molecular mechanics to first principles calculations, as well as of mathematical (graph theoretical and combinatorial) methods. The process is similar as in experimental combinatorial chemistry: First, a large set of candidate structures is generated which is complete in the sense that the best possible structure for a particular purpose must be found among the set. This structure is then identified using computational chemistry. We will apply methodologies at different stages in hierarchical order and successively screen the set of candidate structures. Screening criteria are based on the computer simulations and include geometry, stability and properties of the candidate structures. Detailed characteristics of the final materials will be simulated, including the X-ray diffraction pattern, the electronic structure, and the target properties. We will apply C3 to two important problems of environmental science. (i) We will optimise nanoporous materials to act as molecular sieves to separate water from ethanol, an important task for the production of biofuels. Here, materials are optimised to transport ethanol, but not water (or vice versa). The tuning parameters are the channel size of the material and its polarity. (ii) We will optimise nanoporous materials to transport protons, an important task for the design of energy-efficient fuel cells, by distributing flexible functional groups, acting as hopping sites for the protons, in the framework.

1 500 000 €

Start date: 2011-02-01, End date: 2016-04-30

With this proposal the PI capitalises on his recent breakthroughs in transition metal catalysed carbene (migratory) insertion reactions to build up a new research line for controlled catalytic preparation of a variety of new functionalised (co)polymers with expected special material properties. Metallo-carbenes are well-known intermediates in olefin cyclopropanation and olefin metathesis, but the PI recently discovered that their chemistry is far richer. He demonstrated for the first time that metallo-carbenoids can be used in transition metal catalysed insertion polymerisation to arrive at completely new types of stereoregular carbon-chain polymers functionalised at each carbon of the polymer backbone. Rhodium mediated polymerisation of carbenes provides the means to prepare new materials with yet unknown properties. It also provides a valuable alternative to prepare practically identical polymers as in the desirable (but still unachievable) highly stereo-selective (co)polymerisation of functionalised olefins, representing the ‘holey-grail’ in world-wide TM polymerisation catalysis research. The mechanism and scope of this remarkable new discovery will be investigated and new, improved catalysts will be developed for the preparation of novel materials based on homo- and copolymerisation of a variety of carbene precursors. Copolymerisation of carbenes and other reactive monomers will also be investigated and the properties of all new materials will be investigated. In addition the team will try to uncover new reactions in which carbene insertion reactions play a central role. DFT calculations suggest that the transition state (TS) of the new carbene polymerisation reaction is very similar to the TS’s of a variety of carbonyl insertion reactions. Based on this analogy, the team will investigate several new carbene insertion reactions, potentially leading to new, useful polymeric materials and new synthetic routes to prepare small functional organic molecules.

1 250 000 €

Start date: 2008-08-01, End date: 2013-07-31

"Spatially distributed multi-agent networks have been used successfully to model a wide range of natural, social and engineered complex systems, such as animal groups, online communities and electric power grids. In various contexts, it is crucial to introduce control actions into such networks to either achieve desired collective dynamics or test the understanding of the systems’ behavior. However, controlling such systems is extremely challenging due to agents’ complicated sensing, communication and control interactions that are distributed in space. Systematic methodologies to attack this challenge are in urgent need, especially when vast efforts are being made in multiple disciplines to apply the model of complex multi-agent networks. The goal of the project is twofold. First, understand whether a complex multi-agent network can be controlled effectively when the agents can only sense and communicate locally. Second, provide methodologies to implement distributed control in typical spatially distributed complex multi-agent networks. The project requires integrated skills since both rigorous theoretical analysis and novel empirical explorations are necessary. The research methods that I plan to adopt have two distinguishing features. First, I use tools from algebraic graph theory and complex network theory to investigate the impact of network topologies on the systems’ controller performances characterized by mathematical control theory. Second, I utilize a homemade robotic-fish testbed to implement various multi-agent control algorithms. The unique combination of theoretical and empirical studies is expected to lead to breakthroughs in developing an integrated set of principles and techniques to control effectively spatially distributed multi-agent networks. The expected results will make original contributions to control engineering and robotics, and inspire innovative research methods in theoretical biology and theoretical sociology."

1 495 444 €

Start date: 2013-01-01, End date: 2017-12-31

The mammalian brain is assembled from thousands of neuronal cell types that are organized into distinct circuits to perform behaviourally relevant computations. To gain mechanistic insights about brain function and to treat specific diseases of the nervous system it is crucial to understand what these local circuits are computing and how they achieve these computations. By examining the structure and function of a few genetically identified and experimentally accessible neural circuits we plan to address fundamental questions about the functional architecture of neural circuits. First, are cell types assigned to a unique functional circuit with a well-defined function or do they participate in multiple circuits (“multitasking cell types”), adjusting their role depending on the state of these circuits? Second, does a neural circuit perform “a single computation” or depending on the information content of its inputs can it carry out radically different functions? Third, how, among the large number of other cell types, do the cells belonging to the same functional circuit connect together during development? We use the mouse retina as a model system to address these questions. Finally, we will study the structure and function of a specialised neural circuit in the human fovea that enables humans to read. We predict that our insights into the mechanism of multitasking, network switches and the development of selective connectivity will be instructive to study similar phenomena in other brain circuits. Knowledge of the structure and function of the human fovea will open up new opportunities to correlate human retinal function with human visual behaviour and our genetic technologies to study human foveal function will allow us and others to design better strategies for restoring vision for the blind.

1 499 000 €

Start date: 2010-11-01, End date: 2015-10-31

The cerebellum is a critical regulator of motor function, which acts to integrate ongoing body states, sensory inputs and desired outcomes to adjust motor output. This motor control is achieved by a relatively small number of neuron types receiving two main sources of inputs and forming a single output pathway, the axons of Purkinje cells. Although the cerebellum is one of the first structures of the brain to differentiate, it undergoes a prolonged differentiation period such that mature cellular and circuit configuration is achieved only late after birth. Despite the functional importance of this structure, the molecular mechanisms that control type-specific cerebellar neurons generation, differentiation, and circuit assembly are poorly understood and are the topic of the present study. In my research program, I propose to investigate the transcriptional programs that control the generation of distinct subtypes of cerebellar neurons from progenitors, including Purkinje cells, granule cells and molecular layer interneurons (Work Package 1); the diversity of Purkinje cells across cerebellar regions (Work Package 2) and the postnatal differentiation and circuit integration of granule cells and molecular layer interneurons (Work Package 3). The general bases of the approach I propose consist in: i) specifically label cerebellar neuron progenitors and their progeny at sequential developmental time points pre- and post-natally using birthdate-based tagging, ii) FAC-sort these distinct cell types, iii) isolate these cells and identify their transcriptional signatures with single-cell resolution, iv) functionally interrogate top candidate genes and associated transcriptional programs using in vivo gain- and loss-of-function approaches. Together, these experiments aim at deciphering the cell-intrinsic processes controlling cerebellar circuit formation, towards a better understanding of the molecular mechanisms underlying cerebellar function and dysfunction.

1 499 885 €

Start date: 2018-02-01, End date: 2023-01-31

As a result of their unplanned, license-free nature, WiFi networks have grown quickly in recent years, giving users unprecedented improvements in wireless access to the Internet. But being “chaotic,” i.e. unplanned, they have grown to be victims of their own success: when eager users set up too many wireless access points in a densely-populated area, the resulting noise and interference hurt everyones throughput and connectivity. Cellular mobile telephone networks are planned carefully, but in order to expand coverage indoors, providers are turning to customer-deployed femtocells, thus incuring the drawbacks of chaotic WiFi networks. We propose a ground-up redesign of chaotic wireless networks, with new architectural contributions focusing on what information the physical layer should pass up to higher layers. We propose a new physical layer interface called SoftAoA that passes angle-of-arrival (AoA) information from the physical layer up to higher layers. Using this expanded physical layer interface, we will first investigate fountain coding and receiver-based rate adaptation methods to improve wireless capacity in the vagaries of the “grey zone” of marginal coverage. Second, we will investigate improvements to security and localization that can be made based on the profiling of incoming packets’ AoA at an access point. Finally, we will investigate how a chaotically-deployed network can mitigate the interference it experiences from networks not under the same administrative control, and manage the interference it causes to those networks. The result will be more scalable, secure, and reliable chaotic wireless networks that play an even more prominent role in our lives.

1 457 675 €

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

Nanoscale systems binding single molecules, or small numbers of molecules, in conducting junctions show considerable promise for a range of technological applications, from photovoltaics to rectifiers to sensors. These environments differ significantly from the traditional domain of chemical studies involving molecules in solution and the gas phase, necessitating renewed efforts to understand the physical properties of these systems. The objective of this proposal concerns one particular class of physical processes: understanding and controlling local heating in molecular junctions in terms of excitation, dissipation and transfer. Local heating and dissipation in molecular junctions has long been a concern due to the possibly detrimental impact on device stability and function. More recently there has been increased interest, as these processes underlie both spectroscopic techniques and potential technological applications. Together these issues make an investigation of ways to chemically control local heating in molecular junctions timely and important. The proposal objective will be addressed through the investigation of three challenges: - Developing chemical control of local heating in molecular junctions. - Developing chemical control of heat dissipation in molecular junctions. - Design of optimal thermoelectric materials. These three challenges constitute distinct, yet complementary, avenues for investigation with progress in each area supporting the other two. All three challenges build on existing theoretical methods, with the important shift of focus to methods to achieve chemical control. The combination of state-of-the-art computational methods with careful chemical studies promises significant new developments for the area.

1 499 999 €

Start date: 2010-12-01, End date: 2015-11-30

Smell and taste are the least studied of all senses. Very little is known about chemosensory information processing beyond the level of receptor neurons. Every morning we enjoy our coffee thanks to our brains ability to combine and process multiple sensory modalities. Meanwhile, we can still review a document on our desk by adjusting the weights of numerous sensory inputs that constantly bombard our brains. Yet, the smell of our coffee may remind us that pleasant weekend breakfast through associative learning and memory. In the proposed project we will explore the function and the architecture of neural circuits that are involved in olfactory and gustatory information processing, namely habenula and brainstem. Moreover we will investigate the fundamental principles underlying multimodal sensory integration and the neural basis of behavior in these highly conserved brain areas. To achieve these goals we will take an innovative approach by combining two-photon calcium imaging, optogenetics and electrophysiology with the expanding genetic toolbox of a small vertebrate, the zebrafish. This pioneering approach will enable us to design new types of experiments that were unthinkable only a few years ago. Using this unique combination of methods, we will monitor and perturb the activity of functionally distinct elements of habenular and brainstem circuits, in vivo. The habenula and brainstem are important in mediating stress/anxiety and eating habits respectively. Therefore, understanding the neural computations in these brain regions is important for comprehending the neural mechanisms underlying psychological conditions related to anxiety and eating disorders. We anticipate that our results will go beyond chemical senses and contribute new insights to the understanding of how brain circuits work and interact with the sensory world to shape neural activity and behavioral outputs of animals.

1 499 471 €

Start date: 2014-04-01, End date: 2019-03-31

"From scientific publications to the popular media, there have been numerous speculations about wirelessly controlled microrobots (microbots) navigating the human body. Microbots have the potential to revolutionize analytics, targeted drug delivery, and microsurgery, but until now there has not been any untethered microscopic system that could be properly moved let alone controlled in fluidic environments. Using glancing angle (physical vapor deposition) we will grow billions of micron-sized colloidal screw-propellers on a wafer. These chiral mesoscopic screws can be magnetized and moved through solution under computer control. The screw-propellers resemble artificial flagella and are the only ‘microbots’ to date that can be fully controlled in solution at micron length scales. The proposed work will advance the fabrication so that active microbots can be applied in rheological measurements and analytics. We will use these novel probes in bio-microrheology with the potential to probe the viscoelastic properties of membranes and tissues, and to explore questions of micro-hydrodynamics. At the same time we will develop these structures as ""colloidal molecules"" and grow asymmetric mesoscopic particles with tailored shapes and properties. We propose experiments that allow the observation of fundamental effects, such as chiral Brownian motion, something that exist at the molecular scale, but has never been observed to date. Similarly, we will be able to demonstrate for the first time chiral separations based purely on physical fields. The proposed technical advances of the growth of nanostructured surfaces will at the same time permit wafer-scale 3-D nano-structuring for photonic and plasmonic applications, which we plan to demonstrate. We will develop a system for targeted drug delivery, study the interaction of swarms of microbots and devise techniques to control and image these swarms."

1 479 760 €

Start date: 2012-02-01, End date: 2018-01-31

The key organizing principles that characterize neuronal systems include asymmetric, parallel, and topographic connectivity of the neural circuits. The main aim of my research is to elucidate the key principles underlying functional development of neural circuits by focusing on those organizing principles. I choose mouse visual system as my model since it contains all of these principles and provides sophisticated genetic tools to label and manipulate individual circuit components. My research is based on the central hypothesis that the mechanisms of brain development cannot be fully understood without first identifying individual functional cell types in adults, and then understanding how the functions of these cell types become established, using cell-type-specific molecular and synaptic mechanisms in developing animals. Recently, I have identified several transgenic mouse lines in which specific cell types in a visual center, the superior colliculus, are labeled with Cre recombinase in both developing and adult animals. Here I will take advantage of these mouse lines to ask fundamental questions about the functional development of neural circuits. First, how are distinct sensory features processed by the parallel topographic neuronal pathways, and how do they contribute to behavior? Second, what are the molecular and synaptic mechanisms that underlie developmental circuit plasticity for forming parallel topographic neuronal maps in the brain? Third, what are the molecular mechanisms that set up spatially asymmetric circuit connectivity without the need for sensory experience? I predict that my insights into the developmental mechanism of asymmetric, parallel, and topographic connectivity and circuit plasticity will be instructive when studying other brain circuits which contain similar organizing principles.

1 500 000 €

Start date: 2015-04-01, End date: 2020-03-31

A key question in neuroscience is how information is processed by sensory systems to guide behavior. Most of our knowledge about sensory processing is based on presentation of simple isolated stimuli and recording corresponding neural activity in relevant brain areas. Yet sensory stimuli in real life are never isolated and typically not simple. How the brain processes complex stimuli, simultaneously arising from multiple objects is unknown. Our daily experience (as well as well-controlled experiments) shows that only parts of a complex sensory scene can be perceived - we cannot listen to more than one speaker in a party. Importantly, one can easily choose what is important and should be processed and what can be ignored as background. These observations lead to the prevalent hypothesis that feedback projections from ‘higher’ brain areas to more peripheral sensory areas are involved in processing of complex stimuli. However experimental analysis of signals conveyed by feedback projections in behaving animals is scarce. The nature of these signals and how they relate to behavior is unknown. Here I propose a cutting edge approach to directly record feedback signals in the olfactory system of behaving mice. We will use chronically implanted electrodes to record the modulation of olfactory bulb (OB) principal neurons by task related context. Additionally, we will record from piriform cortical (PC) neurons that project back to the OB. These will be tagged with channelrhodopsin-2 and identified by light sensitivity. Finally, we will express the spectrally distinct Ca++ indicators GCaMP6 and RCaMP2 in PC neurons and in olfactory sensory neurons, respectively, and use 2-photon microscopy to analyze the spatio-temporal relationship between feedforward and feedback inputs in the OB. This comprehensive approach will provide an explanation of how feedforward and feedback inputs are integrated to process complex stimuli.

1 500 000 €

Start date: 2018-04-01, End date: 2023-03-31

COLDNANO (UltraCOLD ion and electron beams for NANOscience), aspires to build novel ion and electron sources with superior performance in terms of brightness, energy spread and minimum achievable spot size. Such monochromatic, spatially focused and well controlled electron and ion beams are expected to open many research possibilities in material sciences, in surface investigations (imaging, lithography) and in semiconductor diagnostics. The proposed project intends to develop sources with the best beam quality ever produced and to assess them in some advanced surface science research domains. Laterally, I will develop expertise exchange with one Small and Medium Enterprise who will exploit industrial prototypes. The novel concept is to create ion and electron sources using advanced laser cooling techniques combined with the particular ionization properties of cold atoms. It would then be first time that “laser cooling” would lead to a real industrial development. A cesium magneto-optical trap will first be used. The atoms will then be excited by lasers and ionized in order to provide the electron source. The specific extraction optics for the electrons will be developed. This source will be compact and portable to be used for several applications such as Low Energy Electron Microscopy, functionalization of semi-conducting surfaces or high resolution Electron Energy Loss Spectrometry by coupling to a Scanning Transmission Electron Microscope. Based on the knowledge developed with the first experiment, a second ambitious xenon dual ion and electron beam machine will then be realized and used to study the scattering of ion and electron at low energy. Finally, I present a very innovative scheme to control the time, position and velocity of individual particles in the beams. Such a machine providing ions or electrons on demand would open the way for the “ultimate” resolution in time and space for surface analysis, lithography, microscopy or implantation.

1 944 000 €

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

Networks have been studied in depth for several decades, but one aspect has received little attention: Interference. Most networks use clever algorithms to avoid interference, and this strategy has proved effective for traditional supply-chain or wired communication networks. However, the emergence of wireless networks revealed that simply avoiding interference leads to significant performance loss. A wealth of cooperative communication strategies have recently been developed to address this issue. Two fundamental roadblocks are emerging: First, it is ultimately unclear how to integrate cooperative techniques into the larger fabric of networks (short of case-by-case redesigns); and second, the lack of source/channel separation in networks (i.e., more bits do not imply better end-to-end signal quality) calls for ever more specialized cooperative techniques. This proposal advocates a new understanding of interference as computation: Interference garbles together inputs to produce an output. This can be thought of as a certain computation, perhaps subject to noise or other stochastic effects. The proposed work will develop strategies that permit to exploit this computational potential. Building on these ``computation codes,'' an enhanced physical layer is proposed: Rather than only forwarding bits, the revised physical layer can also forward functions from several transmitting nodes to a receiver, much more efficiently than the full information. Near-seamless integration into the fabric of existing network architectures is thus possible, providing a solution for the first roadblock. In response to the second roadblock, computation codes suggest new computational primitives as fundamental currencies of information.

1 776 473 €

Start date: 2011-05-01, End date: 2016-04-30

High-speed optical fiber networks form the backbone of the information and communication technologies, including the Internet. More than 99% of the Internet data traffic is carried by a network of global optical fibers. Despite their great importance, today's optical fiber networks face a looming capacity crunch: The achievable rates of all current technologies characteristically vanish at high input powers due to distortions that arise from fiber nonlinearity. The solution of this long-standing complex problem has become the holy grail of the field of the optical communication. The aim of this project is to develop a novel foundation for optical fiber communication based on the nonlinear Fourier transform (NFT). The NFT decorrelates signal degrees-of-freedom in optical fiber, in much the same way that the conventional Fourier transform does for linear systems. My collaborators and I have recently proposed nonlinear frequency-division multiplexing (NFDM) based on the NFT, in which the information is encoded in the generalized frequencies and their spectral amplitudes (similar to orthogonal frequency-division multiplexing). Since distortions such as inter-symbol and inter-channel interference are absent in NFDM, it achieves data rates higher than conventional methods. The objective of this proposal is to advance NFDM to the extent that it can be built in practical large-scale systems, thereby overcoming the limitation that fiber nonlinearity sets on the transmission rate of the communication networks. The proposed research relies on novel methodology and spans all aspects of the NFDM system design, including determining the fundamental information-theoretic limits, design of the NFDM transmitter and receiver, algorithms and implementations. The feasibility of the project is manifest in preliminary proof-of-concepts in small examples and toy models, PI's leadership and track-record in the field, as well as the ideal research environment.

1 499 180 €

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

Multidrug resistant bacteria that render worthless the current arsenal of antibiotics are a growing global problem. This grave challenge could be tackled by polyketide synthases (PKSs), which are gigantic modular enzymatic assembly lines for natural products. PKSs could be developed for industry to produce chemically difficult to synthesize drugs, but cannot be harnessed until we understand how they work on the molecular level. However, such understanding is missing because we cannot easily investigate large complexes with current structural biology and modeling methods. A key puzzle is how the function of these multicomponent systems emerges from atomic-scale interactions of their parts. Solving this puzzle requires a holistic approach involving measuring and modeling the relevant interacting parts together. Our goal is to develop a multidisciplinary approach rooted in solid and solution state NMR that will make possible studies of complexes from PKSs. The two main challenges for the NMR of PKSs are increasing sensitivity and resolution. Recent innovations from our lab allow application of solid-state to study large complexes in 2–10 nanomole quantities. Building on this approach, with a protein-antibody complex as a test case, we will develop new NMR methods that will enable a study of structure and motions of domains in complexes. We will probe, for the first time, the structural dynamics of PKSs of enacyloxin and gladiolin, which are antibiotics against life-threatening multidrug resistant hospital-acquired Acinetobacter baumannii infections and tuberculosis. These studies will guide rational engineering of the PKSs to enable synthetic biology approaches to produce new antibiotics. If successful, this project will go beyond the state of the art by: enabling studies of unknown proteins in large complexes and providing unique insights into novel mechanisms for controlling biosynthesis in PKSs, turning them into truly programmable synthetic biology devices.

1 999 044 €

Start date: 2015-05-01, End date: 2020-04-30

The field of electronics has been a veritable powerhouse of the economy, driving technological breakthroughs that affect all aspects of everyday life. Aside from silicon, there has been growing interest in developing a novel generation of electronic devices based on pi-conjugated polymers and oligomers. While their goal is not to exceed the performance of silicon technologies, they could enable far reduced fabrication costs as well as completely new functionalities (e.g. mechanical flexibility, transparency, impact resistance). The performance of these organic devices is greatly dependent on the organization and electronic structures of π-conjugated polymer chains at the molecular level. To achieve full potential, technological developments require fine-tuning of the relative orientation/position of the pi-conjugated moieties, which provide a practical means to enhance electronic properties. The discovery pace of novel materials can be accelerated considerably by the development of efficient computational schemes. This requires an integrated approach, based on which the structural, electronic, and charge transport properties of novel molecular candidates are evaluated computationally and predictions benchmarked by proof of principle experiments. This research program aims at developing a threefold computational screening strategy enabling the design of an emerging class of molecular precursors based on the insertion of π-conjugated molecules into self-assembled hydrogen bond aggregator segments (e.g. oligopeptide, nucleotide and carbohydrate motifs). These bioinspired functionalized pi-conjugated systems offer the highly desirable prospect of achieving ordered suprastructures abundant in nature with the enhanced functionalities only observed in synthetic polymers. A more holistic objective is to definitively establish the relationship between highly ordered architectures and the nature of the electronic interactions and charge transfer properties in the assemblies.

1 482 240 €

Start date: 2012-12-01, End date: 2017-11-30

"CON-HUMO focuses on novel concepts for automatic control based on data-driven human models and machine learning. This enables innovative control applications that are difficult if not impossible to realize using traditional control and identification methods, in particular in the challenging area of smart human-machine interaction. In order to achieve intuitive and efficient goal-oriented interaction, anticipation is key. For control selection based on prediction a dynamic model of the human interaction behavior is required, which, however, is difficult to obtain from first principles. In order to cope with the high complexity of human behavior with unknown inputs and only sparsely available training data we propose to use machine-learning techniques for statistical modeling of the dynamics. In this new field of human interaction modeling – data-driven and machine-learned – control methods with guaranteed properties do not exist. CON-HUMO addresses this niche. Key methodological innovation and breakthrough is the merger of probabilistic learning with model-based control concepts through model confidence and prediction uncertainty. For the sake of concreteness and evaluation the focus is on one of the most challenging problem classes, namely physical human-machine interaction: Because of the physical contact between the human and the machine not only information, but also energy is exchanged posing fundamental challenges for real-time human-adaptive and safe decision making/control and requiring provable stability and performance guarantees. The developed methods are a direct enabler for societally important applications such as machine-based physical rehabilitation, mobility and manipulation aids for elderly, and collaborative human-machine production systems. With its fundamental results CON-HUMO lays the ground for the systematic control design for smart human-machine/infrastructure interaction."

1 494 640 €

Start date: 2014-02-01, End date: 2019-01-31

Developing minimalistic biological neural networks and observing their functional activity is crucial to decipher the information processing in the brain. This project aims to address two major challenges: to design and fabricate in vitro biological neural networks that are organized in physiological relevant ways and to provide a label-free monitoring platform capable of observing neural activity both at the neuron resolution and at large fields of view. To do so, the project will develop a unique microfluidic compartmentalized chips where populations of primary neurons will be seeded in deposition chambers with physiological relevant number and densities. Chambers will be connected by microgrooves in which neurites only can grow and whose dimensions will be tuned according to the connectivity pattern to reproduce. To observe the activity of such complex neural networks, we will develop a disruptive observation technique that will transduce the electrical activity of spiking neurons into optical differences observed on a lens-free platform, without calcium labelling and constantly in-incubo. By combining neuro-engineering patterning and the lens-free platform, we will compare individual spiking to global oscillators in basic neural networks under localized external stimulations. Such results will provide experimental insight into computational neuroscience current approaches. Finally, we will design an in vitro network that will reproduce a neural loop implied in major neurodegenerative diseases with physiological relevant neural types, densities and connectivities. This circuitry will be manipulated in order to model Huntington and Parkinson diseases on the chip and assess the impact of known drugs on the functional activity of the entire network. This project will engineer microfluidics chips with physiological relevant neural network and a lensfree activity monitoring platform to answer fundamental and clinically relevant issues in neuroscience.

1 727 731 €

Start date: 2016-11-01, End date: 2021-10-31

Devices in wireless networks are no longer used only for communicating binary information, but also for navigation and to sense their surroundings. We are currently approaching fundamental limitations in terms of communication throughput, position information availability and accuracy, and decision making based on sensory data. The goal of this proposal is to understand how the cooperative nature of future wireless networks can be leveraged to perform timekeeping, positioning, communication, and decision making, so as to obtain orders of magnitude performance improvements compared to current architectures. Our research will have implications in many fields and will comprise fundamental theoretical contributions as well as a cooperative wireless testbed. The fundamental contributions will lead to a deep understanding of cooperative wireless networks and will enable new pervasive applications which currently cannot be supported. The testbed will be used to validate the research, and will serve as a kernel for other researchers worldwide to advance knowledge on cooperative networks. Our work will build on and consolidate knowledge currently dispersed in different scientific disciplines and communities (such as communication theory, sensor networks, distributed estimation and detection, environmental monitoring, control theory, positioning and timekeeping, distributed optimization). It will give a new thrust to research within those communities and forge relations between them.

1 500 000 €

Start date: 2011-05-01, End date: 2016-04-30