Project acronym AGENSI
Project A Genetic View into Past Sea Ice Variability in the Arctic
Researcher (PI) Stijn DE SCHEPPER
Host Institution (HI) NORCE NORWEGIAN RESEARCH CENTRE AS
Call Details Consolidator Grant (CoG), PE10, ERC-2018-COG
Summary Arctic sea ice decline is the exponent of the rapidly transforming Arctic climate. The ensuing local and global implications can be understood by studying past climate transitions, yet few methods are available to examine past Arctic sea ice cover, severely restricting our understanding of sea ice in the climate system. The decline in Arctic sea ice cover is a ‘canary in the coalmine’ for the state of our climate, and if greenhouse gas emissions remain unchecked, summer sea ice loss may pass a critical threshold that could drastically transform the Arctic. Because historical observations are limited, it is crucial to have reliable proxies for assessing natural sea ice variability, its stability and sensitivity to climate forcing on different time scales. Current proxies address aspects of sea ice variability, but are limited due to a selective fossil record, preservation effects, regional applicability, or being semi-quantitative. With such restraints on our knowledge about natural variations and drivers, major uncertainties about the future remain.
I propose to develop and apply a novel sea ice proxy that exploits genetic information stored in marine sediments, sedimentary ancient DNA (sedaDNA). This innovation uses the genetic signature of phytoplankton communities from surface waters and sea ice as it gets stored in sediments. This wealth of information has not been explored before for reconstructing sea ice conditions. Preliminary results from my cross-disciplinary team indicate that our unconventional approach can provide a detailed, qualitative account of past sea ice ecosystems and quantitative estimates of sea ice parameters. I will address fundamental questions about past Arctic sea ice variability on different timescales, information essential to provide a framework upon which to assess the ecological and socio-economic consequences of a changing Arctic. This new proxy is not limited to sea ice research and can transform the field of paleoceanography.
Summary
Arctic sea ice decline is the exponent of the rapidly transforming Arctic climate. The ensuing local and global implications can be understood by studying past climate transitions, yet few methods are available to examine past Arctic sea ice cover, severely restricting our understanding of sea ice in the climate system. The decline in Arctic sea ice cover is a ‘canary in the coalmine’ for the state of our climate, and if greenhouse gas emissions remain unchecked, summer sea ice loss may pass a critical threshold that could drastically transform the Arctic. Because historical observations are limited, it is crucial to have reliable proxies for assessing natural sea ice variability, its stability and sensitivity to climate forcing on different time scales. Current proxies address aspects of sea ice variability, but are limited due to a selective fossil record, preservation effects, regional applicability, or being semi-quantitative. With such restraints on our knowledge about natural variations and drivers, major uncertainties about the future remain.
I propose to develop and apply a novel sea ice proxy that exploits genetic information stored in marine sediments, sedimentary ancient DNA (sedaDNA). This innovation uses the genetic signature of phytoplankton communities from surface waters and sea ice as it gets stored in sediments. This wealth of information has not been explored before for reconstructing sea ice conditions. Preliminary results from my cross-disciplinary team indicate that our unconventional approach can provide a detailed, qualitative account of past sea ice ecosystems and quantitative estimates of sea ice parameters. I will address fundamental questions about past Arctic sea ice variability on different timescales, information essential to provide a framework upon which to assess the ecological and socio-economic consequences of a changing Arctic. This new proxy is not limited to sea ice research and can transform the field of paleoceanography.
Max ERC Funding
2 615 858 €
Duration
Start date: 2019-08-01, End date: 2024-07-31
Project acronym BrainNanoFlow
Project Nanoscale dynamics in the extracellular space of the brain in vivo
Researcher (PI) Juan Alberto VARELA
Host Institution (HI) THE UNIVERSITY COURT OF THE UNIVERSITY OF ST ANDREWS
Call Details Starting Grant (StG), LS5, ERC-2018-STG
Summary Aggregates of proteins such as amyloid-beta and alpha-synuclein circulate the extracellular space of the brain (ECS) and are thought to be key players in the development of neurodegenerative diseases. The clearance of these aggregates (among other toxic metabolites) is a fundamental physiological feature of the brain which is poorly understood due to the lack of techniques to study the nanoscale organisation of the ECS. Exciting advances in this field have recently shown that clearance is enhanced during sleep due to a major volume change in the ECS, facilitating the flow of the interstitial fluid. However, this process has only been characterised at a low spatial resolution while the physiological changes occur at the nanoscale. The recently proposed “glymphatic” pathway still remains controversial, as there are no techniques capable of distinguishing between diffusion and bulk flow in the ECS of living animals. Understanding these processes at a higher spatial resolution requires the development of single-molecule imaging techniques that can study the brain in living animals. Taking advantage of the strategies I have recently developed to target single-molecules in the brain in vivo with nanoparticles, we will do “nanoscopy” in living animals. Our proposal will test the glymphatic pathway at the spatial scale in which events happen, and explore how sleep and wake cycles alter the ECS and the diffusion of receptors in neuronal plasma membrane. Overall, BrainNanoFlow aims to understand how nanoscale changes in the ECS facilitate clearance of protein aggregates. We will also provide new insights to the pathological consequences of impaired clearance, focusing on the interactions between these aggregates and their putative receptors. Being able to perform single-molecule studies in vivo in the brain will be a major breakthrough in neurobiology, making possible the study of physiological and pathological processes that cannot be studied in simpler brain preparations.
Summary
Aggregates of proteins such as amyloid-beta and alpha-synuclein circulate the extracellular space of the brain (ECS) and are thought to be key players in the development of neurodegenerative diseases. The clearance of these aggregates (among other toxic metabolites) is a fundamental physiological feature of the brain which is poorly understood due to the lack of techniques to study the nanoscale organisation of the ECS. Exciting advances in this field have recently shown that clearance is enhanced during sleep due to a major volume change in the ECS, facilitating the flow of the interstitial fluid. However, this process has only been characterised at a low spatial resolution while the physiological changes occur at the nanoscale. The recently proposed “glymphatic” pathway still remains controversial, as there are no techniques capable of distinguishing between diffusion and bulk flow in the ECS of living animals. Understanding these processes at a higher spatial resolution requires the development of single-molecule imaging techniques that can study the brain in living animals. Taking advantage of the strategies I have recently developed to target single-molecules in the brain in vivo with nanoparticles, we will do “nanoscopy” in living animals. Our proposal will test the glymphatic pathway at the spatial scale in which events happen, and explore how sleep and wake cycles alter the ECS and the diffusion of receptors in neuronal plasma membrane. Overall, BrainNanoFlow aims to understand how nanoscale changes in the ECS facilitate clearance of protein aggregates. We will also provide new insights to the pathological consequences of impaired clearance, focusing on the interactions between these aggregates and their putative receptors. Being able to perform single-molecule studies in vivo in the brain will be a major breakthrough in neurobiology, making possible the study of physiological and pathological processes that cannot be studied in simpler brain preparations.
Max ERC Funding
1 552 948 €
Duration
Start date: 2018-12-01, End date: 2023-11-30
Project acronym DEEPTIME
Project Probing the history of matter in deep time
Researcher (PI) Martin BIZZARRO
Host Institution (HI) KOBENHAVNS UNIVERSITET
Call Details Advanced Grant (AdG), PE10, ERC-2018-ADG
Summary The solar system represents the archetype for the formation of rocky planets and habitable worlds. A full understanding of its formation and earliest evolution is thus one of the most fundamental goals in natural sciences. The only tangible record of the formative stages of the solar system comes from ancient meteorites and their components some of which date back to the to the birth of our Sun. The main objective of this proposal is to investigate the timescales and processes leading to the formation of the solar system, including the delivery of volatile elements to the accretion regions of rocky planets, by combining absolute ages, isotopic and trace element compositions as well as atomic and structural analysis of meteorites and their components. We identify nucleosynthetic fingerprinting as a tool allowing us to probe the history of solids parental to our solar system across cosmic times, namely from their parent stars in the Galaxy through their modification and incorporation into disk objects, including asteroidal bodies and planets. Our data will be obtained using state-of-the-art instruments including mass-spectrometers (MC-ICPMS, TIMS, SIMS), atom probe and transmission electron microscopy. These data will allow us to: (1) provide formation timescales for presolar grains and their parent stars as well as understand how these grains may control the solar system’s nucleosynthetic variability, (2) track the formation timescales of disk reservoirs and the mass fluxes between and within these regions (3) better our understanding of the timing and flux of volatile elements to the inner protoplanetary disk as well as the timescales and mechanism of primordial crust formation in rocky planets. The novel questions outlined in this proposal, including high-risk high-gain ventures, can only now be tackled using pioneering methods and approaches developed by the PI’s group and collaborators. Thus, we are in a unique position to make step-change discoveries.
Summary
The solar system represents the archetype for the formation of rocky planets and habitable worlds. A full understanding of its formation and earliest evolution is thus one of the most fundamental goals in natural sciences. The only tangible record of the formative stages of the solar system comes from ancient meteorites and their components some of which date back to the to the birth of our Sun. The main objective of this proposal is to investigate the timescales and processes leading to the formation of the solar system, including the delivery of volatile elements to the accretion regions of rocky planets, by combining absolute ages, isotopic and trace element compositions as well as atomic and structural analysis of meteorites and their components. We identify nucleosynthetic fingerprinting as a tool allowing us to probe the history of solids parental to our solar system across cosmic times, namely from their parent stars in the Galaxy through their modification and incorporation into disk objects, including asteroidal bodies and planets. Our data will be obtained using state-of-the-art instruments including mass-spectrometers (MC-ICPMS, TIMS, SIMS), atom probe and transmission electron microscopy. These data will allow us to: (1) provide formation timescales for presolar grains and their parent stars as well as understand how these grains may control the solar system’s nucleosynthetic variability, (2) track the formation timescales of disk reservoirs and the mass fluxes between and within these regions (3) better our understanding of the timing and flux of volatile elements to the inner protoplanetary disk as well as the timescales and mechanism of primordial crust formation in rocky planets. The novel questions outlined in this proposal, including high-risk high-gain ventures, can only now be tackled using pioneering methods and approaches developed by the PI’s group and collaborators. Thus, we are in a unique position to make step-change discoveries.
Max ERC Funding
2 495 496 €
Duration
Start date: 2020-01-01, End date: 2024-12-31
Project acronym DEVORHBIOSHIP
Project The Developmental Origins of Health: Biology, Shocks, Investments, and Policies
Researcher (PI) Gabriella CONTI
Host Institution (HI) UNIVERSITY COLLEGE LONDON
Call Details Consolidator Grant (CoG), SH1, ERC-2018-COG
Summary What are the origins of inequalities in health? A recent literature in economics has established causal impacts of early life shocks, investments and policies on lifelong health. However, several unknowns remain. The mechanisms through which shocks, investments, and policies interact are just beginning to be understood. Our knowledge of sensitive periods is imprecise. Little is also known about the impact of shocks and policies across different ages. Commonly used health capital measures, such as birth weight, lack sensitivity and specificity. The interplay between genes and environments in the formation of health inequalities is poorly understood.
To fill these gaps, I will build on insights from my earlier work, and use a combination of high-quality data, more sensitive measures, robust identification strategies and richer models to untangle the complex interactions between biology, shocks, investments and policies.
First, I will investigate causal impacts and mechanisms of two public health policies on child health and development: medical treatments for pregnancy complications and prenatal home visiting programmes. Second, I will examine the effects of two environmental shocks (pollution and influenza) on the formation of early health and human capital, and their interplay with maternal investments in nutrition. Third, I will study interactions between shocks, investments and policies from birth to adulthood, to understand the dynamic interplay between SES and health. Throughout, I will explore their interactions with genetic susceptibility or potential.
I will analyse administrative records, registries linked to survey data, cohort data with biomarkers; and a randomized controlled trial. I will use state-of-the-art econometric techniques for observational and experimental data. My findings will have direct policy implications and will help understand whether and to which extent early life interventions are a cost-effective mean to promote health.
Summary
What are the origins of inequalities in health? A recent literature in economics has established causal impacts of early life shocks, investments and policies on lifelong health. However, several unknowns remain. The mechanisms through which shocks, investments, and policies interact are just beginning to be understood. Our knowledge of sensitive periods is imprecise. Little is also known about the impact of shocks and policies across different ages. Commonly used health capital measures, such as birth weight, lack sensitivity and specificity. The interplay between genes and environments in the formation of health inequalities is poorly understood.
To fill these gaps, I will build on insights from my earlier work, and use a combination of high-quality data, more sensitive measures, robust identification strategies and richer models to untangle the complex interactions between biology, shocks, investments and policies.
First, I will investigate causal impacts and mechanisms of two public health policies on child health and development: medical treatments for pregnancy complications and prenatal home visiting programmes. Second, I will examine the effects of two environmental shocks (pollution and influenza) on the formation of early health and human capital, and their interplay with maternal investments in nutrition. Third, I will study interactions between shocks, investments and policies from birth to adulthood, to understand the dynamic interplay between SES and health. Throughout, I will explore their interactions with genetic susceptibility or potential.
I will analyse administrative records, registries linked to survey data, cohort data with biomarkers; and a randomized controlled trial. I will use state-of-the-art econometric techniques for observational and experimental data. My findings will have direct policy implications and will help understand whether and to which extent early life interventions are a cost-effective mean to promote health.
Max ERC Funding
1 738 763 €
Duration
Start date: 2019-04-01, End date: 2024-03-31
Project acronym DYNNET
Project Opinion Dynamics
Researcher (PI) Friederike MENGEL
Host Institution (HI) UNIVERSITY OF ESSEX
Call Details Starting Grant (StG), SH1, ERC-2018-STG
Summary In this project I propose to study opinion dynamics in social networks and groups. In particular, I will ask how opinion dynamics contribute to shape social identity and how, conversely, social identity affects communication. I also ask whether and when social identity is a barrier to communication, when “opinion bubbles” are created and when and how “fake news” can spread. The types of social identity I consider include social class, ethnicity and gender. The project consists of four subprojects.
The first subproject [A] focuses on communication between social classes and inequality. The subproject asks how opinion dynamics contribute to diverging experiences, core behaviours and values that go much beyond income inequality. I will first document this divergence by conducting experiments in a representative sample of the UK population via the UK Household panel and then conduct lab experiments to study opinion dynamics and the conditions under which “opinion bubbles” arise in more detail.
Subproject [B] focuses on gender bias in committees. A large body of empirical evidence has documented gender biases in decisions, such as hiring, promotion, or performance evaluations. Many of these decisions involve communication and deliberation among committee members. Nevertheless the role of opinion dynamics in committees in creating or amplifying gender bias has not been explored. Subproject [B] aims to fill this gap.
Subproject [C] will focus on how perceived uncertainty contributes to the spread of discriminatory attitudes with a particular focus on ethnic discrimination. Subproject [C] will be conducted both using a representative sample of the UK population via the Innovation Panel of Understanding Society, the UK Household panel as well as lab experiments.
The last subproject [D] will use lab experiments to study under which conditions opinion dynamics can become vulnerable to “fake news”.
Summary
In this project I propose to study opinion dynamics in social networks and groups. In particular, I will ask how opinion dynamics contribute to shape social identity and how, conversely, social identity affects communication. I also ask whether and when social identity is a barrier to communication, when “opinion bubbles” are created and when and how “fake news” can spread. The types of social identity I consider include social class, ethnicity and gender. The project consists of four subprojects.
The first subproject [A] focuses on communication between social classes and inequality. The subproject asks how opinion dynamics contribute to diverging experiences, core behaviours and values that go much beyond income inequality. I will first document this divergence by conducting experiments in a representative sample of the UK population via the UK Household panel and then conduct lab experiments to study opinion dynamics and the conditions under which “opinion bubbles” arise in more detail.
Subproject [B] focuses on gender bias in committees. A large body of empirical evidence has documented gender biases in decisions, such as hiring, promotion, or performance evaluations. Many of these decisions involve communication and deliberation among committee members. Nevertheless the role of opinion dynamics in committees in creating or amplifying gender bias has not been explored. Subproject [B] aims to fill this gap.
Subproject [C] will focus on how perceived uncertainty contributes to the spread of discriminatory attitudes with a particular focus on ethnic discrimination. Subproject [C] will be conducted both using a representative sample of the UK population via the Innovation Panel of Understanding Society, the UK Household panel as well as lab experiments.
The last subproject [D] will use lab experiments to study under which conditions opinion dynamics can become vulnerable to “fake news”.
Max ERC Funding
830 623 €
Duration
Start date: 2018-12-01, End date: 2022-11-30
Project acronym EvolutioNeuroCircuit
Project Cellular and genetic bases of neural circuits evolution
Researcher (PI) Lucia PRIETO GODINO
Host Institution (HI) THE FRANCIS CRICK INSTITUTE LIMITED
Call Details Starting Grant (StG), LS5, ERC-2018-STG
Summary Sensory systems encode the world around us to produce context-dependent appropriate behaviours. However, we know little about the way new sensory evoked behaviours arise as neural circuits are re-shaped during evolution. Tackling this question requires a deep understanding of the circuits underlying specific behaviours and integration of this knowledge with tools from other fields, including evolutionary and developmental biology. Recent technological advancements on neural circuit interrogation and genome editing have put progress on this fundamental biological question within reach.
The olfactory system of the larval stage of the fly Drosophila melanogaster and related species is an ideal model for investigating these questions because (i) D. melanogaster has pioneered both the fields of population genetics and neurogenetics and (ii) its olfactory system is one of the best-characterised neural circuits. We will address the question of how olfactory circuits evolve by studying four species with divergent odour-guided behaviours through the following multidisciplinary aims:
1. Which olfactory pathways are targeted in the evolution of ecological specialisation? – Combining high-throughput behavioural assays, optogenetics and calcium imaging in the larva of all four species we will determine whether/which olfactory pathways have switched valences or sensitivity.
2. How have central neural circuits diverged? – We will address this question at unprecedented resolution through whole-brain calcium imaging and serial electron microscopy reconstruction.
3. What are the molecular and genetic bases of neural circuits rewiring during evolution? – Using transcriptomic profiling we will identify differentially expressed genes in conserved and divergent circuits across species, and functionally probe selected candidates to establish causality.
4. How do evolutionary forces shape olfactory circuits? – We will investigate this question using field studies and population genetics
Summary
Sensory systems encode the world around us to produce context-dependent appropriate behaviours. However, we know little about the way new sensory evoked behaviours arise as neural circuits are re-shaped during evolution. Tackling this question requires a deep understanding of the circuits underlying specific behaviours and integration of this knowledge with tools from other fields, including evolutionary and developmental biology. Recent technological advancements on neural circuit interrogation and genome editing have put progress on this fundamental biological question within reach.
The olfactory system of the larval stage of the fly Drosophila melanogaster and related species is an ideal model for investigating these questions because (i) D. melanogaster has pioneered both the fields of population genetics and neurogenetics and (ii) its olfactory system is one of the best-characterised neural circuits. We will address the question of how olfactory circuits evolve by studying four species with divergent odour-guided behaviours through the following multidisciplinary aims:
1. Which olfactory pathways are targeted in the evolution of ecological specialisation? – Combining high-throughput behavioural assays, optogenetics and calcium imaging in the larva of all four species we will determine whether/which olfactory pathways have switched valences or sensitivity.
2. How have central neural circuits diverged? – We will address this question at unprecedented resolution through whole-brain calcium imaging and serial electron microscopy reconstruction.
3. What are the molecular and genetic bases of neural circuits rewiring during evolution? – Using transcriptomic profiling we will identify differentially expressed genes in conserved and divergent circuits across species, and functionally probe selected candidates to establish causality.
4. How do evolutionary forces shape olfactory circuits? – We will investigate this question using field studies and population genetics
Max ERC Funding
1 312 500 €
Duration
Start date: 2019-03-01, End date: 2024-02-29
Project acronym FirmIneq
Project Wage inequality within and across firms: The role of market forces, government and firm policies
Researcher (PI) Uta SCHOENBERG
Host Institution (HI) UNIVERSITY COLLEGE LONDON
Call Details Consolidator Grant (CoG), SH1, ERC-2018-COG
Summary Wage inequality in industrialised countries has increased sharply over the past decades, and much of this increase has occurred between rather than within firms. Furthermore, substantial inequality between men and women persists in all industrialised countries, and a large part of the gender gaps observed today is attributable to the arrival of children. In this proposal, we put firms at the centre of the analysis and ask the following questions: First, which market forces can (partly) explain the increasing wage inequality between firms? Second, how do government policies alter the wage structure? And third, how do firm policies and the firm environment impact on gender inequality? All projects draw on four decades of German social security records comprising the near universe of workers and establishments, which we augment with survey and administrative data on firms. In Project A, we investigate how two important market forces, increased product market competition and routine-biased technological change, contributed to the increasing wage inequality between firms, by changing which firms operate in the market (selection) and how employment is distributed across low and high productivity firms (reallocation), and by differentially affecting wage growth across firm types (differential wage growth). In Project B, we study how two prominent government policies, the introduction of a minimum wage and changes in business tax rates, affect wage dispersion between firms through selection, reallocation and differential growth effects. In Project C, we first analyse whether firm provided family-friendly policies, most notably flexible working times and child care facilities, can be effective at reducing gender inequality. We then investigate how the firm environment, specifically the presence of co-workers who are likely to have a working mother and hold more egalitarian gender attitudes, shapes mothers’ return-to-work decisions and earnings trajectories after childbirth.
Summary
Wage inequality in industrialised countries has increased sharply over the past decades, and much of this increase has occurred between rather than within firms. Furthermore, substantial inequality between men and women persists in all industrialised countries, and a large part of the gender gaps observed today is attributable to the arrival of children. In this proposal, we put firms at the centre of the analysis and ask the following questions: First, which market forces can (partly) explain the increasing wage inequality between firms? Second, how do government policies alter the wage structure? And third, how do firm policies and the firm environment impact on gender inequality? All projects draw on four decades of German social security records comprising the near universe of workers and establishments, which we augment with survey and administrative data on firms. In Project A, we investigate how two important market forces, increased product market competition and routine-biased technological change, contributed to the increasing wage inequality between firms, by changing which firms operate in the market (selection) and how employment is distributed across low and high productivity firms (reallocation), and by differentially affecting wage growth across firm types (differential wage growth). In Project B, we study how two prominent government policies, the introduction of a minimum wage and changes in business tax rates, affect wage dispersion between firms through selection, reallocation and differential growth effects. In Project C, we first analyse whether firm provided family-friendly policies, most notably flexible working times and child care facilities, can be effective at reducing gender inequality. We then investigate how the firm environment, specifically the presence of co-workers who are likely to have a working mother and hold more egalitarian gender attitudes, shapes mothers’ return-to-work decisions and earnings trajectories after childbirth.
Max ERC Funding
1 491 803 €
Duration
Start date: 2019-06-01, End date: 2024-05-31
Project acronym iGLURs - A NEW VIEW
Project Exposing nature’s view of ligand recognition in ionotropic glutamate receptors
Researcher (PI) Timothy Peter Lynagh
Host Institution (HI) UNIVERSITETET I BERGEN
Call Details Starting Grant (StG), LS5, ERC-2018-STG
Summary Molecular biology strives for the prediction of function, based on the genetic code. Within neuroscience, this is reflected in the intense study of the molecular basis for ligand recognition by neurotransmitter receptors. Consequently, structural and functional studies have rendered a profoundly high-resolution view of ionotropic glutamate receptors (iGluRs), the archetypal excitatory receptor in the brain. But even this view is obsolete: we don’t know why some receptors recognize glutamate yet others recognize other ligands; and we have been unable to functionally test the underlying chemical interactions. In other words, our view differs substantially from nature’s own view of ligand recognition. I plan to lead a workgroup attacking this problem on three fronts. First, bioinformatic identification and electrophysiological characterization of a broad and representative sample of iGluRs from across the spectrum of life will unveil the diversity of ligand recognition in iGluRs. Second, phylogenetic analyses combined with functional experiments will reveal the molecular changes that nature employed in arriving at existing means of ligand recognition in iGluRs. Finally, chemical-scale mutagenesis will be employed to overcome previous technical limitations and dissect the precise chemical interactions that determine the specific recognition of certain ligands. With my experience in combining phylogenetics and functional experiments and in the use of chemical-scale mutagenesis, the objectives are within reach. Together, they form a unique approach that will expose nature’s own view of ligand recognition in iGluRs, revealing the molecular blueprint for protein function in the nervous system.
Summary
Molecular biology strives for the prediction of function, based on the genetic code. Within neuroscience, this is reflected in the intense study of the molecular basis for ligand recognition by neurotransmitter receptors. Consequently, structural and functional studies have rendered a profoundly high-resolution view of ionotropic glutamate receptors (iGluRs), the archetypal excitatory receptor in the brain. But even this view is obsolete: we don’t know why some receptors recognize glutamate yet others recognize other ligands; and we have been unable to functionally test the underlying chemical interactions. In other words, our view differs substantially from nature’s own view of ligand recognition. I plan to lead a workgroup attacking this problem on three fronts. First, bioinformatic identification and electrophysiological characterization of a broad and representative sample of iGluRs from across the spectrum of life will unveil the diversity of ligand recognition in iGluRs. Second, phylogenetic analyses combined with functional experiments will reveal the molecular changes that nature employed in arriving at existing means of ligand recognition in iGluRs. Finally, chemical-scale mutagenesis will be employed to overcome previous technical limitations and dissect the precise chemical interactions that determine the specific recognition of certain ligands. With my experience in combining phylogenetics and functional experiments and in the use of chemical-scale mutagenesis, the objectives are within reach. Together, they form a unique approach that will expose nature’s own view of ligand recognition in iGluRs, revealing the molecular blueprint for protein function in the nervous system.
Max ERC Funding
1 500 000 €
Duration
Start date: 2019-03-01, End date: 2024-02-29
Project acronym INSTRUCT
Project Information structures in consumer markets
Researcher (PI) Mark Armstrong
Host Institution (HI) THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Call Details Advanced Grant (AdG), SH1, ERC-2018-ADG
Summary Information flows are fundamental to how well markets work for consumers and firms. Consumers get different deals depending on (a) how much they know about the offerings of different firms and, conversely, (b) how much firms know about consumer preferences. The internet is transforming both (a) and (b), allowing consuInformation flows are fundamental to how well markets work for consumers and firms. Consumers get different deals depending on (a) how much they know about the offerings of different firms and, conversely, (b) how much firms know about consumer preferences. The internet is transforming both (a) and (b), allowing consumers to discover and evaluate products with greater ease and enabling firms to personalise prices and target their advertising. Economic understanding currently lags behind what is needed for robust policy formulation in the areas of consumer privacy, price discrimination, and the costs of search and advertising. This project aims to fill that gap.
How does the structure of information in consumer markets affect market performance, and which kinds of information should be stimulated or controlled? I propose four lines of enquiry to address this over-arching theme: (1) to develop innovative modeling techniques to understand how the structure of information about consumer preferences (possessed by firms and by consumers themselves) affects overall surplus and how that surplus is divided between firms and consumers; (2) to develop methods to study how the structure of consideration sets (i.e., the set of firms a consumer is able or willing to consider for her purchase) affects market outcomes; (3) to analyse how the information channels of advertising by firms and search by consumers interact and which is more important for the efficient functioning of markets, and (4) to investigate which aspects of their preferences consumers are willing to share with firms and thereby understand better how to solve difficult but important pricing problems.
Summary
Information flows are fundamental to how well markets work for consumers and firms. Consumers get different deals depending on (a) how much they know about the offerings of different firms and, conversely, (b) how much firms know about consumer preferences. The internet is transforming both (a) and (b), allowing consuInformation flows are fundamental to how well markets work for consumers and firms. Consumers get different deals depending on (a) how much they know about the offerings of different firms and, conversely, (b) how much firms know about consumer preferences. The internet is transforming both (a) and (b), allowing consumers to discover and evaluate products with greater ease and enabling firms to personalise prices and target their advertising. Economic understanding currently lags behind what is needed for robust policy formulation in the areas of consumer privacy, price discrimination, and the costs of search and advertising. This project aims to fill that gap.
How does the structure of information in consumer markets affect market performance, and which kinds of information should be stimulated or controlled? I propose four lines of enquiry to address this over-arching theme: (1) to develop innovative modeling techniques to understand how the structure of information about consumer preferences (possessed by firms and by consumers themselves) affects overall surplus and how that surplus is divided between firms and consumers; (2) to develop methods to study how the structure of consideration sets (i.e., the set of firms a consumer is able or willing to consider for her purchase) affects market outcomes; (3) to analyse how the information channels of advertising by firms and search by consumers interact and which is more important for the efficient functioning of markets, and (4) to investigate which aspects of their preferences consumers are willing to share with firms and thereby understand better how to solve difficult but important pricing problems.
Max ERC Funding
1 221 744 €
Duration
Start date: 2019-09-01, End date: 2023-08-31
Project acronym LeaRNN
Project Principles of Learning in a Recurrent Neural Network
Researcher (PI) Marta Zlatic
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
Call Details Consolidator Grant (CoG), LS5, ERC-2018-COG
Summary Forming memories, generating predictions based on memories, and updating memories when predictions no longer match actual experience are fundamental brain functions. Dopaminergic neurons provide a so-called “teaching signal” that drives the formation and updates of associative memories across the animal kingdom. Many theoretical models propose how neural circuits could compute the teaching signals, but the actual implementation of this computation in real nervous systems is unknown.
This project will discover the basic principles by which neural circuits compute the teaching signals that drive memory formation and updates using a tractable insect model system, the Drosophila larva. We will generate, for the first time in any animal, the following essential datasets for a distributed, multilayered, recurrent learning circuit, the mushroom body-related circuitry in the larval brain. First, building on our preliminary work that provides the synaptic-resolution connectome of the circuit, including all feedforward and feedback pathways upstream of all dopaminergic neurons, we will generate a map of functional monosynaptic connections. Second, we will obtain cellular-resolution whole-nervous system activity maps in intact living animals, as they form, extinguish, or consolidate memories to discover the features represented in each layer of the circuit (e.g. predictions, actual reinforcement, and prediction errors), the learning algorithms, and the candidate circuit motifs that implement them. Finally, we will develop a model of the circuit constrained by these datasets and test the predictions about the necessity and sufficiency of uniquely identified circuit elements for implementing learning algorithms by selectively manipulating their activity.
Understanding the basic functional principles of an entire multilayered recurrent learning circuit in an animal has the potential to revolutionize, not only neuroscience and medicine, but also machine-learning and robotics.
Summary
Forming memories, generating predictions based on memories, and updating memories when predictions no longer match actual experience are fundamental brain functions. Dopaminergic neurons provide a so-called “teaching signal” that drives the formation and updates of associative memories across the animal kingdom. Many theoretical models propose how neural circuits could compute the teaching signals, but the actual implementation of this computation in real nervous systems is unknown.
This project will discover the basic principles by which neural circuits compute the teaching signals that drive memory formation and updates using a tractable insect model system, the Drosophila larva. We will generate, for the first time in any animal, the following essential datasets for a distributed, multilayered, recurrent learning circuit, the mushroom body-related circuitry in the larval brain. First, building on our preliminary work that provides the synaptic-resolution connectome of the circuit, including all feedforward and feedback pathways upstream of all dopaminergic neurons, we will generate a map of functional monosynaptic connections. Second, we will obtain cellular-resolution whole-nervous system activity maps in intact living animals, as they form, extinguish, or consolidate memories to discover the features represented in each layer of the circuit (e.g. predictions, actual reinforcement, and prediction errors), the learning algorithms, and the candidate circuit motifs that implement them. Finally, we will develop a model of the circuit constrained by these datasets and test the predictions about the necessity and sufficiency of uniquely identified circuit elements for implementing learning algorithms by selectively manipulating their activity.
Understanding the basic functional principles of an entire multilayered recurrent learning circuit in an animal has the potential to revolutionize, not only neuroscience and medicine, but also machine-learning and robotics.
Max ERC Funding
2 350 000 €
Duration
Start date: 2019-09-01, End date: 2024-08-31