Project acronym 19TH-CENTURY_EUCLID
Project Nineteenth-Century Euclid: Geometry and the Literary Imagination from Wordsworth to Wells
Researcher (PI) Alice Jenkins
Host Institution (HI) UNIVERSITY OF GLASGOW
Country United Kingdom
Call Details Starting Grant (StG), SH4, ERC-2007-StG
Summary This radically interdisciplinary project aims to bring a substantially new field of research – literature and mathematics studies – to prominence as a tool for investigating the culture of nineteenth-century Britain. It will result in three kinds of outcome: a monograph, two interdisciplinary and international colloquia, and a collection of essays. The project focuses on Euclidean geometry as a key element of nineteenth-century literary and scientific culture, showing that it was part of the shared knowledge flowing through elite and popular Romantic and Victorian writing, and figuring notably in the work of very many of the century’s best-known writers. Despite its traditional cultural prestige and educational centrality, geometry has been almost wholly neglected by literary history. This project shows how literature and mathematics studies can draw a new map of nineteenth-century British culture, revitalising our understanding of the Romantic and Victorian imagination through its writing about geometry.
Summary
This radically interdisciplinary project aims to bring a substantially new field of research – literature and mathematics studies – to prominence as a tool for investigating the culture of nineteenth-century Britain. It will result in three kinds of outcome: a monograph, two interdisciplinary and international colloquia, and a collection of essays. The project focuses on Euclidean geometry as a key element of nineteenth-century literary and scientific culture, showing that it was part of the shared knowledge flowing through elite and popular Romantic and Victorian writing, and figuring notably in the work of very many of the century’s best-known writers. Despite its traditional cultural prestige and educational centrality, geometry has been almost wholly neglected by literary history. This project shows how literature and mathematics studies can draw a new map of nineteenth-century British culture, revitalising our understanding of the Romantic and Victorian imagination through its writing about geometry.
Max ERC Funding
323 118 €
Duration
Start date: 2009-01-01, End date: 2011-10-31
Project acronym 2D4D
Project Disruptive Digitalization for Decarbonization
Researcher (PI) Elena Verdolini
Host Institution (HI) UNIVERSITA DEGLI STUDI DI BRESCIA
Country Italy
Call Details Starting Grant (StG), SH2, ERC-2019-STG
Summary By 2040, all major sectors of the European economy will be deeply digitalized. By then, the EU aims at reducing greenhouse gas emissions by 60% with respect to 1990 levels. Digitalization will affect decarbonization efforts because of its impacts on energy demand, employment, competitiveness, trade patterns and its distributional, behavioural and ethical implications. Yet, the policy debates around these two transformations are largely disjoint.
The aim of the 2D4D project is ensure that the digital revolution acts as an enabler – and not as a barrier – for decarbonization. The project quantifies the decarbonization implications of three disruptive digitalization technologies in hard-to-decarbonize sectors: (1) Additive Manufacturing in industry, (2) Mobility-as-a-Service in transportation, and (3) Artificial Intelligence in buildings.
The first objective of 2D4D is to generate a one-of-a-kind data collection to investigate the technical and socio-economic dynamics of these technologies, and how they may affect decarbonization narratives and scenarios. This will be achieved through several data collection methods, including desk research, surveys and expert elicitations.
The second objective of 2D4D is to include digitalization dynamics in decarbonization narratives and pathways. On the one hand, this entails enhancing decarbonization narratives (specifically, the Shared Socio-economic Pathways) to describe digitalization dynamics. On the other hand, it requires improving the representation of sector-specific digitalization dynamics in Integrated Assessment Models, one of the main tools available to generate decarbonization pathways.
The third objective of 2D4D is to identify no-regret, robust policy portfolios. These will be designed to ensure that digitalization unfolds in an inclusive, climate-beneficial way, and that decarbonization policies capitalize on digital technologies to support the energy transition.
Summary
By 2040, all major sectors of the European economy will be deeply digitalized. By then, the EU aims at reducing greenhouse gas emissions by 60% with respect to 1990 levels. Digitalization will affect decarbonization efforts because of its impacts on energy demand, employment, competitiveness, trade patterns and its distributional, behavioural and ethical implications. Yet, the policy debates around these two transformations are largely disjoint.
The aim of the 2D4D project is ensure that the digital revolution acts as an enabler – and not as a barrier – for decarbonization. The project quantifies the decarbonization implications of three disruptive digitalization technologies in hard-to-decarbonize sectors: (1) Additive Manufacturing in industry, (2) Mobility-as-a-Service in transportation, and (3) Artificial Intelligence in buildings.
The first objective of 2D4D is to generate a one-of-a-kind data collection to investigate the technical and socio-economic dynamics of these technologies, and how they may affect decarbonization narratives and scenarios. This will be achieved through several data collection methods, including desk research, surveys and expert elicitations.
The second objective of 2D4D is to include digitalization dynamics in decarbonization narratives and pathways. On the one hand, this entails enhancing decarbonization narratives (specifically, the Shared Socio-economic Pathways) to describe digitalization dynamics. On the other hand, it requires improving the representation of sector-specific digitalization dynamics in Integrated Assessment Models, one of the main tools available to generate decarbonization pathways.
The third objective of 2D4D is to identify no-regret, robust policy portfolios. These will be designed to ensure that digitalization unfolds in an inclusive, climate-beneficial way, and that decarbonization policies capitalize on digital technologies to support the energy transition.
Max ERC Funding
1 498 375 €
Duration
Start date: 2020-10-01, End date: 2025-09-30
Project acronym 3D-In-Macro
Project Inequality in 3D – measurement and implications for macroeconomic theory
Researcher (PI) Andreas Fagereng
Host Institution (HI) STIFTELSEN HANDELSHOYSKOLEN BI
Country Norway
Call Details Starting Grant (StG), SH1, ERC-2019-STG
Summary This project will contribute toward a better understanding of inequality and its macroeconomic implications. We will study inequality and its dynamics along three dimensions: Consumption, Income and Wealth, “3D Inequality.” With novel microdata we can measure the entirety of the economy down to the single household along the 3 dimensions.
In macroeconomics, much theoretical progress has been made in understanding when distributions matter for aggregates. Newer heterogeneous agent models deliver strikingly different implications for monetary and fiscal policies than what the traditional representative agent models do, and also allow us to study the distributional implications of different policies across households. In principle, this class of models can incorporate the potentially rich interactions between inequality and the macroeconomy: on the one hand, inequality shapes macroeconomic aggregates; on the other hand, macroeconomic shocks and policies affect inequality. However, absent precise micro-level facts it is difficult to establish which of the potential mechanisms highlighted by these models are the most important in reality.
Our empirical efforts will be disciplined by these recent developments in modelling macroeconomic phenomena with microeconomic heterogeneity. Our overarching motivation is to quantify the type of micro heterogeneity that matters for macroeconomic theory and thereby inform the development of current and future macroeconomic models. The novel insights we aim to provide could lead to substantial improvements in both fiscal and monetary policy tools. Furthermore, a better understanding of the forces behind growing inequality will inform the current debate on this issue and provide important lessons to policy makers who see economic inequality as a problem in itself.
Summary
This project will contribute toward a better understanding of inequality and its macroeconomic implications. We will study inequality and its dynamics along three dimensions: Consumption, Income and Wealth, “3D Inequality.” With novel microdata we can measure the entirety of the economy down to the single household along the 3 dimensions.
In macroeconomics, much theoretical progress has been made in understanding when distributions matter for aggregates. Newer heterogeneous agent models deliver strikingly different implications for monetary and fiscal policies than what the traditional representative agent models do, and also allow us to study the distributional implications of different policies across households. In principle, this class of models can incorporate the potentially rich interactions between inequality and the macroeconomy: on the one hand, inequality shapes macroeconomic aggregates; on the other hand, macroeconomic shocks and policies affect inequality. However, absent precise micro-level facts it is difficult to establish which of the potential mechanisms highlighted by these models are the most important in reality.
Our empirical efforts will be disciplined by these recent developments in modelling macroeconomic phenomena with microeconomic heterogeneity. Our overarching motivation is to quantify the type of micro heterogeneity that matters for macroeconomic theory and thereby inform the development of current and future macroeconomic models. The novel insights we aim to provide could lead to substantial improvements in both fiscal and monetary policy tools. Furthermore, a better understanding of the forces behind growing inequality will inform the current debate on this issue and provide important lessons to policy makers who see economic inequality as a problem in itself.
Max ERC Funding
1 376 875 €
Duration
Start date: 2020-05-01, End date: 2025-04-30
Project acronym ABACUS
Project Advancing Behavioral and Cognitive Understanding of Speech
Researcher (PI) Bart De Boer
Host Institution (HI) VRIJE UNIVERSITEIT BRUSSEL
Country Belgium
Call Details Starting Grant (StG), SH4, ERC-2011-StG_20101124
Summary I intend to investigate what cognitive mechanisms give us combinatorial speech. Combinatorial speech is the ability to make new words using pre-existing speech sounds. Humans are the only apes that can do this, yet we do not know how our brains do it, nor how exactly we differ from other apes. Using new experimental techniques to study human behavior and new computational techniques to model human cognition, I will find out how we deal with combinatorial speech.
The experimental part will study individual and cultural learning. Experimental cultural learning is a new technique that simulates cultural evolution in the laboratory. Two types of cultural learning will be used: iterated learning, which simulates language transfer across generations, and social coordination, which simulates emergence of norms in a language community. Using the two types of cultural learning together with individual learning experiments will help to zero in, from three angles, on how humans deal with combinatorial speech. In addition it will make a methodological contribution by comparing the strengths and weaknesses of the three methods.
The computer modeling part will formalize hypotheses about how our brains deal with combinatorial speech. Two models will be built: a high-level model that will establish the basic algorithms with which combinatorial speech is learned and reproduced, and a neural model that will establish in more detail how the algorithms are implemented in the brain. In addition, the models, through increasing understanding of how humans deal with speech, will help bridge the performance gap between human and computer speech recognition.
The project will advance science in four ways: it will provide insight into how our unique ability for using combinatorial speech works, it will tell us how this is implemented in the brain, it will extend the novel methodology of experimental cultural learning and it will create new computer models for dealing with human speech.
Summary
I intend to investigate what cognitive mechanisms give us combinatorial speech. Combinatorial speech is the ability to make new words using pre-existing speech sounds. Humans are the only apes that can do this, yet we do not know how our brains do it, nor how exactly we differ from other apes. Using new experimental techniques to study human behavior and new computational techniques to model human cognition, I will find out how we deal with combinatorial speech.
The experimental part will study individual and cultural learning. Experimental cultural learning is a new technique that simulates cultural evolution in the laboratory. Two types of cultural learning will be used: iterated learning, which simulates language transfer across generations, and social coordination, which simulates emergence of norms in a language community. Using the two types of cultural learning together with individual learning experiments will help to zero in, from three angles, on how humans deal with combinatorial speech. In addition it will make a methodological contribution by comparing the strengths and weaknesses of the three methods.
The computer modeling part will formalize hypotheses about how our brains deal with combinatorial speech. Two models will be built: a high-level model that will establish the basic algorithms with which combinatorial speech is learned and reproduced, and a neural model that will establish in more detail how the algorithms are implemented in the brain. In addition, the models, through increasing understanding of how humans deal with speech, will help bridge the performance gap between human and computer speech recognition.
The project will advance science in four ways: it will provide insight into how our unique ability for using combinatorial speech works, it will tell us how this is implemented in the brain, it will extend the novel methodology of experimental cultural learning and it will create new computer models for dealing with human speech.
Max ERC Funding
1 276 620 €
Duration
Start date: 2012-02-01, End date: 2017-01-31
Project acronym ABEP
Project Asset Bubbles and Economic Policy
Researcher (PI) Jaume Ventura Fontanet
Host Institution (HI) Centre de Recerca en Economia Internacional (CREI)
Country Spain
Call Details Advanced Grant (AdG), SH1, ERC-2009-AdG
Summary Advanced capitalist economies experience large and persistent movements in asset prices that are difficult to justify with economic fundamentals. The internet bubble of the 1990s and the real state market bubble of the 2000s are two recent examples. The predominant view is that these bubbles are a market failure, and are caused by some form of individual irrationality on the part of market participants. This project is based instead on the view that market participants are individually rational, although this does not preclude sometimes collectively sub-optimal outcomes. Bubbles are thus not a source of market failure by themselves but instead arise as a result of a pre-existing market failure, namely, the existence of pockets of dynamically inefficient investments. Under some conditions, bubbles partly solve this problem, increasing market efficiency and welfare. It is also possible however that bubbles do not solve the underlying problem and, in addition, create negative side-effects. The main objective of this project is to develop this view of asset bubbles, and produce an empirically-relevant macroeconomic framework that allows us to address the following questions: (i) What is the relationship between bubbles and financial market frictions? Special emphasis is given to how the globalization of financial markets and the development of new financial products affect the size and effects of bubbles. (ii) What is the relationship between bubbles, economic growth and unemployment? The theory suggests the presence of virtuous and vicious cycles, as economic growth creates the conditions for bubbles to pop up, while bubbles create incentives for economic growth to happen. (iii) What is the optimal policy to manage bubbles? We need to develop the tools that allow policy makers to sustain those bubbles that have positive effects and burst those that have negative effects.
Summary
Advanced capitalist economies experience large and persistent movements in asset prices that are difficult to justify with economic fundamentals. The internet bubble of the 1990s and the real state market bubble of the 2000s are two recent examples. The predominant view is that these bubbles are a market failure, and are caused by some form of individual irrationality on the part of market participants. This project is based instead on the view that market participants are individually rational, although this does not preclude sometimes collectively sub-optimal outcomes. Bubbles are thus not a source of market failure by themselves but instead arise as a result of a pre-existing market failure, namely, the existence of pockets of dynamically inefficient investments. Under some conditions, bubbles partly solve this problem, increasing market efficiency and welfare. It is also possible however that bubbles do not solve the underlying problem and, in addition, create negative side-effects. The main objective of this project is to develop this view of asset bubbles, and produce an empirically-relevant macroeconomic framework that allows us to address the following questions: (i) What is the relationship between bubbles and financial market frictions? Special emphasis is given to how the globalization of financial markets and the development of new financial products affect the size and effects of bubbles. (ii) What is the relationship between bubbles, economic growth and unemployment? The theory suggests the presence of virtuous and vicious cycles, as economic growth creates the conditions for bubbles to pop up, while bubbles create incentives for economic growth to happen. (iii) What is the optimal policy to manage bubbles? We need to develop the tools that allow policy makers to sustain those bubbles that have positive effects and burst those that have negative effects.
Max ERC Funding
1 000 000 €
Duration
Start date: 2010-04-01, End date: 2015-03-31
Project acronym ABRSEIST
Project Antibiotic Resistance: Socio-Economic Determinants and the Role of Information and Salience in Treatment Choice
Researcher (PI) Hannes ULLRICH
Host Institution (HI) DEUTSCHES INSTITUT FUR WIRTSCHAFTSFORSCHUNG DIW (INSTITUT FUR KONJUNKTURFORSCHUNG) EV
Country Germany
Call Details Starting Grant (StG), SH1, ERC-2018-STG
Summary Antibiotics have contributed to a tremendous increase in human well-being, saving many millions of lives. However, antibiotics become obsolete the more they are used as selection pressure promotes the development of resistant bacteria. The World Health Organization has proclaimed antibiotic resistance as a major global threat to public health. Today, 700,000 deaths per year are due to untreatable infections. To win the battle against antibiotic resistance, new policies affecting the supply and demand of existing and new drugs must be designed. I propose new research to identify and evaluate feasible and effective demand-side policy interventions targeting the relevant decision makers: physicians and patients. ABRSEIST will make use of a broad econometric toolset to identify mechanisms linking antibiotic resistance and consumption exploiting a unique combination of physician-patient-level antibiotic resistance, treatment, and socio-economic data. Using machine learning methods adapted for causal inference, theory-driven structural econometric analysis, and randomization in the field it will provide rigorous evidence on effective intervention designs. This research will improve our understanding of how prescribing, resistance, and the effect of antibiotic use on resistance, are distributed in the general population which has important implications for the design of targeted interventions. It will then estimate a structural model of general practitioners’ acquisition and use of information under uncertainty about resistance in prescription choice, allowing counterfactual analysis of information-improving policies such as mandatory diagnostic testing. The large-scale and structural econometric analyses allow flexible identification of physician heterogeneity, which ABRSEIST will exploit to design and evaluate targeted, randomized information nudges in the field. The result will be improved rational use and a toolset applicable in contexts of antibiotic prescribing.
Summary
Antibiotics have contributed to a tremendous increase in human well-being, saving many millions of lives. However, antibiotics become obsolete the more they are used as selection pressure promotes the development of resistant bacteria. The World Health Organization has proclaimed antibiotic resistance as a major global threat to public health. Today, 700,000 deaths per year are due to untreatable infections. To win the battle against antibiotic resistance, new policies affecting the supply and demand of existing and new drugs must be designed. I propose new research to identify and evaluate feasible and effective demand-side policy interventions targeting the relevant decision makers: physicians and patients. ABRSEIST will make use of a broad econometric toolset to identify mechanisms linking antibiotic resistance and consumption exploiting a unique combination of physician-patient-level antibiotic resistance, treatment, and socio-economic data. Using machine learning methods adapted for causal inference, theory-driven structural econometric analysis, and randomization in the field it will provide rigorous evidence on effective intervention designs. This research will improve our understanding of how prescribing, resistance, and the effect of antibiotic use on resistance, are distributed in the general population which has important implications for the design of targeted interventions. It will then estimate a structural model of general practitioners’ acquisition and use of information under uncertainty about resistance in prescription choice, allowing counterfactual analysis of information-improving policies such as mandatory diagnostic testing. The large-scale and structural econometric analyses allow flexible identification of physician heterogeneity, which ABRSEIST will exploit to design and evaluate targeted, randomized information nudges in the field. The result will be improved rational use and a toolset applicable in contexts of antibiotic prescribing.
Max ERC Funding
1 498 920 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym ACAP
Project Acency Costs and Asset Pricing
Researcher (PI) Thomas Mariotti
Host Institution (HI) FONDATION JEAN JACQUES LAFFONT,TOULOUSE SCIENCES ECONOMIQUES
Country France
Call Details Starting Grant (StG), SH1, ERC-2007-StG
Summary The main objective of this research project is to contribute at bridging the gap between the two main branches of financial theory, namely corporate finance and asset pricing. It is motivated by the conviction that these two aspects of financial activity should and can be analyzed within a unified framework. This research will borrow from these two approaches in order to construct theoretical models that allow one to analyze the design and issuance of financial securities, as well as the dynamics of their valuations. Unlike asset pricing, which takes as given the price of the fundamentals, the goal is to derive security price processes from a precise description of firm’s operations and internal frictions. Regarding the latter, and in line with traditional corporate finance theory, the analysis will emphasize the role of agency costs within the firm for the design of its securities. But the analysis will be pushed one step further by studying the impact of these agency costs on key financial variables such as stock and bond prices, leverage, book-to-market ratios, default risk, or the holding of liquidities by firms. One of the contributions of this research project is to show how these variables are interrelated when firms and investors agree upon optimal financial arrangements. The final objective is to derive a rich set of testable asset pricing implications that would eventually be brought to the data.
Summary
The main objective of this research project is to contribute at bridging the gap between the two main branches of financial theory, namely corporate finance and asset pricing. It is motivated by the conviction that these two aspects of financial activity should and can be analyzed within a unified framework. This research will borrow from these two approaches in order to construct theoretical models that allow one to analyze the design and issuance of financial securities, as well as the dynamics of their valuations. Unlike asset pricing, which takes as given the price of the fundamentals, the goal is to derive security price processes from a precise description of firm’s operations and internal frictions. Regarding the latter, and in line with traditional corporate finance theory, the analysis will emphasize the role of agency costs within the firm for the design of its securities. But the analysis will be pushed one step further by studying the impact of these agency costs on key financial variables such as stock and bond prices, leverage, book-to-market ratios, default risk, or the holding of liquidities by firms. One of the contributions of this research project is to show how these variables are interrelated when firms and investors agree upon optimal financial arrangements. The final objective is to derive a rich set of testable asset pricing implications that would eventually be brought to the data.
Max ERC Funding
1 000 000 €
Duration
Start date: 2008-11-01, End date: 2014-10-31
Project acronym ACCUPOL
Project Unlimited Growth? A Comparative Analysis of Causes and Consequences of Policy Accumulation
Researcher (PI) Christoph KNILL
Host Institution (HI) LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN
Country Germany
Call Details Advanced Grant (AdG), SH2, ERC-2017-ADG
Summary ACCUPOL systematically analyzes an intuitively well-known, but curiously under-researched phenomenon: policy accumulation. Societal modernization and progress bring about a continuously growing pile of policies in most political systems. At the same time, however, the administrative capacities for implementation are largely stagnant. While being societally desirable in principle, ever-more policies hence may potentially imply less in terms of policy achievements. Whether or not policy accumulation remains at a ‘sustainable’ rate thus crucially affects the long-term output legitimacy of modern democracies.
Given this development, the central focus of ACCUPOL lies on three questions: Do accumulation rates vary across countries and policy sectors? Which factors mitigate policy accumulation? And to what extent is policy accumulation really associated with an increasing prevalence of implementation deficits? In answering these questions, ACCUPOL radically departs from established research traditions in public policy.
First, the project develops new analytical concepts: Rather than relying on individual policy change as the unit of analysis, we consider policy accumulation to assess the growth of policy portfolios over time. In terms of implementation, ACCUPOL takes into account the overall prevalence of implementation deficits in a given sector instead of analyzing the effectiveness of individual implementation processes.
Second, this analytical innovation also implies a paradigmatic theoretical shift. Because existing theories focus on the analysis of individual policies, they are of limited help to understand causes and consequences of policy accumulation. ACCUPOL develops a novel theoretical approach to fill this theoretical gap.
Third, the project provides new empirical evidence on the prevalence of policy accumulation and implementation deficits focusing on 25 OECD countries and two key policy areas (social and environmental policy).
Summary
ACCUPOL systematically analyzes an intuitively well-known, but curiously under-researched phenomenon: policy accumulation. Societal modernization and progress bring about a continuously growing pile of policies in most political systems. At the same time, however, the administrative capacities for implementation are largely stagnant. While being societally desirable in principle, ever-more policies hence may potentially imply less in terms of policy achievements. Whether or not policy accumulation remains at a ‘sustainable’ rate thus crucially affects the long-term output legitimacy of modern democracies.
Given this development, the central focus of ACCUPOL lies on three questions: Do accumulation rates vary across countries and policy sectors? Which factors mitigate policy accumulation? And to what extent is policy accumulation really associated with an increasing prevalence of implementation deficits? In answering these questions, ACCUPOL radically departs from established research traditions in public policy.
First, the project develops new analytical concepts: Rather than relying on individual policy change as the unit of analysis, we consider policy accumulation to assess the growth of policy portfolios over time. In terms of implementation, ACCUPOL takes into account the overall prevalence of implementation deficits in a given sector instead of analyzing the effectiveness of individual implementation processes.
Second, this analytical innovation also implies a paradigmatic theoretical shift. Because existing theories focus on the analysis of individual policies, they are of limited help to understand causes and consequences of policy accumulation. ACCUPOL develops a novel theoretical approach to fill this theoretical gap.
Third, the project provides new empirical evidence on the prevalence of policy accumulation and implementation deficits focusing on 25 OECD countries and two key policy areas (social and environmental policy).
Max ERC Funding
2 359 000 €
Duration
Start date: 2018-10-01, End date: 2023-09-30
Project acronym ACQDIV
Project Acquisition processes in maximally diverse languages: Min(d)ing the ambient language
Researcher (PI) Sabine Erika Stoll
Host Institution (HI) University of Zurich
Country Switzerland
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 ActionContraThreat
Project Action selection under threat: the complex control of human defense
Researcher (PI) Dominik BACH
Host Institution (HI) UNIVERSITY COLLEGE LONDON
Country United Kingdom
Call Details Consolidator Grant (CoG), SH4, ERC-2018-COG
Summary Run away, sidestep, duck-and-cover, watch: when under threat, humans immediately choreograph a large repertoire of defensive actions. Understanding action-selection under threat is important for anybody wanting to explain why anxiety disorders imply some of these behaviours in harmless situations. Current concepts of human defensive behaviour are largely derived from rodent research and focus on a small number of broad, cross-species, action tendencies. This is likely to underestimate the complexity of the underlying action-selection mechanisms. This research programme will take decisive steps to understand these psychological mechanisms and elucidate their neural implementation.
To elicit threat-related action in the laboratory, I will use virtual reality computer games with full body motion, and track actions with motion-capture technology. Based on a cognitive-computational framework, I will systematically characterise the space of actions under threat, investigate the psychological mechanisms by which actions are selected in different scenarios, and describe them with computational algorithms that allow quantitative predictions. To independently verify their neural implementation, I will use wearable magnetoencephalography (MEG) in freely moving subjects.
This proposal fills a lacuna between defence system concepts based on rodent research, emotion psychology, and clinical accounts of anxiety disorders. By combining a stringent experimental approach with the formalism of cognitive-computational psychology, it furnishes a unique opportunity to understand the mechanisms of action-selection under threat, and how these are distinct from more general-purpose action-selection systems. Beyond its immediate scope, the proposal has a potential to lead to a better understanding of anxiety disorders, and to pave the way towards improved diagnostics and therapies.
Summary
Run away, sidestep, duck-and-cover, watch: when under threat, humans immediately choreograph a large repertoire of defensive actions. Understanding action-selection under threat is important for anybody wanting to explain why anxiety disorders imply some of these behaviours in harmless situations. Current concepts of human defensive behaviour are largely derived from rodent research and focus on a small number of broad, cross-species, action tendencies. This is likely to underestimate the complexity of the underlying action-selection mechanisms. This research programme will take decisive steps to understand these psychological mechanisms and elucidate their neural implementation.
To elicit threat-related action in the laboratory, I will use virtual reality computer games with full body motion, and track actions with motion-capture technology. Based on a cognitive-computational framework, I will systematically characterise the space of actions under threat, investigate the psychological mechanisms by which actions are selected in different scenarios, and describe them with computational algorithms that allow quantitative predictions. To independently verify their neural implementation, I will use wearable magnetoencephalography (MEG) in freely moving subjects.
This proposal fills a lacuna between defence system concepts based on rodent research, emotion psychology, and clinical accounts of anxiety disorders. By combining a stringent experimental approach with the formalism of cognitive-computational psychology, it furnishes a unique opportunity to understand the mechanisms of action-selection under threat, and how these are distinct from more general-purpose action-selection systems. Beyond its immediate scope, the proposal has a potential to lead to a better understanding of anxiety disorders, and to pave the way towards improved diagnostics and therapies.
Max ERC Funding
1 998 750 €
Duration
Start date: 2019-10-01, End date: 2024-09-30
