Project acronym MEMORYSTICK
Project Plasticity and formation of lasting memories in health and disease. Genetic modeling of key regulators in adult and aging mammals and in neurodegenerative disease
Researcher (PI) Lars Olson
Host Institution (HI) KAROLINSKA INSTITUTET
Call Details Advanced Grant (AdG), LS5, ERC-2012-ADG_20120314
Summary When an adult mammal acquires new skills and new knowledge, the degree to which transition will occur from temporary to permanent memories of such events is governed by factors such as emotional weight and importance of the experiences for survival. To execute the necessary structural synaptic reorganisations needed to permanently embed novel memories in the brain, a complex and precisely orchestrated molecular machinery is activated. We have found that rapid down-regulation of Nogo receptor 1 (NgR1) is one key element needed to allow permanent memories to form. Thus, our MemoFlex mice, with inducible overexpression of NgR1 in forebrain neurons, are severely impaired with respect to the ability to form lasting memories. When transgenic NgR1 is turned off in these mice, the ability to form lasting memories is restored. Several other genes are also involved in the process of consolidation of memories, including prompt activity-driven upregulation of BDNF. Very recently, we have discovered that Lotus, a newly identified negative regulator of NgR1, is also upregulated by activity, thus providing additional efficacy to the process of causing nerve endings to become temporarily insensitive to Nogo when plasticity is needed. Based on our experience with neurotrophic factors and the Nogo signaling system, and using additional transgenic mouse models, including the mtDNA Mutator mouse with premature, yet typical aging, NgR1 KO mice and mice modeling neurodegenerative diseases (such as APPSwePSEN mice and our MitoPark mice to model aspects of Alzheimer’s and Parkinson’s disease, respectively) we will examine the formation of lasting normal and pathological (addiction, posttraumatic stress disorder) memories in adult and aging individuals with and without additional neurodegenerative genotypes known to include cognitive impariment. This research will further the understanding of mechanisms behind memory dysfunction and help the design of memory-improving stratetegies.
Summary
When an adult mammal acquires new skills and new knowledge, the degree to which transition will occur from temporary to permanent memories of such events is governed by factors such as emotional weight and importance of the experiences for survival. To execute the necessary structural synaptic reorganisations needed to permanently embed novel memories in the brain, a complex and precisely orchestrated molecular machinery is activated. We have found that rapid down-regulation of Nogo receptor 1 (NgR1) is one key element needed to allow permanent memories to form. Thus, our MemoFlex mice, with inducible overexpression of NgR1 in forebrain neurons, are severely impaired with respect to the ability to form lasting memories. When transgenic NgR1 is turned off in these mice, the ability to form lasting memories is restored. Several other genes are also involved in the process of consolidation of memories, including prompt activity-driven upregulation of BDNF. Very recently, we have discovered that Lotus, a newly identified negative regulator of NgR1, is also upregulated by activity, thus providing additional efficacy to the process of causing nerve endings to become temporarily insensitive to Nogo when plasticity is needed. Based on our experience with neurotrophic factors and the Nogo signaling system, and using additional transgenic mouse models, including the mtDNA Mutator mouse with premature, yet typical aging, NgR1 KO mice and mice modeling neurodegenerative diseases (such as APPSwePSEN mice and our MitoPark mice to model aspects of Alzheimer’s and Parkinson’s disease, respectively) we will examine the formation of lasting normal and pathological (addiction, posttraumatic stress disorder) memories in adult and aging individuals with and without additional neurodegenerative genotypes known to include cognitive impariment. This research will further the understanding of mechanisms behind memory dysfunction and help the design of memory-improving stratetegies.
Max ERC Funding
2 330 974 €
Duration
Start date: 2013-03-01, End date: 2018-02-28
Project acronym MESSI
Project Mesocorticolimbic System: functional anatomy,
drug-evoked synaptic plasticity & behavioral correlates of Synaptic Inhibition
Researcher (PI) Christian Lüscher
Host Institution (HI) UNIVERSITE DE GENEVE
Call Details Advanced Grant (AdG), LS5, ERC-2012-ADG_20120314
Summary The mesocorticolimbic (MCL) system, extending from the ventral tegmental area (VTA) to the nucleus accumbens and prefrontal cortex, comprises a dopamine (DA) projection implicated in reinforcement learning. The MCL system is the target of addictive substances and of drug-evoked synaptic plasticity, a cellular mechanism that may underlie the adaptive, pathological behaviors that occur after repeated drug exposure. While most previous work has focused on excitatory transmission, recent studies suggest that inhibitory transmission may play a crucial role in mediating specific functions of the MCL system. However the identity of the inhibitory synapses and circuits and the plasticity mechanisms underlying these forms of normal and pathological learning remain elusive.
We hypothesize that distinct inhibitory circuits in the MCL system mediate specific behaviors and that adaptive synaptic plasticity of these circuits are fundamental to both normal reward learning and addictive behaviors.
We will test this hypothesis using optogenetic projection targeting to characterize specific inhibitory projections, to selectively change the activity of these neurons in freely behaving animals to explore their behavioral relevance, and to identify precise circuit changes that underlie behavioral alterations after drug exposure. Taken together, the experiments we propose will not only identify the specific circuits and basic role of inhibition in mediating reward-related behaviors, but will allow us to understand how the alteration of these circuits after drugs can result in pathological behavior. Ultimately, our results will establish the importance of inhibitory synaptic transmission in the MCL system, are likely to fundamentally change current views of this important modulatory system, and will allow us to design strategies to interfere with drug-evoked synaptic plasticity to revert addictive behavior.
Summary
The mesocorticolimbic (MCL) system, extending from the ventral tegmental area (VTA) to the nucleus accumbens and prefrontal cortex, comprises a dopamine (DA) projection implicated in reinforcement learning. The MCL system is the target of addictive substances and of drug-evoked synaptic plasticity, a cellular mechanism that may underlie the adaptive, pathological behaviors that occur after repeated drug exposure. While most previous work has focused on excitatory transmission, recent studies suggest that inhibitory transmission may play a crucial role in mediating specific functions of the MCL system. However the identity of the inhibitory synapses and circuits and the plasticity mechanisms underlying these forms of normal and pathological learning remain elusive.
We hypothesize that distinct inhibitory circuits in the MCL system mediate specific behaviors and that adaptive synaptic plasticity of these circuits are fundamental to both normal reward learning and addictive behaviors.
We will test this hypothesis using optogenetic projection targeting to characterize specific inhibitory projections, to selectively change the activity of these neurons in freely behaving animals to explore their behavioral relevance, and to identify precise circuit changes that underlie behavioral alterations after drug exposure. Taken together, the experiments we propose will not only identify the specific circuits and basic role of inhibition in mediating reward-related behaviors, but will allow us to understand how the alteration of these circuits after drugs can result in pathological behavior. Ultimately, our results will establish the importance of inhibitory synaptic transmission in the MCL system, are likely to fundamentally change current views of this important modulatory system, and will allow us to design strategies to interfere with drug-evoked synaptic plasticity to revert addictive behavior.
Max ERC Funding
2 499 506 €
Duration
Start date: 2013-03-01, End date: 2019-02-28
Project acronym MitoMyelin
Project Roles of mitochondria in healthy and diseased myelin
Researcher (PI) Nicolas Tricaud
Host Institution (HI) INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE
Call Details Starting Grant (StG), LS5, ERC-2012-StG_20111109
Summary Demyelinating peripheral neuropathies form a diverse group of pathologies that include diabetic and aging peripheral neuropathies and inherited Charcot-Marie-Tooth diseases. Mitochondrial dysfunctions have recently emerged as one major cause for these diseases. The goal of this project is to investigate the role of mitochondria in healthy and diseased myelin and to test whether we can change mitochondrial status and functions to prevent or treat these diseases. Our working hypothesis is that glial mitochondria act as a homeostatic interface between axon and glia: they participate to the destabilization of Schwann cells during demyelination and they help to detoxify axons by scavenging reactive oxygen species produced by axonal mitochondria. We have developed a novel approach that uses viral vectors to express cDNAs and/or small inhibitory RNAs in myelinating Schwann cells and myelinated axons in mice in vivo. I propose to use this approach combined with state-of-the-art imaging technique to challenge this preliminary concept in a meaningful in vivo context. Viral tools will first be used to generate defects in mitochondrial functions in the myelinating Schwann cell. The impact on myelination and myelin maintenance will be assessed by light and electron microscopy. Second, viruses will be used to express genetically-encoded fluorescent probes designed to analyze mitochondrial status in living cells. This imaging approach will allow investigating mitochondrial status in healthy, demyelinating and diseased myelinating Schwann cells in vivo. Finally we will investigate the impact of glial mitochondria dysfunctions on the axon. Reversely we will also modify axonal mitochondria and check the impact of these changes on myelin and glial mitochondria. This concept will be highly relevant to understand the molecular mechanisms of peripheral neuropathies but also of brain diseases such as multiple sclerosis, Alzheimer’s, Parkinson’s and Huntington’s diseases.
Summary
Demyelinating peripheral neuropathies form a diverse group of pathologies that include diabetic and aging peripheral neuropathies and inherited Charcot-Marie-Tooth diseases. Mitochondrial dysfunctions have recently emerged as one major cause for these diseases. The goal of this project is to investigate the role of mitochondria in healthy and diseased myelin and to test whether we can change mitochondrial status and functions to prevent or treat these diseases. Our working hypothesis is that glial mitochondria act as a homeostatic interface between axon and glia: they participate to the destabilization of Schwann cells during demyelination and they help to detoxify axons by scavenging reactive oxygen species produced by axonal mitochondria. We have developed a novel approach that uses viral vectors to express cDNAs and/or small inhibitory RNAs in myelinating Schwann cells and myelinated axons in mice in vivo. I propose to use this approach combined with state-of-the-art imaging technique to challenge this preliminary concept in a meaningful in vivo context. Viral tools will first be used to generate defects in mitochondrial functions in the myelinating Schwann cell. The impact on myelination and myelin maintenance will be assessed by light and electron microscopy. Second, viruses will be used to express genetically-encoded fluorescent probes designed to analyze mitochondrial status in living cells. This imaging approach will allow investigating mitochondrial status in healthy, demyelinating and diseased myelinating Schwann cells in vivo. Finally we will investigate the impact of glial mitochondria dysfunctions on the axon. Reversely we will also modify axonal mitochondria and check the impact of these changes on myelin and glial mitochondria. This concept will be highly relevant to understand the molecular mechanisms of peripheral neuropathies but also of brain diseases such as multiple sclerosis, Alzheimer’s, Parkinson’s and Huntington’s diseases.
Max ERC Funding
1 918 878 €
Duration
Start date: 2013-04-01, End date: 2018-03-31
Project acronym MLCS
Project Machine learning for computational science:
statistical and formal modelling of biological systems
Researcher (PI) Guido Sanguinetti
Host Institution (HI) THE UNIVERSITY OF EDINBURGH
Call Details Starting Grant (StG), PE6, ERC-2012-StG_20111012
Summary Computational modelling is changing the face of science. Many complex systems can be understood as embodied computational systems performing distributed computations on a massive scale. Biology is the discipline where these ideas find their most natural application: cells can be viewed as input/ output devices, with proteins and organelles behaving as finite state machines performing distributed computations inside the cell. This led to the influential framework of cell as computation, and the successful deployment of formal verification and analysis on models of biological systems.
This paradigm shift in our understanding of biology has been possible due to the increasingly quantitative experimental techniques being developed in experimental biology. Formal modelling techniques, however, do not have mechanisms to directly include the information obtained from experimental observations in a statistically consistent way. This difficulty in relating the experimental and theoretical developments in biology is a central problem: without incorporating observations, it is extremely difficult to obtain reliable parametrisations of models. More importantly, it is impossible to assess the confidence of model predictions. This means that the central scientific task of falsifying hypotheses cannot be performed in a statistically meaningful way, and that it is very difficult to employ model predictions to rationally plan novel experiments.
In this project we will build and develop machine learning tools for continuous time stochastic processes to obtain a principled treatment of the uncertainty at every step of the modelling pipeline. We will use and extend probabilistic programming languages to fully automate the inference tasks, and link to advanced modelling languages to allow formal analysis tools to be deployed in a data modelling framework. We will pursue twoapplications to fundamental problems in systems biology, guaranteeing impact on exciting scientific questions.
Summary
Computational modelling is changing the face of science. Many complex systems can be understood as embodied computational systems performing distributed computations on a massive scale. Biology is the discipline where these ideas find their most natural application: cells can be viewed as input/ output devices, with proteins and organelles behaving as finite state machines performing distributed computations inside the cell. This led to the influential framework of cell as computation, and the successful deployment of formal verification and analysis on models of biological systems.
This paradigm shift in our understanding of biology has been possible due to the increasingly quantitative experimental techniques being developed in experimental biology. Formal modelling techniques, however, do not have mechanisms to directly include the information obtained from experimental observations in a statistically consistent way. This difficulty in relating the experimental and theoretical developments in biology is a central problem: without incorporating observations, it is extremely difficult to obtain reliable parametrisations of models. More importantly, it is impossible to assess the confidence of model predictions. This means that the central scientific task of falsifying hypotheses cannot be performed in a statistically meaningful way, and that it is very difficult to employ model predictions to rationally plan novel experiments.
In this project we will build and develop machine learning tools for continuous time stochastic processes to obtain a principled treatment of the uncertainty at every step of the modelling pipeline. We will use and extend probabilistic programming languages to fully automate the inference tasks, and link to advanced modelling languages to allow formal analysis tools to be deployed in a data modelling framework. We will pursue twoapplications to fundamental problems in systems biology, guaranteeing impact on exciting scientific questions.
Max ERC Funding
1 421 944 €
Duration
Start date: 2012-10-01, End date: 2017-09-30
Project acronym MQC
Project Methods for Quantum Computing
Researcher (PI) Andris Ambainis
Host Institution (HI) LATVIJAS UNIVERSITATE
Call Details Advanced Grant (AdG), PE6, ERC-2012-ADG_20120216
Summary "Quantum information science (QIS) is a young research area at the frontier of both computer science and physics. It studies what happens when we apply the principles of quantum mechanics to problems in computer science and information processing. This has resulted in many unexpected discoveries and opened up new frontiers.
Quantum algorithms (such as Shor’s factoring algorithm) can solve computational problems that are intractable for conventional computers. Quantum mechanics also enables quantum cryptography which provides an ultimate degree of security that cannot be achieved by conventional methods. These developments have generated an enormous interest both in building a quantum computer and exploring the mathematical foundations of quantum information.
We will study computer science aspects of QIS. Our first goal is to develop new quantum algorithms and, more generally, new algorithmic techniques for developing quantum algorithms. We will explore a variety of new ideas: quantum walks, span programs, learning graphs, linear equation solving, computing by transforming quantum states.
Secondly, we will study the limits of quantum computing. We will look at various classes of computational problems and analyze what are the biggest speedups that quantum algorithms can achieve. We will also work on identifying computational problems which are hard even for a quantum computer. Such problems can serve as a basis for cryptography that would be secure against quantum computers.
Thirdly, the ideas from quantum information can lead to very surprising connections between different fields. The mathematical methods from quantum information can be applied to solve purely classical (non-quantum) problems in computer science. The ideas from computer science can be used to study the complexity of physical systems in quantum mechanics. We think that both of those directions have the potential for unexpected breakthroughs and we will pursue both of them."
Summary
"Quantum information science (QIS) is a young research area at the frontier of both computer science and physics. It studies what happens when we apply the principles of quantum mechanics to problems in computer science and information processing. This has resulted in many unexpected discoveries and opened up new frontiers.
Quantum algorithms (such as Shor’s factoring algorithm) can solve computational problems that are intractable for conventional computers. Quantum mechanics also enables quantum cryptography which provides an ultimate degree of security that cannot be achieved by conventional methods. These developments have generated an enormous interest both in building a quantum computer and exploring the mathematical foundations of quantum information.
We will study computer science aspects of QIS. Our first goal is to develop new quantum algorithms and, more generally, new algorithmic techniques for developing quantum algorithms. We will explore a variety of new ideas: quantum walks, span programs, learning graphs, linear equation solving, computing by transforming quantum states.
Secondly, we will study the limits of quantum computing. We will look at various classes of computational problems and analyze what are the biggest speedups that quantum algorithms can achieve. We will also work on identifying computational problems which are hard even for a quantum computer. Such problems can serve as a basis for cryptography that would be secure against quantum computers.
Thirdly, the ideas from quantum information can lead to very surprising connections between different fields. The mathematical methods from quantum information can be applied to solve purely classical (non-quantum) problems in computer science. The ideas from computer science can be used to study the complexity of physical systems in quantum mechanics. We think that both of those directions have the potential for unexpected breakthroughs and we will pursue both of them."
Max ERC Funding
1 360 980 €
Duration
Start date: 2013-05-01, End date: 2018-04-30
Project acronym MU TUNING
Project Fine Tuning the Final Common Pathway: Molecular Determinants of Motor Unit Development and Plasticity
Researcher (PI) Till Marquardt
Host Institution (HI) UNIVERSITAETSKLINIKUM AACHEN
Call Details Starting Grant (StG), LS5, ERC-2012-StG_20111109
Summary Motor neurons (MNs) constitute the final common pathway in the generation of behaviors by linking the CNS with the movement apparatus. Herein, MNs diversify into fast, intermediate and slow types whose properties are tuned to the speed, force and endurance of the muscle fiber contractions they elicit. The MN-muscle fiber units display marked plasticity towards chronically altered physical activity, and show strong differences in their vulnerability towards degenerative conditions affecting the neuromuscular system, including amyotrophic lateral sclerosis and aging. Despite their central importance for determining neuromuscular output, plasticity and vulnerability the molecular mechanisms determining the functional MN types remain unknown. My group will use a cross-disciplinary approach by employing molecular genetic, cell biological, electrophysiological and motor behavior assays in mouse and chick to dissect molecular pathways determining MN type status and their contribution to neuromuscular system function and plasticity. Based on our preliminary data, this will focus on the contribution of non-canonical Notch signaling to MN type-specification and neuromuscular function, in addition to four newly identified neural activity modulators as candidate effectors of motor unit output and plasticity. This will be complemented by screening additional pathway components for roles in determining MN type properties through newly developed rapid gene tagging and electrophysiological interrogation in chick, followed by addressing their requirement for motor unit specification and function in mouse. Through an iterative cycle of (i) investigating candidate determinants of motor unit type, (ii) defining their role and mode of action in motor unit specification and function in the context of the neuromuscular system, and (iii) identifying essential downstream components, the proposal will explore molecular pathways operating in motor unit specification, function and plasticity.
Summary
Motor neurons (MNs) constitute the final common pathway in the generation of behaviors by linking the CNS with the movement apparatus. Herein, MNs diversify into fast, intermediate and slow types whose properties are tuned to the speed, force and endurance of the muscle fiber contractions they elicit. The MN-muscle fiber units display marked plasticity towards chronically altered physical activity, and show strong differences in their vulnerability towards degenerative conditions affecting the neuromuscular system, including amyotrophic lateral sclerosis and aging. Despite their central importance for determining neuromuscular output, plasticity and vulnerability the molecular mechanisms determining the functional MN types remain unknown. My group will use a cross-disciplinary approach by employing molecular genetic, cell biological, electrophysiological and motor behavior assays in mouse and chick to dissect molecular pathways determining MN type status and their contribution to neuromuscular system function and plasticity. Based on our preliminary data, this will focus on the contribution of non-canonical Notch signaling to MN type-specification and neuromuscular function, in addition to four newly identified neural activity modulators as candidate effectors of motor unit output and plasticity. This will be complemented by screening additional pathway components for roles in determining MN type properties through newly developed rapid gene tagging and electrophysiological interrogation in chick, followed by addressing their requirement for motor unit specification and function in mouse. Through an iterative cycle of (i) investigating candidate determinants of motor unit type, (ii) defining their role and mode of action in motor unit specification and function in the context of the neuromuscular system, and (iii) identifying essential downstream components, the proposal will explore molecular pathways operating in motor unit specification, function and plasticity.
Max ERC Funding
1 456 807 €
Duration
Start date: 2012-11-01, End date: 2017-10-31
Project acronym MultSens
Project Limits and prerequisites of information integration in the human brain: attention, awareness & vigilance
Researcher (PI) Uta Noppeney
Host Institution (HI) THE UNIVERSITY OF BIRMINGHAM
Call Details Starting Grant (StG), LS5, ERC-2012-StG_20111109
Summary Information integration is critical for the brain to interact effectively with our multisensory environment. Defining the limits and prerequisites of information integration is fundamental for understanding the mechanisms of normal brain functioning and their disintegration in diseases such as neglect & vegetative state. A key question is to what extent multisensory integration (MSI) is automatic or dependent on higher cognitive resources.
This proposal combines psychophysics, neuroimaging and Bayesian models to unravel the neural and computational mechanisms of MSI and their dependency on higher cognitive resources in the healthy & diseased brain.
First, we manipulate attention and stimulus awareness to dissociate bottom-up automatic from ‘cognitively controlled’ MSI. We hypothesize that automatic MSI relies primarily on feed-forward thalamocortical mechanisms, while ‘controlled’ MSI involves more top-down effects from association areas. Combining concurrent TMS-fMRI & Dynamic Causal Modelling, we will investigate how the network dynamics and integration capacity is affected by perturbations to parietal cortex. This research is complemented with studies in neglect patients to develop a multisensory model and novel MS therapies for neglect.
Second, combined fMRI/EEG studies will investigate how sensory inputs are integrated at reduced vigilance during sleep. We hypothesize that MSI is partly preserved in sleep via thalamocortical mechanisms. These paradigms are applied to patients in vegetative state to identify residual MSI functions and develop neural MSI signatures as predictors of recovery.
This research characterizes the neural and computational mechanisms of the multifaceted interplay of MSI with attention, awareness & vigilance. It significantly advances our understanding of information integration & segregation in the brain and has important implications for clinical diagnosis and rehabilitation of patients with neglect & vegetative state.
Summary
Information integration is critical for the brain to interact effectively with our multisensory environment. Defining the limits and prerequisites of information integration is fundamental for understanding the mechanisms of normal brain functioning and their disintegration in diseases such as neglect & vegetative state. A key question is to what extent multisensory integration (MSI) is automatic or dependent on higher cognitive resources.
This proposal combines psychophysics, neuroimaging and Bayesian models to unravel the neural and computational mechanisms of MSI and their dependency on higher cognitive resources in the healthy & diseased brain.
First, we manipulate attention and stimulus awareness to dissociate bottom-up automatic from ‘cognitively controlled’ MSI. We hypothesize that automatic MSI relies primarily on feed-forward thalamocortical mechanisms, while ‘controlled’ MSI involves more top-down effects from association areas. Combining concurrent TMS-fMRI & Dynamic Causal Modelling, we will investigate how the network dynamics and integration capacity is affected by perturbations to parietal cortex. This research is complemented with studies in neglect patients to develop a multisensory model and novel MS therapies for neglect.
Second, combined fMRI/EEG studies will investigate how sensory inputs are integrated at reduced vigilance during sleep. We hypothesize that MSI is partly preserved in sleep via thalamocortical mechanisms. These paradigms are applied to patients in vegetative state to identify residual MSI functions and develop neural MSI signatures as predictors of recovery.
This research characterizes the neural and computational mechanisms of the multifaceted interplay of MSI with attention, awareness & vigilance. It significantly advances our understanding of information integration & segregation in the brain and has important implications for clinical diagnosis and rehabilitation of patients with neglect & vegetative state.
Max ERC Funding
1 498 660 €
Duration
Start date: 2013-05-01, End date: 2018-04-30
Project acronym MUTRIPS
Project Mechanisms Underlying Treatment Responses in Psychosis
Researcher (PI) Sukhwinder Singh Shergill
Host Institution (HI) KING'S COLLEGE LONDON
Call Details Starting Grant (StG), LS5, ERC-2012-StG_20111109
Summary Psychotic symptoms (hallucinations and delusions) have been associated with a striatal hyperdopaminergic state.
Less explored, but also implicated are functional abnormalities in cognitive control, particularly in the prefrontal cortex; and a functional and structural disconnectivity between this and other areas of the brain.
Such a disconnectivity would explain the lack of coherent response to conventional treatment: antipsychotic drugs do not benefit between 20 and 45 per cent of people with schizophrenia.
The aim of this project is twofold: firstly, to explore the neural mechanisms underling cognitive control and the level at which cognitive control dysfunction operates in treatment refractory psychosis.
The second is to test the hypothesis that cognitive dysfunction in patients who have treatment-resistant psychosis is associated with a specific neural signature – and discover whether that neural signature can be used as a biomarker of treatment resistance. Such a biomarker would help personalise treatment decisions and make treatment regimes more effective. It would also aid the development of novel treatments (other complementary work is investigating medication that enhances frontal cortical function as well as non-invasive brain stimulation techniques such as transcranial direct cortical stimulation).
The project involves two linked brain imaging studies.
The first will establish the indicative biomarker using both structural and functional MRI scanning and tasks to assess cognitive control at different levels of complexity.
The second study will establish the validity of the biomarker by following a cohort of first episode psychosis patients for two years to discover whether their actual outcome corresponds with the outcome predicted by the neural signature shown in MRI scans.
Summary
Psychotic symptoms (hallucinations and delusions) have been associated with a striatal hyperdopaminergic state.
Less explored, but also implicated are functional abnormalities in cognitive control, particularly in the prefrontal cortex; and a functional and structural disconnectivity between this and other areas of the brain.
Such a disconnectivity would explain the lack of coherent response to conventional treatment: antipsychotic drugs do not benefit between 20 and 45 per cent of people with schizophrenia.
The aim of this project is twofold: firstly, to explore the neural mechanisms underling cognitive control and the level at which cognitive control dysfunction operates in treatment refractory psychosis.
The second is to test the hypothesis that cognitive dysfunction in patients who have treatment-resistant psychosis is associated with a specific neural signature – and discover whether that neural signature can be used as a biomarker of treatment resistance. Such a biomarker would help personalise treatment decisions and make treatment regimes more effective. It would also aid the development of novel treatments (other complementary work is investigating medication that enhances frontal cortical function as well as non-invasive brain stimulation techniques such as transcranial direct cortical stimulation).
The project involves two linked brain imaging studies.
The first will establish the indicative biomarker using both structural and functional MRI scanning and tasks to assess cognitive control at different levels of complexity.
The second study will establish the validity of the biomarker by following a cohort of first episode psychosis patients for two years to discover whether their actual outcome corresponds with the outcome predicted by the neural signature shown in MRI scans.
Max ERC Funding
1 498 902 €
Duration
Start date: 2013-03-01, End date: 2018-11-30
Project acronym MW-DISK
Project How the Milky Way Built Its Disk
Researcher (PI) Hans-Walter Rix
Host Institution (HI) MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Call Details Advanced Grant (AdG), PE9, ERC-2012-ADG_20120216
Summary Our Milky Way is a very typical galaxy, yet our position within it makes it a unique object of study: star-by-star we can obtain 3D positions, 3D velocities and chemical abundances. This wealth of information about our Galaxy’s stellar body holds the key to understanding how disk galaxies form and how dark matter acts on the scales of galaxies. Ongoing surveys have recently hundred-folded the number of stars with good distance estimates, radial and transverse velocities and abundance estimates; and this only forebodes the data wealth expected from ESA’s Gaia mission. Yet, practical approaches to extract the enormous astrophysical information content of these data have been sorely underdeveloped. Just within the last year, the PI and his collaborators have pioneered how to construct rigorously both mass density and kinematic maps of the Milky Way's stellar disk from existing spectroscopic surveys. It is proposed here to unleash the full potential of this approach.
This proposal builds on the PI's unique track record encompassing both extensive survey data analysis and detailed dynamical modeling, combined with his role in proprietary key data sets for this project. Focusing a group of experienced post-docs and PhD students for five years on these challenges will bring the critical mass in one single place to implementing such a comprehensive data/modeling machinery. The first years of the project will focus on the technique development and applications to ground-based data. The results will tell us how the Galaxy's disk was built and shaped, and will map dark matter in the inner parts of the MW. Such an analysis machinery is also indispensable for capitalizing (astrophysically) on the catalogs that the Gaia mission will provide.
Summary
Our Milky Way is a very typical galaxy, yet our position within it makes it a unique object of study: star-by-star we can obtain 3D positions, 3D velocities and chemical abundances. This wealth of information about our Galaxy’s stellar body holds the key to understanding how disk galaxies form and how dark matter acts on the scales of galaxies. Ongoing surveys have recently hundred-folded the number of stars with good distance estimates, radial and transverse velocities and abundance estimates; and this only forebodes the data wealth expected from ESA’s Gaia mission. Yet, practical approaches to extract the enormous astrophysical information content of these data have been sorely underdeveloped. Just within the last year, the PI and his collaborators have pioneered how to construct rigorously both mass density and kinematic maps of the Milky Way's stellar disk from existing spectroscopic surveys. It is proposed here to unleash the full potential of this approach.
This proposal builds on the PI's unique track record encompassing both extensive survey data analysis and detailed dynamical modeling, combined with his role in proprietary key data sets for this project. Focusing a group of experienced post-docs and PhD students for five years on these challenges will bring the critical mass in one single place to implementing such a comprehensive data/modeling machinery. The first years of the project will focus on the technique development and applications to ground-based data. The results will tell us how the Galaxy's disk was built and shaped, and will map dark matter in the inner parts of the MW. Such an analysis machinery is also indispensable for capitalizing (astrophysically) on the catalogs that the Gaia mission will provide.
Max ERC Funding
2 421 960 €
Duration
Start date: 2013-05-01, End date: 2018-04-30
Project acronym NEMESIS
Project Neuroprotection in Multiple Sclerosis: From Molecular Imaging to Screenable Models
Researcher (PI) Martin Kerschensteiner
Host Institution (HI) LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN
Call Details Starting Grant (StG), LS5, ERC-2012-StG_20111109
Summary "Multiple Sclerosis (MS) is an inflammatory CNS disease that affects more than 2.5 million individuals worldwide. Damage to axonal connections determines the functional deficits of MS patients. How axons are damaged in MS is only incompletely understood. Using in vivo multiphoton imaging we have discovered a novel axon loss process that underlies axonal damage in experimental and human neuroinflammatory lesions. We have termed this process Focal Axonal Degeneration (FAD). FAD is characterized by a sequence of morphologically defined stages that ultimately result in axonal fragmentation. Notably, intermediate stages of FAD can persist for several days in vivo and still recover spontaneously. In this proposal I want to explore the biological and medical significance of FAD by addressing its:
1. Functional Characteristics
I want to analyze two key aspects of axonal function, the ability to transport cargoes and the ability to propagate action potentials, in experimental neuroinflammatory lesions to better understand the in vivo relation between structural and functional deficits during axon damage.
2. Molecular Mechanisms
I want to deploy new molecular imaging approaches to directly monitor the redox potential, calcium and ATP levels of axons and their mitochondria in experimental neuroinflammatory lesions. This will allow us to reveal the key effector mechanisms of FAD and the sequence in which they are activated in vivo.
3.Therapeutic Opportunities
I plan to make use of advances in automated imaging and microfluidics to develop new in vivo assays for high-throughput screening of therapeutic interventions. This will help us to identify novel strategies for limiting progression and improving recovery of axon damage.
The proposed project should provide new insights into the functional and molecular underpinnings of axon damage in vivo, establish new tools and models to study it and guide the development of therapeutic strategies that can prevent or reverse it."
Summary
"Multiple Sclerosis (MS) is an inflammatory CNS disease that affects more than 2.5 million individuals worldwide. Damage to axonal connections determines the functional deficits of MS patients. How axons are damaged in MS is only incompletely understood. Using in vivo multiphoton imaging we have discovered a novel axon loss process that underlies axonal damage in experimental and human neuroinflammatory lesions. We have termed this process Focal Axonal Degeneration (FAD). FAD is characterized by a sequence of morphologically defined stages that ultimately result in axonal fragmentation. Notably, intermediate stages of FAD can persist for several days in vivo and still recover spontaneously. In this proposal I want to explore the biological and medical significance of FAD by addressing its:
1. Functional Characteristics
I want to analyze two key aspects of axonal function, the ability to transport cargoes and the ability to propagate action potentials, in experimental neuroinflammatory lesions to better understand the in vivo relation between structural and functional deficits during axon damage.
2. Molecular Mechanisms
I want to deploy new molecular imaging approaches to directly monitor the redox potential, calcium and ATP levels of axons and their mitochondria in experimental neuroinflammatory lesions. This will allow us to reveal the key effector mechanisms of FAD and the sequence in which they are activated in vivo.
3.Therapeutic Opportunities
I plan to make use of advances in automated imaging and microfluidics to develop new in vivo assays for high-throughput screening of therapeutic interventions. This will help us to identify novel strategies for limiting progression and improving recovery of axon damage.
The proposed project should provide new insights into the functional and molecular underpinnings of axon damage in vivo, establish new tools and models to study it and guide the development of therapeutic strategies that can prevent or reverse it."
Max ERC Funding
1 487 200 €
Duration
Start date: 2012-12-01, End date: 2017-11-30
