Project acronym BiT
Project How the Human Brain Masters Time
Researcher (PI) Domenica Bueti
Host Institution (HI) SCUOLA INTERNAZIONALE SUPERIORE DI STUDI AVANZATI DI TRIESTE
Call Details Consolidator Grant (CoG), SH4, ERC-2015-CoG
Summary If you suddenly hear your song on the radio and spontaneously decide to burst into dance in your living room, you need to precisely time your movements if you do not want to find yourself on your bookshelf. Most of what we do or perceive depends on how accurately we represent the temporal properties of the environment however we cannot see or touch time. As such, time in the millisecond range is both a fundamental and elusive dimension of everyday experiences. Despite the obvious importance of time to information processing and to behavior in general, little is known yet about how the human brain process time. Existing approaches to the study of the neural mechanisms of time mainly focus on the identification of brain regions involved in temporal computations (‘where’ time is processed in the brain), whereas most computational models vary in their biological plausibility and do not always make clear testable predictions. BiT is a groundbreaking research program designed to challenge current models of time perception and to offer a new perspective in the study of the neural basis of time. The groundbreaking nature of BiT derives from the novelty of the questions asked (‘when’ and ‘how’ time is processed in the brain) and from addressing them using complementary but distinct research approaches (from human neuroimaging to brain stimulation techniques, from the investigation of the whole brain to the focus on specific brain regions). By testing a new biologically plausible hypothesis of temporal representation (via duration tuning and ‘chronotopy’) and by scrutinizing the functional properties and, for the first time, the temporal hierarchies of ‘putative’ time regions, BiT will offer a multifaceted knowledge of how the human brain represents time. This new knowledge will challenge our understanding of brain organization and function that typically lacks of a time angle and will impact our understanding of how the brain uses time information for perception and action
Summary
If you suddenly hear your song on the radio and spontaneously decide to burst into dance in your living room, you need to precisely time your movements if you do not want to find yourself on your bookshelf. Most of what we do or perceive depends on how accurately we represent the temporal properties of the environment however we cannot see or touch time. As such, time in the millisecond range is both a fundamental and elusive dimension of everyday experiences. Despite the obvious importance of time to information processing and to behavior in general, little is known yet about how the human brain process time. Existing approaches to the study of the neural mechanisms of time mainly focus on the identification of brain regions involved in temporal computations (‘where’ time is processed in the brain), whereas most computational models vary in their biological plausibility and do not always make clear testable predictions. BiT is a groundbreaking research program designed to challenge current models of time perception and to offer a new perspective in the study of the neural basis of time. The groundbreaking nature of BiT derives from the novelty of the questions asked (‘when’ and ‘how’ time is processed in the brain) and from addressing them using complementary but distinct research approaches (from human neuroimaging to brain stimulation techniques, from the investigation of the whole brain to the focus on specific brain regions). By testing a new biologically plausible hypothesis of temporal representation (via duration tuning and ‘chronotopy’) and by scrutinizing the functional properties and, for the first time, the temporal hierarchies of ‘putative’ time regions, BiT will offer a multifaceted knowledge of how the human brain represents time. This new knowledge will challenge our understanding of brain organization and function that typically lacks of a time angle and will impact our understanding of how the brain uses time information for perception and action
Max ERC Funding
1 670 830 €
Duration
Start date: 2016-10-01, End date: 2021-09-30
Project acronym CHRONOS
Project A geochemical clock to measure timescales of volcanic eruptions
Researcher (PI) Diego Perugini
Host Institution (HI) UNIVERSITA DEGLI STUDI DI PERUGIA
Call Details Consolidator Grant (CoG), PE10, ERC-2013-CoG
Summary "The eruption of volcanoes appears one of the most unpredictable phenomena on Earth. Yet the situation is rapidly changing. Quantification of the eruptive record constrains what is possible in a given volcanic system. Timing is the hardest part to quantify.
The main process triggering an eruption is the refilling of a sub-volcanic magma chamber by a new magma coming from depth. This process results in magma mixing and provokes a time-dependent diffusion of chemical elements. Understanding the time elapsed from mixing to eruption is fundamental to discerning pre-eruptive behaviour of volcanoes to mitigate the huge impact of volcanic eruptions on society and the environment.
The CHRONOS project proposes a new method that will cut the Gordian knot of the presently intractable problem of volcanic eruption timing using a surgical approach integrating textural, geochemical and experimental data on magma mixing. I will use the compositional heterogeneity frozen in time in the rocks the same way a broken clock at a crime scene is used to determine the time of the incident. CHRONOS will aim to:
1) be the first study to reproduce magma mixing, by performing unique experiments constrained by natural data and using natural melts, under controlled rheological and fluid-dynamics conditions;
2) obtain unprecedented high-quality data on the time dependence of chemical exchanges during magma mixing;
3) derive empirical relationships linking the extent of chemical exchanges and the mixing timescales;
4) determine timescales of volcanic eruptions combining natural and experimental data.
CHRONOS will open a new window on the physico-chemical processes occurring in the days preceding volcanic eruptions providing unprecedented information to build the first inventory of eruption timescales for planet Earth. If these timescales can be linked with geophysical signals occurring prior to eruptions, this inventory will have an immense value, enabling precise prediction of volcanic eruptions."
Summary
"The eruption of volcanoes appears one of the most unpredictable phenomena on Earth. Yet the situation is rapidly changing. Quantification of the eruptive record constrains what is possible in a given volcanic system. Timing is the hardest part to quantify.
The main process triggering an eruption is the refilling of a sub-volcanic magma chamber by a new magma coming from depth. This process results in magma mixing and provokes a time-dependent diffusion of chemical elements. Understanding the time elapsed from mixing to eruption is fundamental to discerning pre-eruptive behaviour of volcanoes to mitigate the huge impact of volcanic eruptions on society and the environment.
The CHRONOS project proposes a new method that will cut the Gordian knot of the presently intractable problem of volcanic eruption timing using a surgical approach integrating textural, geochemical and experimental data on magma mixing. I will use the compositional heterogeneity frozen in time in the rocks the same way a broken clock at a crime scene is used to determine the time of the incident. CHRONOS will aim to:
1) be the first study to reproduce magma mixing, by performing unique experiments constrained by natural data and using natural melts, under controlled rheological and fluid-dynamics conditions;
2) obtain unprecedented high-quality data on the time dependence of chemical exchanges during magma mixing;
3) derive empirical relationships linking the extent of chemical exchanges and the mixing timescales;
4) determine timescales of volcanic eruptions combining natural and experimental data.
CHRONOS will open a new window on the physico-chemical processes occurring in the days preceding volcanic eruptions providing unprecedented information to build the first inventory of eruption timescales for planet Earth. If these timescales can be linked with geophysical signals occurring prior to eruptions, this inventory will have an immense value, enabling precise prediction of volcanic eruptions."
Max ERC Funding
1 993 813 €
Duration
Start date: 2014-05-01, End date: 2019-04-30
Project acronym COGTOM
Project Cognitive tomography of mental representations
Researcher (PI) Máté Miklós LENGYEL
Host Institution (HI) KOZEP-EUROPAI EGYETEM
Call Details Consolidator Grant (CoG), SH4, ERC-2016-COG
Summary Internal models are fundamental to our understanding of how the mind constructs percepts, makes decisions, controls movements, and interacts with others. Yet, we lack principled quantitative methods to systematically estimate internal models from observable behaviour, and current approaches for discovering their mental representations remain heuristic and piecemeal. I propose to develop a set of novel 'doubly Bayesian' data analytical methods, using state-of-the-art Bayesian statistical and machine learning techniques to infer humans' internal models formalised as prior distributions in Bayesian models of cognition. This approach, cognitive tomography, takes a series of behavioural observations, each of which in itself may have very limited information content, and accumulates a detailed reconstruction of the internal model based on these observations. I also propose a set of stringent, quantifiable criteria which will be systematically applied at each step of the proposed work to rigorously assess the success of our approach. These methodological advances will allow us to track how the structured, task-general internal models that are so fundamental to humans' superior cognitive abilities, change over time as a result of decay, interference, and learning. We will apply cognitive tomography to a variety of experimental data sets, collected by our collaborators, in paradigms ranging from perceptual learning, through visual and motor structure learning, to social and concept learning. These analyses will allow us to conclusively and quantitatively test our central hypothesis that, rather than simply changing along a single 'memory strength' dimension, internal models typically change via complex and consistent patterns of transformations along multiple dimensions simultaneously. To facilitate the widespread use of our methods, we will release and support off-the-shelf usable implementations of our algorithms together with synthetic and real test data sets.
Summary
Internal models are fundamental to our understanding of how the mind constructs percepts, makes decisions, controls movements, and interacts with others. Yet, we lack principled quantitative methods to systematically estimate internal models from observable behaviour, and current approaches for discovering their mental representations remain heuristic and piecemeal. I propose to develop a set of novel 'doubly Bayesian' data analytical methods, using state-of-the-art Bayesian statistical and machine learning techniques to infer humans' internal models formalised as prior distributions in Bayesian models of cognition. This approach, cognitive tomography, takes a series of behavioural observations, each of which in itself may have very limited information content, and accumulates a detailed reconstruction of the internal model based on these observations. I also propose a set of stringent, quantifiable criteria which will be systematically applied at each step of the proposed work to rigorously assess the success of our approach. These methodological advances will allow us to track how the structured, task-general internal models that are so fundamental to humans' superior cognitive abilities, change over time as a result of decay, interference, and learning. We will apply cognitive tomography to a variety of experimental data sets, collected by our collaborators, in paradigms ranging from perceptual learning, through visual and motor structure learning, to social and concept learning. These analyses will allow us to conclusively and quantitatively test our central hypothesis that, rather than simply changing along a single 'memory strength' dimension, internal models typically change via complex and consistent patterns of transformations along multiple dimensions simultaneously. To facilitate the widespread use of our methods, we will release and support off-the-shelf usable implementations of our algorithms together with synthetic and real test data sets.
Max ERC Funding
1 179 462 €
Duration
Start date: 2017-05-01, End date: 2022-04-30
Project acronym DNAMEREP
Project The role of essential DNA metabolism genes in vertebrate chromosome replication
Researcher (PI) Vincenzo Costanzo
Host Institution (HI) IFOM FONDAZIONE ISTITUTO FIRC DI ONCOLOGIA MOLECOLARE
Call Details Consolidator Grant (CoG), LS1, ERC-2013-CoG
Summary "Faithful chromosomal DNA replication is essential to maintain genome stability. A number of DNA metabolism genes are involved at different levels in DNA replication. These factors are thought to facilitate the establishment of replication origins, assist the replication of chromatin regions with repetitive DNA, coordinate the repair of DNA molecules resulting from aberrant DNA replication events or protect replication forks in the presence of DNA lesions that impair their progression. Some DNA metabolism genes are present mainly in higher eukaryotes, suggesting the existence of more complex repair and replication mechanisms in organisms with complex genomes. The impact on cell survival of many DNA metabolism genes has so far precluded in depth molecular analysis. The use of cell free extracts able to recapitulate cell cycle events might help overcoming survival issues and facilitate these studies. The Xenopus laevis egg cell free extract represents an ideal system to study replication-associated functions of essential genes in vertebrate organisms. We will take advantage of this system together with innovative imaging and proteomic based experimental approaches that we are currently developing to characterize the molecular function of some essential DNA metabolism genes. In particular, we will characterize DNA metabolism genes involved in the assembly and distribution of replication origins in vertebrate cells, elucidate molecular mechanisms underlying the role of essential homologous recombination and fork protection proteins in chromosomal DNA replication, and finally identify and characterize factors required for faithful replication of specific vertebrate genomic regions.
The results of these studies will provide groundbreaking information on several aspects of vertebrate genome metabolism and will allow long-awaited understanding of the function of a number of vertebrate essential DNA metabolism genes involved in the duplication of large and complex genomes."
Summary
"Faithful chromosomal DNA replication is essential to maintain genome stability. A number of DNA metabolism genes are involved at different levels in DNA replication. These factors are thought to facilitate the establishment of replication origins, assist the replication of chromatin regions with repetitive DNA, coordinate the repair of DNA molecules resulting from aberrant DNA replication events or protect replication forks in the presence of DNA lesions that impair their progression. Some DNA metabolism genes are present mainly in higher eukaryotes, suggesting the existence of more complex repair and replication mechanisms in organisms with complex genomes. The impact on cell survival of many DNA metabolism genes has so far precluded in depth molecular analysis. The use of cell free extracts able to recapitulate cell cycle events might help overcoming survival issues and facilitate these studies. The Xenopus laevis egg cell free extract represents an ideal system to study replication-associated functions of essential genes in vertebrate organisms. We will take advantage of this system together with innovative imaging and proteomic based experimental approaches that we are currently developing to characterize the molecular function of some essential DNA metabolism genes. In particular, we will characterize DNA metabolism genes involved in the assembly and distribution of replication origins in vertebrate cells, elucidate molecular mechanisms underlying the role of essential homologous recombination and fork protection proteins in chromosomal DNA replication, and finally identify and characterize factors required for faithful replication of specific vertebrate genomic regions.
The results of these studies will provide groundbreaking information on several aspects of vertebrate genome metabolism and will allow long-awaited understanding of the function of a number of vertebrate essential DNA metabolism genes involved in the duplication of large and complex genomes."
Max ERC Funding
1 999 800 €
Duration
Start date: 2014-06-01, End date: 2019-05-31
Project acronym DyNET
Project Dynamical river NETworks: climatic controls and biogeochemical function
Researcher (PI) Gianluca BOTTER
Host Institution (HI) UNIVERSITA DEGLI STUDI DI PADOVA
Call Details Consolidator Grant (CoG), PE10, ERC-2017-COG
Summary Despite the ubiquity of expansion and retraction dynamics of flowing streams, the large majority of biogeochemical and hydrological studies conceive river networks as static elements of the landscape, and a coherent framework to quantify nature and extent of drainage network dynamics is lacking. The implications of this phenomenon extend far beyond hydrology and involve key ecological and biogeochemical function of riparian corridors. The proposed research project will move beyond the traditional paradigm of static river networks by unravelling, for the first time, physical causes and biogeochemical consequences of stream dynamics. In particular, the project will undertake the following overarching scientific questions: 1) what are the climatic and geomorphic controls on the expansion/contraction of river networks? 2) what is the length of temporary streams and what is their impact on catchment-scale biogeochemical processes and stream water quality across scales? These challenging issues will be addressed by developing a novel theoretical framework complemented by extensive field observations within four representative sites along a climatic gradient in the EU. Field measurements will include long-term weekly mapping of the active drainage network and daily hydro-chemical data across scales. The experimental dataset will be used to develop and inform a set of innovative modelling tools, including an analytical framework for the description of spatially explicit hydrologic dynamics driven by stochastic rainfall and a modular hydro-chemical model based on the concept of water age, able to account for the variable connectivity among soil, groundwater and channels as induced by stream network dynamics. The project will open new avenues to quantify freshwater carbon emissions - crucially dependent on the extent of ephemeral streams - and it will provide a robust basis to identify temporary rivers and maintain their biogeochemical function in times of global change.
Summary
Despite the ubiquity of expansion and retraction dynamics of flowing streams, the large majority of biogeochemical and hydrological studies conceive river networks as static elements of the landscape, and a coherent framework to quantify nature and extent of drainage network dynamics is lacking. The implications of this phenomenon extend far beyond hydrology and involve key ecological and biogeochemical function of riparian corridors. The proposed research project will move beyond the traditional paradigm of static river networks by unravelling, for the first time, physical causes and biogeochemical consequences of stream dynamics. In particular, the project will undertake the following overarching scientific questions: 1) what are the climatic and geomorphic controls on the expansion/contraction of river networks? 2) what is the length of temporary streams and what is their impact on catchment-scale biogeochemical processes and stream water quality across scales? These challenging issues will be addressed by developing a novel theoretical framework complemented by extensive field observations within four representative sites along a climatic gradient in the EU. Field measurements will include long-term weekly mapping of the active drainage network and daily hydro-chemical data across scales. The experimental dataset will be used to develop and inform a set of innovative modelling tools, including an analytical framework for the description of spatially explicit hydrologic dynamics driven by stochastic rainfall and a modular hydro-chemical model based on the concept of water age, able to account for the variable connectivity among soil, groundwater and channels as induced by stream network dynamics. The project will open new avenues to quantify freshwater carbon emissions - crucially dependent on the extent of ephemeral streams - and it will provide a robust basis to identify temporary rivers and maintain their biogeochemical function in times of global change.
Max ERC Funding
1 999 758 €
Duration
Start date: 2018-05-01, End date: 2023-04-30
Project acronym JAXPERTISE
Project Joint action expertise: Behavioral, cognitive, and neural mechanisms for joint action learning
Researcher (PI) Natalie Sebanz
Host Institution (HI) KOZEP-EUROPAI EGYETEM
Call Details Consolidator Grant (CoG), SH4, ERC-2013-CoG
Summary Human life is full of joint action and our achievements are, to a large extent, joint achievements that require the coordination of two or more individuals. Piano duets and tangos, but also complex technical and medical operations rely on and exist because of coordinated actions. In recent years, research has begun to identify the basic mechanisms of joint action. This work focused on simple tasks that can be performed together without practice. However, a striking aspect of human joint action is the expertise interaction partners acquire together. How people acquire joint expertise is still poorly understood. JAXPERTISE will break new ground by identifying the behavioural, cognitive, and neural mechanisms underlying the learning of joint action. Participating in joint activities is also a motor for individual development. Although this has long been recognized, the mechanisms underlying individual learning through engagement in joint activities remain to be spelled out from a cognitive science perspective. JAXPERTISE will make this crucial step by investigating how joint action affects source memory, semantic memory, and individual skill learning. Carefully designed experiments will optimize the balance between capturing relevant interpersonal phenomena and maximizing experimental control. The proposed studies employ behavioural measures, electroencephalography, and physiological measures. Studies tracing learning processes in novices will be complemented by studies analyzing expert performance in music and dance. New approaches, such as training participants to regulate each other’s brain activity, will lead to methodological breakthroughs. JAXPERTISE will generate basic scientific knowledge that will be relevant to a large number of different disciplines in the social sciences, cognitive sciences, and humanities. The insights gained in this project will have impact on the design of robot helpers and the development of social training interventions.
Summary
Human life is full of joint action and our achievements are, to a large extent, joint achievements that require the coordination of two or more individuals. Piano duets and tangos, but also complex technical and medical operations rely on and exist because of coordinated actions. In recent years, research has begun to identify the basic mechanisms of joint action. This work focused on simple tasks that can be performed together without practice. However, a striking aspect of human joint action is the expertise interaction partners acquire together. How people acquire joint expertise is still poorly understood. JAXPERTISE will break new ground by identifying the behavioural, cognitive, and neural mechanisms underlying the learning of joint action. Participating in joint activities is also a motor for individual development. Although this has long been recognized, the mechanisms underlying individual learning through engagement in joint activities remain to be spelled out from a cognitive science perspective. JAXPERTISE will make this crucial step by investigating how joint action affects source memory, semantic memory, and individual skill learning. Carefully designed experiments will optimize the balance between capturing relevant interpersonal phenomena and maximizing experimental control. The proposed studies employ behavioural measures, electroencephalography, and physiological measures. Studies tracing learning processes in novices will be complemented by studies analyzing expert performance in music and dance. New approaches, such as training participants to regulate each other’s brain activity, will lead to methodological breakthroughs. JAXPERTISE will generate basic scientific knowledge that will be relevant to a large number of different disciplines in the social sciences, cognitive sciences, and humanities. The insights gained in this project will have impact on the design of robot helpers and the development of social training interventions.
Max ERC Funding
1 992 331 €
Duration
Start date: 2014-08-01, End date: 2019-07-31
Project acronym LIGHTUP
Project Turning the cortically blind brain to see: from neural computations to system dynamicsgenerating visual awareness in humans and monkeys
Researcher (PI) Marco TAMIETTO
Host Institution (HI) UNIVERSITA DEGLI STUDI DI TORINO
Call Details Consolidator Grant (CoG), SH4, ERC-2017-COG
Summary Visual awareness affords flexibility and experiential richness, and its loss following brain damage has devastating effects. However, patients with blindness following cortical damage may retain visual functions, despite visual awareness is lacking (blindsight). But, how can we translate non-conscious visual abilities into conscious ones after damage to the visual cortex? To place our understanding of visual awareness on firm neurobiological and mechanistic bases, I propose to integrate human and monkey neuroscience. Next, I will translate this wisdom into evidence-based clinical intervention. First, LIGHTUP will apply computational neuroimaging methods at the micro-scale level, estimating population receptive fields in humans and monkeys. This will enable analyzing fMRI signal similar to the way tuning properties are studied in neurophysiology, and to clarify how brain areas translate visual properties into responses associated with awareness. Second, LIGHTUP leverages a behavioural paradigm that can dissociate nonconscious visual abilities from awareness in monkeys, thus offering a refined animal model of visual awareness. Applying behavioural-Dynamic Causal Modelling to combine fMRI and behavioral data, LIGHTUP will build up a Bayesian framework that specifies the directionality of information flow in the interactions across distant brain areas, and their causal role in generating visual awareness. In the third part, I will devise a rehabilitation protocol that combines brain stimulation and visual training to promote the (re)emergence of lost visual awareness. LIGHTUP will exploit non-invasive transcranial magnetic stimulation (TMS) in a novel protocol that enables stimulation of complex cortical circuits and selection of the direction of connectivity that is enhanced. This associative stimulation has been proven to induce Hebbian plasticity, and we have piloted its effects in fostering visual awareness in association with visual restoration training.
Summary
Visual awareness affords flexibility and experiential richness, and its loss following brain damage has devastating effects. However, patients with blindness following cortical damage may retain visual functions, despite visual awareness is lacking (blindsight). But, how can we translate non-conscious visual abilities into conscious ones after damage to the visual cortex? To place our understanding of visual awareness on firm neurobiological and mechanistic bases, I propose to integrate human and monkey neuroscience. Next, I will translate this wisdom into evidence-based clinical intervention. First, LIGHTUP will apply computational neuroimaging methods at the micro-scale level, estimating population receptive fields in humans and monkeys. This will enable analyzing fMRI signal similar to the way tuning properties are studied in neurophysiology, and to clarify how brain areas translate visual properties into responses associated with awareness. Second, LIGHTUP leverages a behavioural paradigm that can dissociate nonconscious visual abilities from awareness in monkeys, thus offering a refined animal model of visual awareness. Applying behavioural-Dynamic Causal Modelling to combine fMRI and behavioral data, LIGHTUP will build up a Bayesian framework that specifies the directionality of information flow in the interactions across distant brain areas, and their causal role in generating visual awareness. In the third part, I will devise a rehabilitation protocol that combines brain stimulation and visual training to promote the (re)emergence of lost visual awareness. LIGHTUP will exploit non-invasive transcranial magnetic stimulation (TMS) in a novel protocol that enables stimulation of complex cortical circuits and selection of the direction of connectivity that is enhanced. This associative stimulation has been proven to induce Hebbian plasticity, and we have piloted its effects in fostering visual awareness in association with visual restoration training.
Max ERC Funding
1 994 212 €
Duration
Start date: 2018-08-01, End date: 2023-07-31
Project acronym REPSUMODDT
Project Mechanisms and regulators coordinating replication integrity and DNA damage tolerance.
Researcher (PI) Dana Branzei
Host Institution (HI) IFOM FONDAZIONE ISTITUTO FIRC DI ONCOLOGIA MOLECOLARE
Call Details Consolidator Grant (CoG), LS1, ERC-2015-CoG
Summary Accurate chromosomal DNA replication is of fundamental importance for cellular function, genome integrity and development. In response to replication perturbations, DNA damage response (DDR) and DNA damage tolerance (DDT) pathways become activated and are crucial for detection and tolerance of lesions, as well as for facilitating replication completion and supporting chromosome structural integrity. While important functions and key players of these regulatory processes have been outlined, much less is known about the choreography and mechanistic interplay between DDR and DDT during replication. Moreover, the principles by which they uniquely or commonly affect replication-associated chromosome integrity remain poorly understood.
Here, we will use novel tools and a palette of ingenious genetic, molecular and proteomic based experimental strategies, to investigate the replication stress response triggered by diverse endogenous and exogenous cues, and to identify the underlying mechanisms. We will define the principles of local and temporal regulation of DDT in response to genotoxic stress, with a focus on the mechanisms of SUMO-regulated DNA metabolism processes. Additionally, we will investigate the topological DNA transitions triggered at intrinsically difficult to replicate genomic regions, stalled and terminal forks, with the aim of identifying key mechanisms and regulators of replication integrity at specific complex genomic regions or following specific types of replication stress. Finally, we will explore the relationship between DDT, replication fork architecture and sister chromatid cohesion in the context of DDR- and SUMO-orchestrated DNA transactions. We expect that these studies will reveal new aspects of how replication-associated DNA metabolism processes are inter-related and regulated, uniformly or at specific loci in the genome, and will break new ground in areas of replication mechanisms and chromosome integrity in general.
Summary
Accurate chromosomal DNA replication is of fundamental importance for cellular function, genome integrity and development. In response to replication perturbations, DNA damage response (DDR) and DNA damage tolerance (DDT) pathways become activated and are crucial for detection and tolerance of lesions, as well as for facilitating replication completion and supporting chromosome structural integrity. While important functions and key players of these regulatory processes have been outlined, much less is known about the choreography and mechanistic interplay between DDR and DDT during replication. Moreover, the principles by which they uniquely or commonly affect replication-associated chromosome integrity remain poorly understood.
Here, we will use novel tools and a palette of ingenious genetic, molecular and proteomic based experimental strategies, to investigate the replication stress response triggered by diverse endogenous and exogenous cues, and to identify the underlying mechanisms. We will define the principles of local and temporal regulation of DDT in response to genotoxic stress, with a focus on the mechanisms of SUMO-regulated DNA metabolism processes. Additionally, we will investigate the topological DNA transitions triggered at intrinsically difficult to replicate genomic regions, stalled and terminal forks, with the aim of identifying key mechanisms and regulators of replication integrity at specific complex genomic regions or following specific types of replication stress. Finally, we will explore the relationship between DDT, replication fork architecture and sister chromatid cohesion in the context of DDR- and SUMO-orchestrated DNA transactions. We expect that these studies will reveal new aspects of how replication-associated DNA metabolism processes are inter-related and regulated, uniformly or at specific loci in the genome, and will break new ground in areas of replication mechanisms and chromosome integrity in general.
Max ERC Funding
1 991 250 €
Duration
Start date: 2016-07-01, End date: 2021-06-30
Project acronym Transfer-Learning
Project Transfer Learning within and between brains
Researcher (PI) Giorgio Coricelli
Host Institution (HI) UNIVERSITA DEGLI STUDI DI TRENTO
Call Details Consolidator Grant (CoG), SH4, ERC-2013-CoG
Summary The neural bases of adaptive behavior in social environments are far from being understood. We propose to use both computational and neuroscientific methodologies to provide new and more accurate models of learning in interactive settings. The long-term objective is to develop a neural theory of learning: a mathematical framework that describes the computations mediating social learning in terms of neural signals, structures and plasticity. We plan to develop a model of adaptive learning based on three basic principles: (1) the observation of the outcome of un-chosen options improves the decisions taken in the learning process, (2) learning can be transferred from one domain to another, and (3) learning can be transferred from one agent to another (i.e. social learning). In all three cases, humans appear able to construct and transfer knowledge from sources other than their own direct experience, an underappreciated though we believe critical aspect of learning. Our approach will combine neural and behavioral data with computational models of learning. The hypotheses will be formalized into machine learning algorithms and neural networks of “regret” learning, to quantify the evolution of the learning computations on a trial-by-trial basis from the sequence of stimuli, choices and outcomes. The existence and accuracy of the predicted computations will be then tested on neural signals recorded with functional magnetic resonance imaging (fMRI). The potential findings of this project could lead us to suggest general principles of social learning, and we will be able to measure and model neural activation to show those general principles in action. In addition, our results could have important implications into policy-making - by revealing what type of information agents are naturally inclined to better learn from - and clinical practice - by outlining potential diagnostic procedures and behavioral therapies for disorders affecting social behavior.
Summary
The neural bases of adaptive behavior in social environments are far from being understood. We propose to use both computational and neuroscientific methodologies to provide new and more accurate models of learning in interactive settings. The long-term objective is to develop a neural theory of learning: a mathematical framework that describes the computations mediating social learning in terms of neural signals, structures and plasticity. We plan to develop a model of adaptive learning based on three basic principles: (1) the observation of the outcome of un-chosen options improves the decisions taken in the learning process, (2) learning can be transferred from one domain to another, and (3) learning can be transferred from one agent to another (i.e. social learning). In all three cases, humans appear able to construct and transfer knowledge from sources other than their own direct experience, an underappreciated though we believe critical aspect of learning. Our approach will combine neural and behavioral data with computational models of learning. The hypotheses will be formalized into machine learning algorithms and neural networks of “regret” learning, to quantify the evolution of the learning computations on a trial-by-trial basis from the sequence of stimuli, choices and outcomes. The existence and accuracy of the predicted computations will be then tested on neural signals recorded with functional magnetic resonance imaging (fMRI). The potential findings of this project could lead us to suggest general principles of social learning, and we will be able to measure and model neural activation to show those general principles in action. In addition, our results could have important implications into policy-making - by revealing what type of information agents are naturally inclined to better learn from - and clinical practice - by outlining potential diagnostic procedures and behavioral therapies for disorders affecting social behavior.
Max ERC Funding
1 999 998 €
Duration
Start date: 2014-08-01, End date: 2020-01-31
