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 APMPAL
Project Asset Prices and Macro Policy when Agents Learn
Researcher (PI) Albert Marcet Torrens
Host Institution (HI) FUNDACIÓ MARKETS, ORGANIZATIONS AND VOTES IN ECONOMICS
Country Spain
Call Details Advanced Grant (AdG), SH1, ERC-2012-ADG_20120411
Summary "A conventional assumption in dynamic models is that agents form their expectations in a very sophisticated manner. In particular, that they have Rational Expectations (RE). We develop some tools to relax this assumption while retaining fully optimal behaviour by agents. We study implications for asset pricing and macro policy.
We assume that agents have a consistent set of beliefs that is close, but not equal, to RE. Agents are ""Internally Rational"", that is, they behave rationally given their system of beliefs. Thus, it is conceptually a small deviation from RE. It provides microfoundations for models of adaptive learning, since the learning algorithm is determined by agents’ optimal behaviour. In previous work we have shown that this framework can match stock price and housing price fluctuations, and that policy implications are quite different.
In this project we intend to: i) develop further the foundations of internally rational (IR) learning, ii) apply this to explain observed asset price price behavior, such as stock prices, bond prices, inflation, commodity derivatives, and exchange rates, iii) extend the IR framework to the case when agents entertain various models, iv) optimal policy under IR learning and under private information when some hidden shocks are not revealed ex-post. Along the way we will address policy issues such as: effects of creating derivative markets, sovereign spread as a signal of sovereign default risk, tests of fiscal sustainability, fiscal policy when agents learn, monetary policy (more specifically, QE measures and interest rate policy), and the role of credibility in macro policy."
Summary
"A conventional assumption in dynamic models is that agents form their expectations in a very sophisticated manner. In particular, that they have Rational Expectations (RE). We develop some tools to relax this assumption while retaining fully optimal behaviour by agents. We study implications for asset pricing and macro policy.
We assume that agents have a consistent set of beliefs that is close, but not equal, to RE. Agents are ""Internally Rational"", that is, they behave rationally given their system of beliefs. Thus, it is conceptually a small deviation from RE. It provides microfoundations for models of adaptive learning, since the learning algorithm is determined by agents’ optimal behaviour. In previous work we have shown that this framework can match stock price and housing price fluctuations, and that policy implications are quite different.
In this project we intend to: i) develop further the foundations of internally rational (IR) learning, ii) apply this to explain observed asset price price behavior, such as stock prices, bond prices, inflation, commodity derivatives, and exchange rates, iii) extend the IR framework to the case when agents entertain various models, iv) optimal policy under IR learning and under private information when some hidden shocks are not revealed ex-post. Along the way we will address policy issues such as: effects of creating derivative markets, sovereign spread as a signal of sovereign default risk, tests of fiscal sustainability, fiscal policy when agents learn, monetary policy (more specifically, QE measures and interest rate policy), and the role of credibility in macro policy."
Max ERC Funding
1 970 260 €
Duration
Start date: 2013-06-01, End date: 2018-08-31
Project acronym BABYRHYTHM
Project Oscillatory Rhythmic Entrainment and the Foundations of Language Acquisition
Researcher (PI) Usha Claire GOSWAMI
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE
Country United Kingdom
Call Details Advanced Grant (AdG), SH4, ERC-2015-AdG
Summary Half of “late talkers”, infants who are not yet speaking by 2 years of age, will go on to develop language impairments. Currently, we have no reliable means of identifying these infants. Here we combine our developmental approach to phonology (psycholinguistic grain size theory), to the neural mechanisms underlying speech encoding (temporal sampling [TS] theory) and our work on the developmental importance of the speech amplitude envelope (AE) to open a new research front in the foundations of language acquisition. Recent adult research confirms our decade-long focus on the importance of sensitivity to AE ‘rise time’ in children’s language development, showing that rise times (‘auditory edges’) re-set the endogenous cortical oscillations that encode speech. Accordingly, we now apply our in-house state-of-the-art methods for measuring oscillatory rhythmic entrainment in children along with our recent theoretical and behavioural advances concerning AE processing to infant studies. Our core aim is to use the TS theoretical perspective and analysis methods to generate robust early neural and behavioural markers of phonological and morphological development: TS for infants. We have published the first-ever studies of oscillatory entrainment to speech rhythm by children and we have developed methods for technically-challenging EEG speech envelope reconstruction. We now apply these innovative methods to infant language learning and infant-directed speech. Using our cutting-edge EEG methods, we will deliver a novel and innovative road map for charting early language acquisition from a rhythmic entrainment perspective. Our recent 5-year study of rise time sensitivity in infants confirms the feasibility of a TS approach. As our focus is on prosody, syllable stress and syllable processing, our methods will apply across European languages.
Summary
Half of “late talkers”, infants who are not yet speaking by 2 years of age, will go on to develop language impairments. Currently, we have no reliable means of identifying these infants. Here we combine our developmental approach to phonology (psycholinguistic grain size theory), to the neural mechanisms underlying speech encoding (temporal sampling [TS] theory) and our work on the developmental importance of the speech amplitude envelope (AE) to open a new research front in the foundations of language acquisition. Recent adult research confirms our decade-long focus on the importance of sensitivity to AE ‘rise time’ in children’s language development, showing that rise times (‘auditory edges’) re-set the endogenous cortical oscillations that encode speech. Accordingly, we now apply our in-house state-of-the-art methods for measuring oscillatory rhythmic entrainment in children along with our recent theoretical and behavioural advances concerning AE processing to infant studies. Our core aim is to use the TS theoretical perspective and analysis methods to generate robust early neural and behavioural markers of phonological and morphological development: TS for infants. We have published the first-ever studies of oscillatory entrainment to speech rhythm by children and we have developed methods for technically-challenging EEG speech envelope reconstruction. We now apply these innovative methods to infant language learning and infant-directed speech. Using our cutting-edge EEG methods, we will deliver a novel and innovative road map for charting early language acquisition from a rhythmic entrainment perspective. Our recent 5-year study of rise time sensitivity in infants confirms the feasibility of a TS approach. As our focus is on prosody, syllable stress and syllable processing, our methods will apply across European languages.
Max ERC Funding
2 614 275 €
Duration
Start date: 2016-09-01, End date: 2022-08-31
Project acronym BAYNET
Project Bayesian Networks and Non-Rational Expectations
Researcher (PI) Ran SPIEGLER
Host Institution (HI) UNIVERSITY COLLEGE LONDON
Country United Kingdom
Call Details Advanced Grant (AdG), SH1, ERC-2015-AdG
Summary "This project will develop a new framework for modeling economic agents having ""boundedly rational expectations"" (BRE). It is based on the concept of Bayesian networks (more generally, graphical models), borrowed from statistics and AI. In the framework's basic version, an agent is characterized by a directed acyclic graph (DAG) over the set of all relevant random variables. The DAG is the agent's ""type"" – it represents how he systematically distorts any objective probability distribution into a subjective belief. Technically, the distortion takes the form of the standard Bayesian-network factorization formula given by the agent's DAG. The agent's choice is modeled as a ""personal equilibrium"", because his subjective belief regarding the implications of his actions can vary with his own long-run behavior. The DAG representation unifies and simplifies existing models of BRE, subsuming them as special cases corresponding to distinct graphical representations. It captures hitherto-unmodeled fallacies such as reverse causation. The framework facilitates behavioral characterizations of general classes of models of BRE and expands their applicability. I will demonstrate this with applications to monetary policy, behavioral I.O., asset pricing, etc. I will extend the basic formalism to multi-agent environments, addressing issues beyond the reach of current models of BRE (e.g., formalizing the notion of ""high-order"" limited understanding of statistical regularities). Finally, I will seek a learning foundation for the graphical representation of BRE, in the sense that it will capture how the agent extrapolates his belief from a dataset (drawn from the objective distribution) containing ""missing values"", via some intuitive ""imputation method"". This part, too, borrows ideas from statistics and AI, further demonstrating the project's interdisciplinary nature."
Summary
"This project will develop a new framework for modeling economic agents having ""boundedly rational expectations"" (BRE). It is based on the concept of Bayesian networks (more generally, graphical models), borrowed from statistics and AI. In the framework's basic version, an agent is characterized by a directed acyclic graph (DAG) over the set of all relevant random variables. The DAG is the agent's ""type"" – it represents how he systematically distorts any objective probability distribution into a subjective belief. Technically, the distortion takes the form of the standard Bayesian-network factorization formula given by the agent's DAG. The agent's choice is modeled as a ""personal equilibrium"", because his subjective belief regarding the implications of his actions can vary with his own long-run behavior. The DAG representation unifies and simplifies existing models of BRE, subsuming them as special cases corresponding to distinct graphical representations. It captures hitherto-unmodeled fallacies such as reverse causation. The framework facilitates behavioral characterizations of general classes of models of BRE and expands their applicability. I will demonstrate this with applications to monetary policy, behavioral I.O., asset pricing, etc. I will extend the basic formalism to multi-agent environments, addressing issues beyond the reach of current models of BRE (e.g., formalizing the notion of ""high-order"" limited understanding of statistical regularities). Finally, I will seek a learning foundation for the graphical representation of BRE, in the sense that it will capture how the agent extrapolates his belief from a dataset (drawn from the objective distribution) containing ""missing values"", via some intuitive ""imputation method"". This part, too, borrows ideas from statistics and AI, further demonstrating the project's interdisciplinary nature."
Max ERC Funding
1 379 288 €
Duration
Start date: 2016-07-01, End date: 2021-06-30
Project acronym BILITERACY
Project Bi-literacy: Learning to read in L1 and in L2
Researcher (PI) Manuel Francisco Carreiras Valina
Host Institution (HI) BCBL BASQUE CENTER ON COGNITION BRAIN AND LANGUAGE
Country Spain
Call Details Advanced Grant (AdG), SH4, ERC-2011-ADG_20110406
Summary Learning to read is probably one of the most exciting discoveries in our life. Using a longitudinal approach, the research proposed examines how the human brain responds to two major challenges: (a) the instantiation a complex cognitive function for which there is no genetic blueprint (learning to read in a first language, L1), and (b) the accommodation to new statistical regularities when learning to read in a second language (L2). The aim of the present research project is to identify the neural substrates of the reading process and its constituent cognitive components, with specific attention to individual differences and reading disabilities; as well as to investigate the relationship between specific cognitive functions and the changes in neural activity that take place in the course of learning to read in L1 and in L2. The project will employ a longitudinal design. We will recruit children before they learn to read in L1 and in L2 and track reading development with both cognitive and neuroimaging measures over 24 months. The findings from this project will provide a deeper understanding of (a) how general neurocognitive factors and language specific factors underlie individual differences – and reading disabilities– in reading acquisition in L1 and in L2; (b) how the neuro-cognitive circuitry changes and brain mechanisms synchronize while instantiating reading in L1 and in L2; (c) what the limitations and the extent of brain plasticity are in young readers. An interdisciplinary and multi-methodological approach is one of the keys to success of the present project, along with strong theory-driven investigation. By combining both we will generate breakthroughs to advance our understanding of how literacy in L1 and in L2 is acquired and mastered. The research proposed will also lay the foundations for more applied investigations of best practice in teaching reading in first and subsequent languages, and devising intervention methods for reading disabilities.
Summary
Learning to read is probably one of the most exciting discoveries in our life. Using a longitudinal approach, the research proposed examines how the human brain responds to two major challenges: (a) the instantiation a complex cognitive function for which there is no genetic blueprint (learning to read in a first language, L1), and (b) the accommodation to new statistical regularities when learning to read in a second language (L2). The aim of the present research project is to identify the neural substrates of the reading process and its constituent cognitive components, with specific attention to individual differences and reading disabilities; as well as to investigate the relationship between specific cognitive functions and the changes in neural activity that take place in the course of learning to read in L1 and in L2. The project will employ a longitudinal design. We will recruit children before they learn to read in L1 and in L2 and track reading development with both cognitive and neuroimaging measures over 24 months. The findings from this project will provide a deeper understanding of (a) how general neurocognitive factors and language specific factors underlie individual differences – and reading disabilities– in reading acquisition in L1 and in L2; (b) how the neuro-cognitive circuitry changes and brain mechanisms synchronize while instantiating reading in L1 and in L2; (c) what the limitations and the extent of brain plasticity are in young readers. An interdisciplinary and multi-methodological approach is one of the keys to success of the present project, along with strong theory-driven investigation. By combining both we will generate breakthroughs to advance our understanding of how literacy in L1 and in L2 is acquired and mastered. The research proposed will also lay the foundations for more applied investigations of best practice in teaching reading in first and subsequent languages, and devising intervention methods for reading disabilities.
Max ERC Funding
2 487 000 €
Duration
Start date: 2012-05-01, End date: 2017-04-30
Project acronym BRAIN2MIND_NEUROCOMP
Project Developing and delivering neurocomputational models to bridge between brain and mind.
Researcher (PI) Matthew Lambon Ralph
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE
Country United Kingdom
Call Details Advanced Grant (AdG), SH4, ERC-2014-ADG
Summary The promise of cognitive neuroscience is truly exciting – to link mind and brain in order to reveal the neural basis of higher cognitive functions. This is crucial, scientifically, if we are to understand the nature of mental processes and how they arise from neural machinery but also, clinically, if we are to establish the basis of neurological patients’ impairments, their clinical management and treatment. Cognitive-clinical neuroscience depends on three ingredients: (a) investigating complex mental behaviours and the underlying cognitive processes; (b) mapping neural systems and their function; and (c) methods and tools that can bridge the gap between brain and mental behaviour. Experimental psychology and behavioural neurology has delivered the first component. In vivo neuroimaging and other allied technologies allow us to probe and map neural systems, their connectivity and neurobiological responses. The principal aim of this ERC Advanced grant is to secure, for the first time, the crucial third ingredient – the methods and tools for bridging systematically between cognitive science and systems neuroscience.
The grant will be based on two main activities: (i) convergence of methods – instead of employing each neuroscience and cognitive method independently, they will be planned and executed simultaneously to force a convergence of results; and (ii) development of a new type of neurocomputational model - to provide a novel formalism for bridging between brain and cognition. Computational models are used in cognitive science to mimic normal and impaired behaviour. Such models also have an as-yet untapped potential to connect neuroanatomy and cognition: latent in every model is a kind of brain-mind duality – each model is based on a computational architecture which generates behaviour. We will retain the ability to simulate detailed cognitive behaviour but simultaneously make the models’ architecture reflect systems-level neuroanatomy and function.
Summary
The promise of cognitive neuroscience is truly exciting – to link mind and brain in order to reveal the neural basis of higher cognitive functions. This is crucial, scientifically, if we are to understand the nature of mental processes and how they arise from neural machinery but also, clinically, if we are to establish the basis of neurological patients’ impairments, their clinical management and treatment. Cognitive-clinical neuroscience depends on three ingredients: (a) investigating complex mental behaviours and the underlying cognitive processes; (b) mapping neural systems and their function; and (c) methods and tools that can bridge the gap between brain and mental behaviour. Experimental psychology and behavioural neurology has delivered the first component. In vivo neuroimaging and other allied technologies allow us to probe and map neural systems, their connectivity and neurobiological responses. The principal aim of this ERC Advanced grant is to secure, for the first time, the crucial third ingredient – the methods and tools for bridging systematically between cognitive science and systems neuroscience.
The grant will be based on two main activities: (i) convergence of methods – instead of employing each neuroscience and cognitive method independently, they will be planned and executed simultaneously to force a convergence of results; and (ii) development of a new type of neurocomputational model - to provide a novel formalism for bridging between brain and cognition. Computational models are used in cognitive science to mimic normal and impaired behaviour. Such models also have an as-yet untapped potential to connect neuroanatomy and cognition: latent in every model is a kind of brain-mind duality – each model is based on a computational architecture which generates behaviour. We will retain the ability to simulate detailed cognitive behaviour but simultaneously make the models’ architecture reflect systems-level neuroanatomy and function.
Max ERC Funding
2 294 781 €
Duration
Start date: 2016-01-01, End date: 2021-12-31
Project acronym BRAINPOWER
Project Brain energy supply and the consequences of its failure
Researcher (PI) David Ian Attwell
Host Institution (HI) University College London
Country United Kingdom
Call Details Advanced Grant (AdG), LS5, ERC-2009-AdG
Summary Energy, supplied in the form of oxygen and glucose in the blood, is essential for the brain s cognitive power. Failure of the energy supply to the nervous system underlies the mental and physical disability occurring in a wide range of economically important neurological disorders, such as stroke, spinal cord injury and cerebral palsy. Using a combination of two-photon imaging, electrophysiological, molecular and transgenic approaches, I will investigate the control of brain energy supply at the vascular level, and at the level of individual neurons and glial cells, and study the deleterious consequences for the neurons, glia and vasculature of a failure of brain energy supply. The work will focus on the following fundamental issues: A. Vascular control of the brain energy supply (1) How important is control of energy supply at the capillary level, by pericytes? (2) Which synapses control blood flow (and thus generate functional imaging signals) in the cortex? B. Neuronal and glial control of brain energy supply (3) How is grey matter neuronal activity powered? (4) How is the white matter supplied with energy? C. The pathological consequences of a loss of brain energy supply (5) How does a fall of energy supply cause neurotoxic glutamate release? (6) How similar are events in the grey and white matter in energy deprivation conditions? (7) How does a transient loss of energy supply affect blood flow regulation? (8) How does brain energy use change after a period without energy supply? Together this work will significantly advance our understanding of how the energy supply to neurons and glia is regulated in normal conditions, and how the loss of the energy supply causes disorders which consume more than 5% of the costs of European health services (5% of ~1000 billion euro/year).
Summary
Energy, supplied in the form of oxygen and glucose in the blood, is essential for the brain s cognitive power. Failure of the energy supply to the nervous system underlies the mental and physical disability occurring in a wide range of economically important neurological disorders, such as stroke, spinal cord injury and cerebral palsy. Using a combination of two-photon imaging, electrophysiological, molecular and transgenic approaches, I will investigate the control of brain energy supply at the vascular level, and at the level of individual neurons and glial cells, and study the deleterious consequences for the neurons, glia and vasculature of a failure of brain energy supply. The work will focus on the following fundamental issues: A. Vascular control of the brain energy supply (1) How important is control of energy supply at the capillary level, by pericytes? (2) Which synapses control blood flow (and thus generate functional imaging signals) in the cortex? B. Neuronal and glial control of brain energy supply (3) How is grey matter neuronal activity powered? (4) How is the white matter supplied with energy? C. The pathological consequences of a loss of brain energy supply (5) How does a fall of energy supply cause neurotoxic glutamate release? (6) How similar are events in the grey and white matter in energy deprivation conditions? (7) How does a transient loss of energy supply affect blood flow regulation? (8) How does brain energy use change after a period without energy supply? Together this work will significantly advance our understanding of how the energy supply to neurons and glia is regulated in normal conditions, and how the loss of the energy supply causes disorders which consume more than 5% of the costs of European health services (5% of ~1000 billion euro/year).
Max ERC Funding
2 499 947 €
Duration
Start date: 2010-04-01, End date: 2016-03-31
Project acronym BUBPOL
Project Monetary Policy and Asset Price Bubbles
Researcher (PI) Jordi GalI Garreta
Host Institution (HI) Centre de Recerca en Economia Internacional (CREI)
Country Spain
Call Details Advanced Grant (AdG), SH1, ERC-2013-ADG
Summary "The proposed research project seeks to further our understanding on two important questions for the design of monetary policy:
(a) What are the effects of monetary policy interventions on asset price bubbles?
(b) How should monetary policy be conducted in the presence of asset price bubbles?
The first part of the project will focus on the development of a theoretical framework that can be used to analyze rigorously the implications of alternative monetary policy rules in the presence of asset price bubbles, and to characterize the optimal monetary policy. In particular, I plan to use such a framework to assess the merits of a “leaning against the wind” strategy, which calls for a systematic rise in interest rates in response to the development of a bubble.
The second part of the project will seek to produce evidence, both empirical and experimental, regarding the effects of monetary policy on asset price bubbles. The empirical evidence will seek to identify and estimate the sign and response of asset price bubbles to interest rate changes, exploiting the potential differences in the joint behavior of interest rates and asset prices during “bubbly” episodes, in comparison to “normal” times. In addition, I plan to conduct some lab experiments in order to shed some light on the link between monetary policy and bubbles. Participants will trade two assets, a one-period riskless asset and a long-lived stock, in an environment consistent with the existence of asset price bubbles in equilibrium. Monetary policy interventions will take the form of changes in the short-term interest rate, engineered by the experimenter. The experiments will allow us to evaluate some of the predictions of the theoretical models regarding the impact of monetary policy on the dynamics of bubbles, as well as the effectiveness of “leaning against the wind” policies."
Summary
"The proposed research project seeks to further our understanding on two important questions for the design of monetary policy:
(a) What are the effects of monetary policy interventions on asset price bubbles?
(b) How should monetary policy be conducted in the presence of asset price bubbles?
The first part of the project will focus on the development of a theoretical framework that can be used to analyze rigorously the implications of alternative monetary policy rules in the presence of asset price bubbles, and to characterize the optimal monetary policy. In particular, I plan to use such a framework to assess the merits of a “leaning against the wind” strategy, which calls for a systematic rise in interest rates in response to the development of a bubble.
The second part of the project will seek to produce evidence, both empirical and experimental, regarding the effects of monetary policy on asset price bubbles. The empirical evidence will seek to identify and estimate the sign and response of asset price bubbles to interest rate changes, exploiting the potential differences in the joint behavior of interest rates and asset prices during “bubbly” episodes, in comparison to “normal” times. In addition, I plan to conduct some lab experiments in order to shed some light on the link between monetary policy and bubbles. Participants will trade two assets, a one-period riskless asset and a long-lived stock, in an environment consistent with the existence of asset price bubbles in equilibrium. Monetary policy interventions will take the form of changes in the short-term interest rate, engineered by the experimenter. The experiments will allow us to evaluate some of the predictions of the theoretical models regarding the impact of monetary policy on the dynamics of bubbles, as well as the effectiveness of “leaning against the wind” policies."
Max ERC Funding
799 200 €
Duration
Start date: 2014-01-01, End date: 2017-12-31
Project acronym CAUSCOG
Project Tool Use As A Tool For Understanding Causal Cognition In Humans And Corvids
Researcher (PI) Nicola Susan Clayton
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE
Country United Kingdom
Call Details Advanced Grant (AdG), SH4, ERC-2013-ADG
Summary "Our ability to understand causality is at the very core of modern civilization. We see potential antecedents of this understanding in some non-human animals, notably apes and corvids. To date, behaviour thought to be indicative of causal understanding, particularly tool-use, has been mainly described as a phenomenon rather than studied as a mechanism and thus suffers from the lack of an experimentally-tested theoretical framework and deconstructive analysis. This significantly constrains our progress in answering key questions such as: (1) how do humans understand the physical world and solve problems? (2) what other ways of understanding causality and problem solving has evolution produced? (3) what selective pressures lead to the evolution of causal cognition? Each of these questions constitutes an area where there exists enormous potential to advance cognitive science. The overarching aim is to create a coherent, experimentally-tested, theoretical framework of the cognitive mechanisms underlying causal knowledge in corvids and humans, both young and adult. The advantage of our approach is that we will study two types of mind that have very different neural machineries and investigate the similarities and differences in their cognitive processes. We will create a sufficient level of abstraction to develop a deep theory of cognition, something that would not be possible by studying only a single species and its close evolutionary relatives. One of the most exciting aspects is that we will begin to map the ‘universal mind’ (i.e. the cognitive mechanisms that are repeatedly created by convergent evolution) to provide a quantum leap in our understanding of cognition. Finally, by discovering evolved biases in children’s learning and reasoning mechanisms we will pave the way for new teaching methods that boost learning in the classroom by appealing to the way children naturally understand the world."
Summary
"Our ability to understand causality is at the very core of modern civilization. We see potential antecedents of this understanding in some non-human animals, notably apes and corvids. To date, behaviour thought to be indicative of causal understanding, particularly tool-use, has been mainly described as a phenomenon rather than studied as a mechanism and thus suffers from the lack of an experimentally-tested theoretical framework and deconstructive analysis. This significantly constrains our progress in answering key questions such as: (1) how do humans understand the physical world and solve problems? (2) what other ways of understanding causality and problem solving has evolution produced? (3) what selective pressures lead to the evolution of causal cognition? Each of these questions constitutes an area where there exists enormous potential to advance cognitive science. The overarching aim is to create a coherent, experimentally-tested, theoretical framework of the cognitive mechanisms underlying causal knowledge in corvids and humans, both young and adult. The advantage of our approach is that we will study two types of mind that have very different neural machineries and investigate the similarities and differences in their cognitive processes. We will create a sufficient level of abstraction to develop a deep theory of cognition, something that would not be possible by studying only a single species and its close evolutionary relatives. One of the most exciting aspects is that we will begin to map the ‘universal mind’ (i.e. the cognitive mechanisms that are repeatedly created by convergent evolution) to provide a quantum leap in our understanding of cognition. Finally, by discovering evolved biases in children’s learning and reasoning mechanisms we will pave the way for new teaching methods that boost learning in the classroom by appealing to the way children naturally understand the world."
Max ERC Funding
2 164 833 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym CCFIB
Project Cardiac Control of Fear in Brain
Researcher (PI) Hugo Dyfrig Critchley
Host Institution (HI) THE UNIVERSITY OF SUSSEX
Country United Kingdom
Call Details Advanced Grant (AdG), SH4, ERC-2012-ADG_20120411
Summary "Imagine what might be possible if you can turn fear on and off. In exploring the contribution of bodily arousal to emotions, we uncovered a specific mechanism whereby the brain’s processing of threatening / fear stimuli is ‘gated’ by the occurrence of heartbeats: Fear stimuli presented when the heart has just made a beat are processed more effectively than at other times, modulating their emotional impact. We term this effect the Cardiac Control of Fear in Brain (CCFIB). Specifically, I wish to refine, develop and exploit CCFIB as; 1) a clinical screening tool for drugs and patients; 2) as the basis of an intervention to accelerate unlearning of fear, e.g. for treatment of anxiety disorders; 3) as a means to optimise and enrich human-machine interactions, in anticipation of the rapid development of virtual or augmented reality (VR/AR) as a therapeutic tool, and to open possibilities for improving machine operation. This ground-breaking project will have impact in many areas, notably in the clinical management of anxiety disorders, which affect 69.1 million European Union citizens at an annual cost of €74.4 billion, and in the educational, recreational and occupational realms of human-machine interaction. The proposal 1) will refine knowledge about the neurochemistry and stimulus-specificity of CCFIB for implementation as a clinical screening tool, using pharmacological and neuroimaging methods. 2) Test in clinical anxiety patients the power of CCFIB to predict symptom profile and response to psychological and pharmacological treatment. 3) Optimize CCFIB to augment psychological and behavioural treatments and validate this in phobic individuals. 4) Instantiate CCFIB in VR/AR settings to enhance engagement with virtual environments, develop VR/AR as a ‘training platform’ in clinical and recreational contexts and to demonstrate how reactions to rapid threats fluctuate with cardiac cycle, motivating corresponding changes in sensitivity of user interfaces (e.g. brakes)."
Summary
"Imagine what might be possible if you can turn fear on and off. In exploring the contribution of bodily arousal to emotions, we uncovered a specific mechanism whereby the brain’s processing of threatening / fear stimuli is ‘gated’ by the occurrence of heartbeats: Fear stimuli presented when the heart has just made a beat are processed more effectively than at other times, modulating their emotional impact. We term this effect the Cardiac Control of Fear in Brain (CCFIB). Specifically, I wish to refine, develop and exploit CCFIB as; 1) a clinical screening tool for drugs and patients; 2) as the basis of an intervention to accelerate unlearning of fear, e.g. for treatment of anxiety disorders; 3) as a means to optimise and enrich human-machine interactions, in anticipation of the rapid development of virtual or augmented reality (VR/AR) as a therapeutic tool, and to open possibilities for improving machine operation. This ground-breaking project will have impact in many areas, notably in the clinical management of anxiety disorders, which affect 69.1 million European Union citizens at an annual cost of €74.4 billion, and in the educational, recreational and occupational realms of human-machine interaction. The proposal 1) will refine knowledge about the neurochemistry and stimulus-specificity of CCFIB for implementation as a clinical screening tool, using pharmacological and neuroimaging methods. 2) Test in clinical anxiety patients the power of CCFIB to predict symptom profile and response to psychological and pharmacological treatment. 3) Optimize CCFIB to augment psychological and behavioural treatments and validate this in phobic individuals. 4) Instantiate CCFIB in VR/AR settings to enhance engagement with virtual environments, develop VR/AR as a ‘training platform’ in clinical and recreational contexts and to demonstrate how reactions to rapid threats fluctuate with cardiac cycle, motivating corresponding changes in sensitivity of user interfaces (e.g. brakes)."
Max ERC Funding
1 912 383 €
Duration
Start date: 2013-06-01, End date: 2017-05-31
