Project acronym ACQDIV
Project Acquisition processes in maximally diverse languages: Min(d)ing the ambient language
Researcher (PI) Sabine Erika Stoll
Host Institution (HI) UNIVERSITAT ZURICH
Call Details Consolidator Grant (CoG), SH4, ERC-2013-CoG
Summary "Children learn any language that they grow up with, adapting to any of the ca. 7000 languages of the world, no matter how divergent or complex their structures are. What cognitive processes make this extreme flexibility possible? This is one of the most burning questions in cognitive science and the ACQDIV project aims at answering it by testing and refining the following leading hypothesis: Language acquisition is flexible and adaptive to any kind of language because it relies on a small set of universal cognitive processes that variably target different structures at different times during acquisition in every language. The project aims at establishing the precise set of processes and at determining the conditions of variation across maximally diverse languages. This project focuses on three processes: (i) distributional learning, (ii) generalization-based learning and (iii) interaction-based learning. To investigate these processes I will work with a sample of five clusters of languages including longitudinal data of two languages each. The clusters were determined by a clustering algorithm seeking the structurally most divergent languages in a typological database. The languages are: Cluster 1: Slavey and Cree, Cluster 2: Indonesian and Yucatec, Cluster 3: Inuktitut and Chintang, Cluster 4: Sesotho and Russian, Cluster 5: Japanese and Turkish. For all languages, corpora are available, except for Slavey where fieldwork is planned. The leading hypothesis will be tested against the acquisition of aspect and negation in each language of the sample and also against the two structures in each language that are most salient and challenging in them (e. g. complex morphology in Chintang). The acquisition processes also depend on statistical patterns in the input children receive. I will examine these patterns across the sample with respect to repetitiveness effects, applying data-mining methods and systematically comparing child-directed and child-surrounding speech."
Summary
"Children learn any language that they grow up with, adapting to any of the ca. 7000 languages of the world, no matter how divergent or complex their structures are. What cognitive processes make this extreme flexibility possible? This is one of the most burning questions in cognitive science and the ACQDIV project aims at answering it by testing and refining the following leading hypothesis: Language acquisition is flexible and adaptive to any kind of language because it relies on a small set of universal cognitive processes that variably target different structures at different times during acquisition in every language. The project aims at establishing the precise set of processes and at determining the conditions of variation across maximally diverse languages. This project focuses on three processes: (i) distributional learning, (ii) generalization-based learning and (iii) interaction-based learning. To investigate these processes I will work with a sample of five clusters of languages including longitudinal data of two languages each. The clusters were determined by a clustering algorithm seeking the structurally most divergent languages in a typological database. The languages are: Cluster 1: Slavey and Cree, Cluster 2: Indonesian and Yucatec, Cluster 3: Inuktitut and Chintang, Cluster 4: Sesotho and Russian, Cluster 5: Japanese and Turkish. For all languages, corpora are available, except for Slavey where fieldwork is planned. The leading hypothesis will be tested against the acquisition of aspect and negation in each language of the sample and also against the two structures in each language that are most salient and challenging in them (e. g. complex morphology in Chintang). The acquisition processes also depend on statistical patterns in the input children receive. I will examine these patterns across the sample with respect to repetitiveness effects, applying data-mining methods and systematically comparing child-directed and child-surrounding speech."
Max ERC Funding
1 998 438 €
Duration
Start date: 2014-09-01, End date: 2019-08-31
Project acronym ADDECCO
Project Adaptive Schemes for Deterministic and Stochastic Flow Problems
Researcher (PI) Remi Abgrall
Host Institution (HI) INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Call Details Advanced Grant (AdG), PE1, ERC-2008-AdG
Summary The numerical simulation of complex compressible flow problem is still a challenge nowaday even for simple models. In our opinion, the most important hard points that need currently to be tackled and solved is how to obtain stable, scalable, very accurate, easy to code and to maintain schemes on complex geometries. The method should easily handle mesh refinement, even near the boundary where the most interesting engineering quantities have to be evaluated. Unsteady uncertainties in the model, for example in the geometry or the boundary conditions should represented efficiently.This proposal goal is to design, develop and evaluate solutions to each of the above problems. Our work program will lead to significant breakthroughs for flow simulations. More specifically, we propose to work on 3 connected problems: 1-A class of very high order numerical schemes able to easily deal with the geometry of boundaries and still can solve steep problems. The geometry is generally defined by CAD tools. The output is used to generate a mesh which is then used by the scheme. Hence, any mesh refinement process is disconnected from the CAD, a situation that prevents the spread of mesh adaptation techniques in industry! 2-A class of very high order numerical schemes which can utilize possibly solution dependant basis functions in order to lower the number of degrees of freedom, for example to compute accurately boundary layers with low resolutions. 3-A general non intrusive technique for handling uncertainties in order to deal with irregular probability density functions (pdf) and also to handle pdf that may evolve in time, for example thanks to an optimisation loop. The curse of dimensionality will be dealt thanks Harten's multiresolution method combined with sparse grid methods. Currently, and up to our knowledge, no scheme has each of these properties. This research program will have an impact on numerical schemes and industrial applications.
Summary
The numerical simulation of complex compressible flow problem is still a challenge nowaday even for simple models. In our opinion, the most important hard points that need currently to be tackled and solved is how to obtain stable, scalable, very accurate, easy to code and to maintain schemes on complex geometries. The method should easily handle mesh refinement, even near the boundary where the most interesting engineering quantities have to be evaluated. Unsteady uncertainties in the model, for example in the geometry or the boundary conditions should represented efficiently.This proposal goal is to design, develop and evaluate solutions to each of the above problems. Our work program will lead to significant breakthroughs for flow simulations. More specifically, we propose to work on 3 connected problems: 1-A class of very high order numerical schemes able to easily deal with the geometry of boundaries and still can solve steep problems. The geometry is generally defined by CAD tools. The output is used to generate a mesh which is then used by the scheme. Hence, any mesh refinement process is disconnected from the CAD, a situation that prevents the spread of mesh adaptation techniques in industry! 2-A class of very high order numerical schemes which can utilize possibly solution dependant basis functions in order to lower the number of degrees of freedom, for example to compute accurately boundary layers with low resolutions. 3-A general non intrusive technique for handling uncertainties in order to deal with irregular probability density functions (pdf) and also to handle pdf that may evolve in time, for example thanks to an optimisation loop. The curse of dimensionality will be dealt thanks Harten's multiresolution method combined with sparse grid methods. Currently, and up to our knowledge, no scheme has each of these properties. This research program will have an impact on numerical schemes and industrial applications.
Max ERC Funding
1 432 769 €
Duration
Start date: 2008-12-01, End date: 2013-11-30
Project acronym ADOS
Project AMPA Receptor Dynamic Organization and Synaptic transmission in health and disease
Researcher (PI) Daniel Georges Gustave Choquet
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Advanced Grant (AdG), LS5, ERC-2013-ADG
Summary AMPA glutamate receptors (AMPAR) play key roles in information processing by the brain as they mediate nearly all fast excitatory synaptic transmission. Their spatio-temporal organization in the post synapse with respect to presynaptic glutamate release sites is a key determinant in synaptic transmission. The activity-dependent regulation of AMPAR organization is at the heart of synaptic plasticity processes underlying learning and memory. Dysfunction of synaptic transmission - hence AMPAR organization - is likely at the origin of a number of brain diseases.
Building on discoveries made during my past ERC grant, our new ground-breaking objective is to uncover the mechanisms that link synaptic transmission with the dynamic organization of AMPAR and associated proteins. For this aim, we have assembled a team of neurobiologists, computer scientists and chemists with a track record of collaboration. We will combine physiology, cellular and molecular neurobiology with development of novel quantitative imaging and biomolecular tools to probe the molecular dynamics that regulate synaptic transmission.
Live high content 3D SuperResolution Light Imaging (SRLI) combined with electron microscopy will allow unprecedented visualization of AMPAR organization in synapses at the scale of individual subunits up to the level of intact tissue. Simultaneous SRLI and electrophysiology will elucidate the intricate relations between dynamic AMPAR organization, trafficking and synaptic transmission. Novel peptide- and small protein-based probes used as protein-protein interaction reporters and modulators will be developed to image and directly interfere with synapse organization.
We will identify new processes that are fundamental to activity dependent modifications of synaptic transmission. We will apply the above findings to understand the causes of early cognitive deficits in models of neurodegenerative disorders and open new avenues of research for innovative therapies.
Summary
AMPA glutamate receptors (AMPAR) play key roles in information processing by the brain as they mediate nearly all fast excitatory synaptic transmission. Their spatio-temporal organization in the post synapse with respect to presynaptic glutamate release sites is a key determinant in synaptic transmission. The activity-dependent regulation of AMPAR organization is at the heart of synaptic plasticity processes underlying learning and memory. Dysfunction of synaptic transmission - hence AMPAR organization - is likely at the origin of a number of brain diseases.
Building on discoveries made during my past ERC grant, our new ground-breaking objective is to uncover the mechanisms that link synaptic transmission with the dynamic organization of AMPAR and associated proteins. For this aim, we have assembled a team of neurobiologists, computer scientists and chemists with a track record of collaboration. We will combine physiology, cellular and molecular neurobiology with development of novel quantitative imaging and biomolecular tools to probe the molecular dynamics that regulate synaptic transmission.
Live high content 3D SuperResolution Light Imaging (SRLI) combined with electron microscopy will allow unprecedented visualization of AMPAR organization in synapses at the scale of individual subunits up to the level of intact tissue. Simultaneous SRLI and electrophysiology will elucidate the intricate relations between dynamic AMPAR organization, trafficking and synaptic transmission. Novel peptide- and small protein-based probes used as protein-protein interaction reporters and modulators will be developed to image and directly interfere with synapse organization.
We will identify new processes that are fundamental to activity dependent modifications of synaptic transmission. We will apply the above findings to understand the causes of early cognitive deficits in models of neurodegenerative disorders and open new avenues of research for innovative therapies.
Max ERC Funding
2 491 157 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym AFMIDMOA
Project "Applying Fundamental Mathematics in Discrete Mathematics, Optimization, and Algorithmics"
Researcher (PI) Alexander Schrijver
Host Institution (HI) UNIVERSITEIT VAN AMSTERDAM
Call Details Advanced Grant (AdG), PE1, ERC-2013-ADG
Summary "This proposal aims at strengthening the connections between more fundamentally oriented areas of mathematics like algebra, geometry, analysis, and topology, and the more applied oriented and more recently emerging disciplines of discrete mathematics, optimization, and algorithmics.
The overall goal of the project is to obtain, with methods from fundamental mathematics, new effective tools to unravel the complexity of structures like graphs, networks, codes, knots, polynomials, and tensors, and to get a grip on such complex structures by new efficient characterizations, sharper bounds, and faster algorithms.
In the last few years, there have been several new developments where methods from representation theory, invariant theory, algebraic geometry, measure theory, functional analysis, and topology found new applications in discrete mathematics and optimization, both theoretically and algorithmically. Among the typical application areas are networks, coding, routing, timetabling, statistical and quantum physics, and computer science.
The project focuses in particular on:
A. Understanding partition functions with invariant theory and algebraic geometry
B. Graph limits, regularity, Hilbert spaces, and low rank approximation of polynomials
C. Reducing complexity in optimization by exploiting symmetry with representation theory
D. Reducing complexity in discrete optimization by homotopy and cohomology
These research modules are interconnected by themes like symmetry, regularity, and complexity, and by common methods from algebra, analysis, geometry, and topology."
Summary
"This proposal aims at strengthening the connections between more fundamentally oriented areas of mathematics like algebra, geometry, analysis, and topology, and the more applied oriented and more recently emerging disciplines of discrete mathematics, optimization, and algorithmics.
The overall goal of the project is to obtain, with methods from fundamental mathematics, new effective tools to unravel the complexity of structures like graphs, networks, codes, knots, polynomials, and tensors, and to get a grip on such complex structures by new efficient characterizations, sharper bounds, and faster algorithms.
In the last few years, there have been several new developments where methods from representation theory, invariant theory, algebraic geometry, measure theory, functional analysis, and topology found new applications in discrete mathematics and optimization, both theoretically and algorithmically. Among the typical application areas are networks, coding, routing, timetabling, statistical and quantum physics, and computer science.
The project focuses in particular on:
A. Understanding partition functions with invariant theory and algebraic geometry
B. Graph limits, regularity, Hilbert spaces, and low rank approximation of polynomials
C. Reducing complexity in optimization by exploiting symmetry with representation theory
D. Reducing complexity in discrete optimization by homotopy and cohomology
These research modules are interconnected by themes like symmetry, regularity, and complexity, and by common methods from algebra, analysis, geometry, and topology."
Max ERC Funding
2 001 598 €
Duration
Start date: 2014-01-01, End date: 2018-12-31
Project acronym AGESPACE
Project SPATIAL NAVIGATION – A UNIQUE WINDOW INTO MECHANISMS OF COGNITIVE AGEING
Researcher (PI) Thomas Wolbers
Host Institution (HI) DEUTSCHES ZENTRUM FUR NEURODEGENERATIVE ERKRANKUNGEN EV
Call Details Starting Grant (StG), SH4, ERC-2013-StG
Summary "By 2040, the European population aged over 60 will rise to 290 million, with those estimated to have dementia to 15.9 million. These dramatic demographic changes will pose huge challenges to health care systems, hence a detailed understanding of age-related cognitive and neurobiological changes is essential for helping elderly populations maintain independence. However, while existing research into cognitive ageing has carefully characterised developmental trajectories of functions such as memory and processing speed, one key cognitive ability that is particularly relevant to everyday functioning has received very little attention: In surveys, elderly people often report substantial declines in navigational abilities such as problems with finding one’s way in a novel environment. Such deficits severely restrict the mobility of elderly people and affect physical activity and social participation, but the underlying behavioural and neuronal mechanisms are poorly understood.
In this proposal, I will take a new approach to cognitive ageing that will bridge the gap between animal neurobiology and human cognitive neuroscience. With support from the ERC, I will create a team that will characterise the mechanisms mediating age-related changes in navigational processing in humans. The project will focus on three structures that perform key computations for spatial navigation, form a closely interconnected triadic network, and are particularly sensitive to the ageing process. Crucially, the team will employ an interdisciplinary methodological approach that combines mathematical modelling, brain imaging and innovative data analysis techniques with novel virtual environment technology, which allows for rigorous testing of predictions derived from animal findings. Finally, the proposal also incorporates a translational project aimed at improving spatial mnemonic functioning with a behavioural intervention, which provides a direct test of functional relevance and societal impact."
Summary
"By 2040, the European population aged over 60 will rise to 290 million, with those estimated to have dementia to 15.9 million. These dramatic demographic changes will pose huge challenges to health care systems, hence a detailed understanding of age-related cognitive and neurobiological changes is essential for helping elderly populations maintain independence. However, while existing research into cognitive ageing has carefully characterised developmental trajectories of functions such as memory and processing speed, one key cognitive ability that is particularly relevant to everyday functioning has received very little attention: In surveys, elderly people often report substantial declines in navigational abilities such as problems with finding one’s way in a novel environment. Such deficits severely restrict the mobility of elderly people and affect physical activity and social participation, but the underlying behavioural and neuronal mechanisms are poorly understood.
In this proposal, I will take a new approach to cognitive ageing that will bridge the gap between animal neurobiology and human cognitive neuroscience. With support from the ERC, I will create a team that will characterise the mechanisms mediating age-related changes in navigational processing in humans. The project will focus on three structures that perform key computations for spatial navigation, form a closely interconnected triadic network, and are particularly sensitive to the ageing process. Crucially, the team will employ an interdisciplinary methodological approach that combines mathematical modelling, brain imaging and innovative data analysis techniques with novel virtual environment technology, which allows for rigorous testing of predictions derived from animal findings. Finally, the proposal also incorporates a translational project aimed at improving spatial mnemonic functioning with a behavioural intervention, which provides a direct test of functional relevance and societal impact."
Max ERC Funding
1 318 990 €
Duration
Start date: 2014-01-01, End date: 2018-12-31
Project acronym AMSTAT
Project Problems at the Applied Mathematics-Statistics Interface
Researcher (PI) Andrew Stuart
Host Institution (HI) THE UNIVERSITY OF WARWICK
Call Details Advanced Grant (AdG), PE1, ERC-2008-AdG
Summary Applied mathematics is concerned with developing models with predictive capability, and with probing those models to obtain qualitative and quantitative insight into the phenomena being modelled. Statistics is data-driven and is aimed at the development of methodologies to optimize the information derived from data. The increasing complexity of phenomena that scientists and engineers wish to model, together with our increased ability to gather, store and interrogate data, mean that the subjects of applied mathematics and statistics are increasingly required to work in conjunction. This research proposal is concerned with a research program at the interface between these two disciplines, aimed at problems in differential equations where profusion of data and the sophisticated model combine to produce the mathematical problem of obtaining information from a probability measure on function space. Applications are far-reaching and include the atmospheric sciences, geophysics, chemistry, econometrics and signal processing. The objectives of the research are: (i) to create the systematic foundations for a range of problems at the applied mathematics and statistics interface which share the common mathematical structure underpinning the range of applications described above; (ii) to exploit this common mathematical structure to design effecient algorithms to sample probability measures on function space; (iii) to apply these algorithms to attack a range of significant problems arising in molecular dynamics and in the atmospheric sciences.
Summary
Applied mathematics is concerned with developing models with predictive capability, and with probing those models to obtain qualitative and quantitative insight into the phenomena being modelled. Statistics is data-driven and is aimed at the development of methodologies to optimize the information derived from data. The increasing complexity of phenomena that scientists and engineers wish to model, together with our increased ability to gather, store and interrogate data, mean that the subjects of applied mathematics and statistics are increasingly required to work in conjunction. This research proposal is concerned with a research program at the interface between these two disciplines, aimed at problems in differential equations where profusion of data and the sophisticated model combine to produce the mathematical problem of obtaining information from a probability measure on function space. Applications are far-reaching and include the atmospheric sciences, geophysics, chemistry, econometrics and signal processing. The objectives of the research are: (i) to create the systematic foundations for a range of problems at the applied mathematics and statistics interface which share the common mathematical structure underpinning the range of applications described above; (ii) to exploit this common mathematical structure to design effecient algorithms to sample probability measures on function space; (iii) to apply these algorithms to attack a range of significant problems arising in molecular dynamics and in the atmospheric sciences.
Max ERC Funding
1 693 501 €
Duration
Start date: 2008-12-01, End date: 2014-11-30
Project acronym ANTEGEFI
Project Analytic Techniques for Geometric and Functional Inequalities
Researcher (PI) Nicola Fusco
Host Institution (HI) UNIVERSITA DEGLI STUDI DI NAPOLI FEDERICO II
Call Details Advanced Grant (AdG), PE1, ERC-2008-AdG
Summary Isoperimetric and Sobolev inequalities are the best known examples of geometric-functional inequalities. In recent years the PI and collaborators have obtained new and sharp quantitative versions of these and other important related inequalities. These results have been obtained by the combined use of classical symmetrization methods, new tools coming from mass transportation theory, deep geometric measure tools and ad hoc symmetrizations. The objective of this project is to further develop thes techniques in order to get: sharp quantitative versions of Faber-Krahn inequality, Gaussian isoperimetric inequality, Brunn-Minkowski inequality, Poincaré and Sobolev logarithm inequalities; sharp decay rates for the quantitative Sobolev inequalities and Polya-Szegö inequality.
Summary
Isoperimetric and Sobolev inequalities are the best known examples of geometric-functional inequalities. In recent years the PI and collaborators have obtained new and sharp quantitative versions of these and other important related inequalities. These results have been obtained by the combined use of classical symmetrization methods, new tools coming from mass transportation theory, deep geometric measure tools and ad hoc symmetrizations. The objective of this project is to further develop thes techniques in order to get: sharp quantitative versions of Faber-Krahn inequality, Gaussian isoperimetric inequality, Brunn-Minkowski inequality, Poincaré and Sobolev logarithm inequalities; sharp decay rates for the quantitative Sobolev inequalities and Polya-Szegö inequality.
Max ERC Funding
600 000 €
Duration
Start date: 2009-01-01, End date: 2013-12-31
Project acronym AQSER
Project Automorphic q-series and their application
Researcher (PI) Kathrin Bringmann
Host Institution (HI) UNIVERSITAET ZU KOELN
Call Details Starting Grant (StG), PE1, ERC-2013-StG
Summary This proposal aims to unravel mysteries at the frontier of number theory and other areas of mathematics and physics. The main focus will be to understand and exploit “modularity” of q-hypergeometric series. “Modular forms are functions on the complex plane that are inordinately symmetric.” (Mazur) The motivation comes from the wide-reaching applications of modularity in combinatorics, percolation, Lie theory, and physics (black holes).
The interplay between automorphic forms, q-series, and other areas of mathematics and physics is often two-sided. On the one hand, the other areas provide interesting examples of automorphic objects and predict their behavior. Sometimes these even motivate new classes of automorphic objects which have not been previously studied. On the other hand, knowing that certain generating functions are modular gives one access to deep theoretical tools to prove results in other areas. “Mathematics is a language, and we need that language to understand the physics of our universe.”(Ooguri) Understanding this interplay has attracted attention of researchers from a variety of areas. However, proofs of modularity of q-hypergeometric series currently fall far short of a comprehensive theory to describe the interplay between them and automorphic forms. A recent conjecture of W. Nahm relates the modularity of such series to K-theory. In this proposal I aim to fill this gap and provide a better understanding of this interplay by building a general structural framework enveloping these q-series. For this I will employ new kinds of automorphic objects and embed the functions of interest into bigger families
A successful outcome of the proposed research will open further horizons and also answer open questions, even those in other areas which were not addressed in this proposal; for example the new theory could be applied to better understand Donaldson invariants.
Summary
This proposal aims to unravel mysteries at the frontier of number theory and other areas of mathematics and physics. The main focus will be to understand and exploit “modularity” of q-hypergeometric series. “Modular forms are functions on the complex plane that are inordinately symmetric.” (Mazur) The motivation comes from the wide-reaching applications of modularity in combinatorics, percolation, Lie theory, and physics (black holes).
The interplay between automorphic forms, q-series, and other areas of mathematics and physics is often two-sided. On the one hand, the other areas provide interesting examples of automorphic objects and predict their behavior. Sometimes these even motivate new classes of automorphic objects which have not been previously studied. On the other hand, knowing that certain generating functions are modular gives one access to deep theoretical tools to prove results in other areas. “Mathematics is a language, and we need that language to understand the physics of our universe.”(Ooguri) Understanding this interplay has attracted attention of researchers from a variety of areas. However, proofs of modularity of q-hypergeometric series currently fall far short of a comprehensive theory to describe the interplay between them and automorphic forms. A recent conjecture of W. Nahm relates the modularity of such series to K-theory. In this proposal I aim to fill this gap and provide a better understanding of this interplay by building a general structural framework enveloping these q-series. For this I will employ new kinds of automorphic objects and embed the functions of interest into bigger families
A successful outcome of the proposed research will open further horizons and also answer open questions, even those in other areas which were not addressed in this proposal; for example the new theory could be applied to better understand Donaldson invariants.
Max ERC Funding
1 240 500 €
Duration
Start date: 2014-01-01, End date: 2019-04-30
Project acronym astromnesis
Project The language of astrocytes: multilevel analysis to understand astrocyte communication and its role in memory-related brain operations and in cognitive behavior
Researcher (PI) Andrea Volterra
Host Institution (HI) UNIVERSITE DE LAUSANNE
Call Details Advanced Grant (AdG), LS5, ERC-2013-ADG
Summary In the 90s, two landmark observations brought to a paradigm shift about the role of astrocytes in brain function: 1) astrocytes respond to signals coming from other cells with transient Ca2+ elevations; 2) Ca2+ transients in astrocytes trigger release of neuroactive and vasoactive agents. Since then, many modulatory astrocytic actions and mechanisms were described, forming a complex - partly contradictory - picture, in which the exact roles and modes of astrocyte action remain ill defined. Our project wants to bring light into the “language of astrocytes”, i.e. into how they communicate with neurons and, ultimately, address their role in brain computations and cognitive behavior. To this end we will perform 4 complementary levels of analysis using highly innovative methodologies in order to obtain unprecedented results. We will study: 1) the subcellular organization of astrocytes underlying local microdomain communications by use of correlative light-electron microscopy; 2) the way individual astrocytes integrate inputs and control synaptic ensembles using 3D two-photon imaging, genetically-encoded Ca2+ indicators, optogenetics and electrophysiology; 3) the contribution of astrocyte ensembles to behavior-relevant circuit operations using miniaturized microscopes capturing neuronal/astrocytic population dynamics in freely-moving mice during memory tests; 4) the contribution of astrocytic signalling mechanisms to cognitive behavior using a set of new mouse lines with conditional, astrocyte-specific genetic modification of signalling pathways. We expect that this combination of groundbreaking ideas, innovative technologies and multilevel analysis makes our project highly attractive to the neuroscience community at large, bridging aspects of molecular, cellular, systems and behavioral neuroscience, with the goal of leading from a provocative hypothesis to the conclusive demonstration of whether and how “the language of astrocytes” participates in memory and cognition.
Summary
In the 90s, two landmark observations brought to a paradigm shift about the role of astrocytes in brain function: 1) astrocytes respond to signals coming from other cells with transient Ca2+ elevations; 2) Ca2+ transients in astrocytes trigger release of neuroactive and vasoactive agents. Since then, many modulatory astrocytic actions and mechanisms were described, forming a complex - partly contradictory - picture, in which the exact roles and modes of astrocyte action remain ill defined. Our project wants to bring light into the “language of astrocytes”, i.e. into how they communicate with neurons and, ultimately, address their role in brain computations and cognitive behavior. To this end we will perform 4 complementary levels of analysis using highly innovative methodologies in order to obtain unprecedented results. We will study: 1) the subcellular organization of astrocytes underlying local microdomain communications by use of correlative light-electron microscopy; 2) the way individual astrocytes integrate inputs and control synaptic ensembles using 3D two-photon imaging, genetically-encoded Ca2+ indicators, optogenetics and electrophysiology; 3) the contribution of astrocyte ensembles to behavior-relevant circuit operations using miniaturized microscopes capturing neuronal/astrocytic population dynamics in freely-moving mice during memory tests; 4) the contribution of astrocytic signalling mechanisms to cognitive behavior using a set of new mouse lines with conditional, astrocyte-specific genetic modification of signalling pathways. We expect that this combination of groundbreaking ideas, innovative technologies and multilevel analysis makes our project highly attractive to the neuroscience community at large, bridging aspects of molecular, cellular, systems and behavioral neuroscience, with the goal of leading from a provocative hypothesis to the conclusive demonstration of whether and how “the language of astrocytes” participates in memory and cognition.
Max ERC Funding
2 513 896 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym AttentionCircuits
Project Modulation of neocortical microcircuits for attention
Researcher (PI) Johannes Jakob Letzkus
Host Institution (HI) MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Call Details Starting Grant (StG), LS5, ERC-2013-StG
Summary At every moment in time, the brain receives a vast amount of sensory information about the environment. This makes attention, the process by which we select currently relevant stimuli for processing and ignore irrelevant input, a fundamentally important brain function. Studies in primates have yielded a detailed description of how attention to a stimulus modifies the responses of neuronal ensembles in visual cortex, but how this modulation is produced mechanistically in the circuit is not well understood. Neuronal circuits comprise a large variety of neuron types, and to gain mechanistic insights, and to treat specific diseases of the nervous system, it is crucial to characterize the contribution of different identified cell types to information processing. Inhibition supplied by a small yet highly diverse set of interneurons controls all aspects of cortical function, and the central hypothesis of this proposal is that differential modulation of genetically-defined interneuron types is a key mechanism of attention in visual cortex. To identify the interneuron types underlying attentional modulation and to investigate how this, in turn, affects computations in the circuit we will use an innovative multidisciplinary approach combining genetic targeting in mice with cutting-edge in vivo 2-photon microscopy-based recordings and selective optogenetic manipulation of activity. Importantly, a key set of experiments will test whether the observed neuronal mechanisms are causally involved in attention at the level of behavior, the ultimate readout of the computations we are interested in. The expected results will provide a detailed, mechanistic dissection of the neuronal basis of attention. Beyond attention, selection of different functional states of the same hard-wired circuit by modulatory input is a fundamental, but poorly understood, phenomenon in the brain, and we predict that our insights will elucidate similar mechanisms in other brain areas and functional contexts.
Summary
At every moment in time, the brain receives a vast amount of sensory information about the environment. This makes attention, the process by which we select currently relevant stimuli for processing and ignore irrelevant input, a fundamentally important brain function. Studies in primates have yielded a detailed description of how attention to a stimulus modifies the responses of neuronal ensembles in visual cortex, but how this modulation is produced mechanistically in the circuit is not well understood. Neuronal circuits comprise a large variety of neuron types, and to gain mechanistic insights, and to treat specific diseases of the nervous system, it is crucial to characterize the contribution of different identified cell types to information processing. Inhibition supplied by a small yet highly diverse set of interneurons controls all aspects of cortical function, and the central hypothesis of this proposal is that differential modulation of genetically-defined interneuron types is a key mechanism of attention in visual cortex. To identify the interneuron types underlying attentional modulation and to investigate how this, in turn, affects computations in the circuit we will use an innovative multidisciplinary approach combining genetic targeting in mice with cutting-edge in vivo 2-photon microscopy-based recordings and selective optogenetic manipulation of activity. Importantly, a key set of experiments will test whether the observed neuronal mechanisms are causally involved in attention at the level of behavior, the ultimate readout of the computations we are interested in. The expected results will provide a detailed, mechanistic dissection of the neuronal basis of attention. Beyond attention, selection of different functional states of the same hard-wired circuit by modulatory input is a fundamental, but poorly understood, phenomenon in the brain, and we predict that our insights will elucidate similar mechanisms in other brain areas and functional contexts.
Max ERC Funding
1 466 505 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
