Project acronym CAFES
Project Causal Analysis of Feedback Systems
Researcher (PI) Joris Marten Mooij
Host Institution (HI) UNIVERSITEIT VAN AMSTERDAM
Call Details Starting Grant (StG), PE6, ERC-2014-STG
Summary Many questions in science, policy making and everyday life are of a causal nature: how would changing A influence B? Causal inference, a branch of statistics and machine learning, studies how cause-effect relationships can be discovered from data and how these can be used for making predictions in situations where a system has been perturbed by an external intervention. The ability to reliably make such causal predictions is of great value for practical applications in a variety of disciplines. Over the last two decades, remarkable progress has been made in the field. However, even though state-of-the-art causal inference algorithms work well on simulated data when all their assumptions are met, there is still a considerable gap between theory and practice. The goal of CAFES is to bridge that gap by developing theory and algorithms that will enable large-scale applications of causal inference in various challenging domains in science, industry and decision making.
The key challenge that will be addressed is how to deal with cyclic causal relationships ("feedback loops"). Feedback loops are very common in many domains (e.g., biology, economy and climatology), but have mostly been ignored so far in the field. Building on recently established connections between dynamical systems and causal models, CAFES will develop theory and algorithms for causal modeling, reasoning, discovery and prediction for cyclic causal systems. Extensions to stationary and non-stationary processes will be developed to advance the state-of-the-art in causal analysis of time-series data. In order to optimally use available resources, computationally efficient and statistically robust algorithms for causal inference from observational and interventional data in the context of confounders and feedback will be developed. The work will be done with a strong focus on applications in molecular biology, one of the most promising areas for automated causal inference from data.
Summary
Many questions in science, policy making and everyday life are of a causal nature: how would changing A influence B? Causal inference, a branch of statistics and machine learning, studies how cause-effect relationships can be discovered from data and how these can be used for making predictions in situations where a system has been perturbed by an external intervention. The ability to reliably make such causal predictions is of great value for practical applications in a variety of disciplines. Over the last two decades, remarkable progress has been made in the field. However, even though state-of-the-art causal inference algorithms work well on simulated data when all their assumptions are met, there is still a considerable gap between theory and practice. The goal of CAFES is to bridge that gap by developing theory and algorithms that will enable large-scale applications of causal inference in various challenging domains in science, industry and decision making.
The key challenge that will be addressed is how to deal with cyclic causal relationships ("feedback loops"). Feedback loops are very common in many domains (e.g., biology, economy and climatology), but have mostly been ignored so far in the field. Building on recently established connections between dynamical systems and causal models, CAFES will develop theory and algorithms for causal modeling, reasoning, discovery and prediction for cyclic causal systems. Extensions to stationary and non-stationary processes will be developed to advance the state-of-the-art in causal analysis of time-series data. In order to optimally use available resources, computationally efficient and statistically robust algorithms for causal inference from observational and interventional data in the context of confounders and feedback will be developed. The work will be done with a strong focus on applications in molecular biology, one of the most promising areas for automated causal inference from data.
Max ERC Funding
1 405 652 €
Duration
Start date: 2015-09-01, End date: 2020-08-31
Project acronym CoordinatedDopamine
Project Coordination of regional dopamine release in the striatum during habit formation and compulsive behaviour
Researcher (PI) Ingo Willuhn
Host Institution (HI) ACADEMISCH MEDISCH CENTRUM BIJ DE UNIVERSITEIT VAN AMSTERDAM
Call Details Starting Grant (StG), LS5, ERC-2014-STG
Summary The basal ganglia consist of a set of neuroanatomical structures that participate in the representation and execution of action sequences. Dopamine neurotransmission in the striatum, the main input nucleus of the basal ganglia, is a fundamental mechanism involved in learning and regulation of such actions. The striatum has multiple functional units, where the limbic striatum is thought to mediate motivational aspects of actions (e.g., goal-directedness) and the sensorimotor striatum their automation (e.g., habit formation). A long-standing question in the field is how limbic and sensorimotor domains communicate with each other, and specifically if they do so during the automation of action sequences. It has been suggested that such coordination is implemented by reciprocal loop connections between striatal projection neurons and the dopaminergic midbrain. Although very influential in theory the effectiveness of this limbic-sensorimotor “bridging” principle has yet to be verified. I hypothesize that during the automation of behaviour regional dopamine signalling is governed by a striatal hierarchy and that dysregulation of this coordination leads to compulsive execution of automatic actions characteristic of several psychiatric disorders. To test this hypothesis, we will conduct electrochemical measurements with real-time resolution simultaneously in limbic and sensorimotor striatum to assess the regional coordination of dopamine release in behaving animals. We developed novel chronically implantable electrodes to enable monitoring of dopamine dynamics throughout the development of habitual behaviour and its compulsive execution in transgenic rats - a species suitable for our complex behavioural assays. Novel rabies virus-mediated gene delivery for in vivo optogenetics in these rats will give us the unique opportunity to test whether specific loop pathways govern striatal dopamine transmission and are causally involved in habit formation and compulsive behaviour.
Summary
The basal ganglia consist of a set of neuroanatomical structures that participate in the representation and execution of action sequences. Dopamine neurotransmission in the striatum, the main input nucleus of the basal ganglia, is a fundamental mechanism involved in learning and regulation of such actions. The striatum has multiple functional units, where the limbic striatum is thought to mediate motivational aspects of actions (e.g., goal-directedness) and the sensorimotor striatum their automation (e.g., habit formation). A long-standing question in the field is how limbic and sensorimotor domains communicate with each other, and specifically if they do so during the automation of action sequences. It has been suggested that such coordination is implemented by reciprocal loop connections between striatal projection neurons and the dopaminergic midbrain. Although very influential in theory the effectiveness of this limbic-sensorimotor “bridging” principle has yet to be verified. I hypothesize that during the automation of behaviour regional dopamine signalling is governed by a striatal hierarchy and that dysregulation of this coordination leads to compulsive execution of automatic actions characteristic of several psychiatric disorders. To test this hypothesis, we will conduct electrochemical measurements with real-time resolution simultaneously in limbic and sensorimotor striatum to assess the regional coordination of dopamine release in behaving animals. We developed novel chronically implantable electrodes to enable monitoring of dopamine dynamics throughout the development of habitual behaviour and its compulsive execution in transgenic rats - a species suitable for our complex behavioural assays. Novel rabies virus-mediated gene delivery for in vivo optogenetics in these rats will give us the unique opportunity to test whether specific loop pathways govern striatal dopamine transmission and are causally involved in habit formation and compulsive behaviour.
Max ERC Funding
1 500 000 €
Duration
Start date: 2015-05-01, End date: 2020-04-30
Project acronym ENCODING IN AXONS
Project Identifying mechanisms of information encoding in myelinated single axons
Researcher (PI) Maarten Kole
Host Institution (HI) KONINKLIJKE NEDERLANDSE AKADEMIE VAN WETENSCHAPPEN - KNAW
Call Details Starting Grant (StG), LS5, ERC-2010-StG_20091118
Summary A major challenge in neuroscience is to understand how information is stored and coded within single nerve cells (neurons) and across neuron populations in the brain. Nerve cell fibres (axons) are thought to provide the wiring to connect neurons and conduct the electrical nerve impulse (action potential; AP). Recent discoveries, however, show that the initial part of axons actively participates in modulating APs and providing a means to enhance the computational repertoire of neurons in the central nervous system. To decrease the temporal delay in information transmission over long distances most axons are myelinated. Here, we will test the hypothesis that the degree of myelination of single axons directly and indirectly influences the mechanisms of AP generation and neural coding. We will use a novel approach of patch-clamp recording combined with immunohistochemical and ultrastructural identification to develop a detailed model of single myelinated neocortical axons. We also will investigate the neuron-glia interactions responsible for the myelination process and measure whether their development follows an activity-dependent process. Finally, we will elucidate the physiological and molecular similarities and discrepancies between myelinated and experimentally demyelinated single neocortical axons. These studies will provide a novel methodological framework to study central nervous system axons and yield basic insights into myelin physiology and pathophysiology.
Summary
A major challenge in neuroscience is to understand how information is stored and coded within single nerve cells (neurons) and across neuron populations in the brain. Nerve cell fibres (axons) are thought to provide the wiring to connect neurons and conduct the electrical nerve impulse (action potential; AP). Recent discoveries, however, show that the initial part of axons actively participates in modulating APs and providing a means to enhance the computational repertoire of neurons in the central nervous system. To decrease the temporal delay in information transmission over long distances most axons are myelinated. Here, we will test the hypothesis that the degree of myelination of single axons directly and indirectly influences the mechanisms of AP generation and neural coding. We will use a novel approach of patch-clamp recording combined with immunohistochemical and ultrastructural identification to develop a detailed model of single myelinated neocortical axons. We also will investigate the neuron-glia interactions responsible for the myelination process and measure whether their development follows an activity-dependent process. Finally, we will elucidate the physiological and molecular similarities and discrepancies between myelinated and experimentally demyelinated single neocortical axons. These studies will provide a novel methodological framework to study central nervous system axons and yield basic insights into myelin physiology and pathophysiology.
Max ERC Funding
1 994 640 €
Duration
Start date: 2011-04-01, End date: 2016-03-31
Project acronym INTERIMPACT
Project Impact of identified interneurons on cellular network mechanisms in the human and rodent neocortex
Researcher (PI) Gábor Tamás
Host Institution (HI) Szegedi Tudomanyegyetem - Hungarian-Netherlands School of Educational Management
Call Details Advanced Grant (AdG), LS5, ERC-2010-AdG_20100317
Summary This application addresses mechanisms linking the activity of single neurons with network events by defining the function of identified cell types in the cerebral cortex. The key hypotheses emerged from our experiments and propose that neurogliaform cells and axo-axonic cells achieve their function in the cortex through extreme forms of unspecificity and specificity, respectively. The project capitalizes on our discovery that neurogliaform cells reach GABAA and GABAB receptors on target cells through unitary volume transmission going beyond the classical theory which states that single cortical neurons act in or around synaptic junctions. We propose that the spatial unspecificity of neurotransmitter action leads to unprecedented functional capabilities for a single neuron simultaneously acting on neuronal, glial and vascular components of the surrounding area allowing neurogliaform cells to synchronize metabolic demand and supply in microcircuits. In contrast, axo-axonic cells represent extreme spatial specificity in the brain: terminals of axo-axonic cells exclusively target the axon initial segment of pyramidal neurons. Axo-axonic cells were considered as the most potent inhibitory neurons of the cortex. However, our experiments suggested that axo-axonic cells can be the most powerful excitatory neurons known to date by triggering complex network events. Our unprecedented recordings in the human cortex show that axo-axonic cells are crucial in activating functional assemblies which were implicated in higher order cognitive representations. We aim to define interactions between active cortical networks and axo-axonic cell triggered assemblies with an emphasis on mechanisms modulated by neurogliaform cells and commonly prescribed drugs.
Summary
This application addresses mechanisms linking the activity of single neurons with network events by defining the function of identified cell types in the cerebral cortex. The key hypotheses emerged from our experiments and propose that neurogliaform cells and axo-axonic cells achieve their function in the cortex through extreme forms of unspecificity and specificity, respectively. The project capitalizes on our discovery that neurogliaform cells reach GABAA and GABAB receptors on target cells through unitary volume transmission going beyond the classical theory which states that single cortical neurons act in or around synaptic junctions. We propose that the spatial unspecificity of neurotransmitter action leads to unprecedented functional capabilities for a single neuron simultaneously acting on neuronal, glial and vascular components of the surrounding area allowing neurogliaform cells to synchronize metabolic demand and supply in microcircuits. In contrast, axo-axonic cells represent extreme spatial specificity in the brain: terminals of axo-axonic cells exclusively target the axon initial segment of pyramidal neurons. Axo-axonic cells were considered as the most potent inhibitory neurons of the cortex. However, our experiments suggested that axo-axonic cells can be the most powerful excitatory neurons known to date by triggering complex network events. Our unprecedented recordings in the human cortex show that axo-axonic cells are crucial in activating functional assemblies which were implicated in higher order cognitive representations. We aim to define interactions between active cortical networks and axo-axonic cell triggered assemblies with an emphasis on mechanisms modulated by neurogliaform cells and commonly prescribed drugs.
Max ERC Funding
2 391 695 €
Duration
Start date: 2011-06-01, End date: 2017-05-31
Project acronym MidFrontalTheta2.0
Project MidFrontal Cortex Theta Oscillations: Causes and Consequences
Researcher (PI) Michael Steven Cohen
Host Institution (HI) STICHTING KATHOLIEKE UNIVERSITEIT
Call Details Starting Grant (StG), LS5, ERC-2014-STG
Summary While reading this text, pat your head and rub your stomach (if someone sees you, tell them it's OK; you're doing science). Right now you are engaging in an action that must be actively monitored and quickly adjusted to avoid making mistakes. Over the past five years, my collaborators and I discovered that there is a specific pattern of brain electrical activity that occurs during response conflict—competition between multiple conflicting actions when a mistake could be made. This brain activity is observed over the midfrontal cortex (MFC) and is characterized by oscillations at around 6 cycles per second (the theta band). MFC theta is a highly statistically robust marker of the neural networks involved in action monitoring and behavior adjustments, correlates with single-trial reaction time, and predicts how well people learn from mistakes. Despite these robust findings linking MFC theta to action monitoring, the significance of MFC theta for how neural microcircuits actually implement action monitoring and adjustments is unknown. In the ERC research we will use computer simulations and rodent models to understand how different types of neurons in different cortical layers might use action potentials and oscillations to implement action monitoring. The results will help us understand how the brain monitors behavior and avoids mistakes, and will also give insight into neural microcircuit organization as it relates to higher cognitive function. While developing these computer simulations and rodent models, we will also take our human research to the next level by asking: If action monitoring in the MFC is supported by theta oscillations, does this mean that our actions, and our ability to monitor and adjust them, occur with theta rhythmicity? To answer this question, we will develop new tasks combining data-gloves and EEG to test how the timing of human sequenced actions during keyboard typing (typists type in “theta”) corresponds to temporal dynamics of MFC theta.
Summary
While reading this text, pat your head and rub your stomach (if someone sees you, tell them it's OK; you're doing science). Right now you are engaging in an action that must be actively monitored and quickly adjusted to avoid making mistakes. Over the past five years, my collaborators and I discovered that there is a specific pattern of brain electrical activity that occurs during response conflict—competition between multiple conflicting actions when a mistake could be made. This brain activity is observed over the midfrontal cortex (MFC) and is characterized by oscillations at around 6 cycles per second (the theta band). MFC theta is a highly statistically robust marker of the neural networks involved in action monitoring and behavior adjustments, correlates with single-trial reaction time, and predicts how well people learn from mistakes. Despite these robust findings linking MFC theta to action monitoring, the significance of MFC theta for how neural microcircuits actually implement action monitoring and adjustments is unknown. In the ERC research we will use computer simulations and rodent models to understand how different types of neurons in different cortical layers might use action potentials and oscillations to implement action monitoring. The results will help us understand how the brain monitors behavior and avoids mistakes, and will also give insight into neural microcircuit organization as it relates to higher cognitive function. While developing these computer simulations and rodent models, we will also take our human research to the next level by asking: If action monitoring in the MFC is supported by theta oscillations, does this mean that our actions, and our ability to monitor and adjust them, occur with theta rhythmicity? To answer this question, we will develop new tasks combining data-gloves and EEG to test how the timing of human sequenced actions during keyboard typing (typists type in “theta”) corresponds to temporal dynamics of MFC theta.
Max ERC Funding
1 500 000 €
Duration
Start date: 2015-07-01, End date: 2020-06-30
Project acronym MULTICONNECT
Project Imaging Brain Circuits to Decode Brain Computations: Multimodal Multiscale Imaging of Cortical Microcircuits to Model Predictive Coding in Human Vision
Researcher (PI) Alard Franc Roebroeck
Host Institution (HI) UNIVERSITEIT MAASTRICHT
Call Details Starting Grant (StG), LS5, ERC-2014-STG
Summary The human brain is one of the largest and most complex biological networks known to exist. The architecture of its circuits, and therefore the computational basis of human cognition, remains largely unknown. The central aim of this proposal is to image human cortical connectivity at multiple spatial scales in order to understand human cortical computations.
Whereas canonical cortical microcircuits are an established theory of the repeating structure of the neocortex’s circuits, predictive coding provides a prominent proposal of what these circuits compute. This leads to the core hypothesis of this proposal: the variations in predictive coding computations performed by human cortical microcircuits in different visual areas are grounded in variations in their microcircuit connectivity. As a central case-study, this proposal investigates human visual apparent motion perception in V1/2/3 and V5/MT+.
The proposed research program is organized in two workpackages (WP I and II). WP I has the aim of imaging the multiscale connections of human neocortical microcircuits. The projects in WP I focus on structure and move from the mesoscale down to the microscale. WP II has the aim of modelling how microcircuits support predictive coding computations. The projects in WP II focus on function and move from the microscale back up to the mesoscale. Structural and functional assessment of microcircuitry in the human brain only recently became possible with the development of magnetic resonance imaging (MRI) at ultra-high field-strengths (UHF) of 7T and above. UHF diffusion MRI, combined with light microscopy, is used to image circuit structure in WP I. UHF functional MRI is used for computational modelling of computations in WP II.
Successful completion of the planned research will significantly advance our understanding of the computations in cortical microcircuits, deliver important new human connectomic reference data, and improve generative models of human cortical processing.
Summary
The human brain is one of the largest and most complex biological networks known to exist. The architecture of its circuits, and therefore the computational basis of human cognition, remains largely unknown. The central aim of this proposal is to image human cortical connectivity at multiple spatial scales in order to understand human cortical computations.
Whereas canonical cortical microcircuits are an established theory of the repeating structure of the neocortex’s circuits, predictive coding provides a prominent proposal of what these circuits compute. This leads to the core hypothesis of this proposal: the variations in predictive coding computations performed by human cortical microcircuits in different visual areas are grounded in variations in their microcircuit connectivity. As a central case-study, this proposal investigates human visual apparent motion perception in V1/2/3 and V5/MT+.
The proposed research program is organized in two workpackages (WP I and II). WP I has the aim of imaging the multiscale connections of human neocortical microcircuits. The projects in WP I focus on structure and move from the mesoscale down to the microscale. WP II has the aim of modelling how microcircuits support predictive coding computations. The projects in WP II focus on function and move from the microscale back up to the mesoscale. Structural and functional assessment of microcircuitry in the human brain only recently became possible with the development of magnetic resonance imaging (MRI) at ultra-high field-strengths (UHF) of 7T and above. UHF diffusion MRI, combined with light microscopy, is used to image circuit structure in WP I. UHF functional MRI is used for computational modelling of computations in WP II.
Successful completion of the planned research will significantly advance our understanding of the computations in cortical microcircuits, deliver important new human connectomic reference data, and improve generative models of human cortical processing.
Max ERC Funding
1 500 000 €
Duration
Start date: 2015-06-01, End date: 2020-05-31
Project acronym Organoid
Project Dissecting microbiome and immune interactions in human intestinal (cancer) organoids
Researcher (PI) Johannes Carolus Clevers
Host Institution (HI) KONINKLIJKE NEDERLANDSE AKADEMIE VAN WETENSCHAPPEN - KNAW
Call Details Advanced Grant (AdG), LS3, ERC-2014-ADG
Summary We pioneered the essential role of Wnt signals in adult stem cells, i.e. in intestinal crypts. We also found that loss of the APC gene activates the Wnt pathway and causes colorectal cancer (CRC). We then identified a Wnt target gene, Lgr5, which allowed us to define the crypt stem cells. In a previous ERC grant based on these findings, we identified novel Lgr5 stem cells in multiple organs, and defined in vitro culture conditions to grow epithelial organoids from single Lgr5 stem cells. Crucial in this was our identification of the Wnt agonistic R-spondins as the Lgr5 ligands. Cultured 'mini-guts' display all characteristics of normal gut, can be expanded for years, transplanted, and remain genetically stable.
Here, I propose a reductionist, ‘mini-gut’-based approach to two exciting research fields that currently mostly focus at the organismal/patient level: Microbiome research leans on deep-sequencing of complex microbial communities in health and disease; and immune checkpoint research in cancer rests largely on clinical trials of checkpoint-blocking antibodies. While many insights exist into the gut microbiome and -immune system, the epithelium is often treated as a neutral player. ‘Mini-gut’ technology allows us to dissect interactions of the gut microbiome with healthy and diseased epithelium, and of Tumor-Infiltrating Lymphocytes (TILs) with CRC 'mini-guts' (tumoroids).
To this end, we will describe/study
1) All immune receptors, -regulators and -effectors in the individual epithelial cell types.
2) 'Mini-guts' recombined with individual bacterial species,
3) CRC tumoroids recombined with their cultured TILs and subjected to immune checkpoint manipulation.
Using advanced molecular and imaging technologies, we will chart the molecular mechanisms that underlie the interactions from the ‘epithelial perspective’. Ultimately, this program will provide molecular detail to the effects of the microbiome and immune system on our gut, in health and disease.
Summary
We pioneered the essential role of Wnt signals in adult stem cells, i.e. in intestinal crypts. We also found that loss of the APC gene activates the Wnt pathway and causes colorectal cancer (CRC). We then identified a Wnt target gene, Lgr5, which allowed us to define the crypt stem cells. In a previous ERC grant based on these findings, we identified novel Lgr5 stem cells in multiple organs, and defined in vitro culture conditions to grow epithelial organoids from single Lgr5 stem cells. Crucial in this was our identification of the Wnt agonistic R-spondins as the Lgr5 ligands. Cultured 'mini-guts' display all characteristics of normal gut, can be expanded for years, transplanted, and remain genetically stable.
Here, I propose a reductionist, ‘mini-gut’-based approach to two exciting research fields that currently mostly focus at the organismal/patient level: Microbiome research leans on deep-sequencing of complex microbial communities in health and disease; and immune checkpoint research in cancer rests largely on clinical trials of checkpoint-blocking antibodies. While many insights exist into the gut microbiome and -immune system, the epithelium is often treated as a neutral player. ‘Mini-gut’ technology allows us to dissect interactions of the gut microbiome with healthy and diseased epithelium, and of Tumor-Infiltrating Lymphocytes (TILs) with CRC 'mini-guts' (tumoroids).
To this end, we will describe/study
1) All immune receptors, -regulators and -effectors in the individual epithelial cell types.
2) 'Mini-guts' recombined with individual bacterial species,
3) CRC tumoroids recombined with their cultured TILs and subjected to immune checkpoint manipulation.
Using advanced molecular and imaging technologies, we will chart the molecular mechanisms that underlie the interactions from the ‘epithelial perspective’. Ultimately, this program will provide molecular detail to the effects of the microbiome and immune system on our gut, in health and disease.
Max ERC Funding
3 062 438 €
Duration
Start date: 2015-11-01, End date: 2020-10-31
Project acronym PAAL
Project Practical Approximation Algorithms
Researcher (PI) Piotr Sankowski
Host Institution (HI) UNIWERSYTET WARSZAWSKI
Call Details Starting Grant (StG), PE6, ERC-2010-StG_20091028
Summary The goal of this proposal is the development and study of practical approximation algorithms. We will base our study on
theoretical models that can describe requirements for algorithms that make them practically efficient. We plan to develop an
efficient and useful programming library of approximation algorithms.
Our research on approximation algorithms will be concentrated on two main topics:
- multi-problem optimization, when the solution has to be composed out of different problems that need to interact,
- interplay between regular and random structure of network that could allow construction of good approximation algorithms.
The above concepts try to capture the notion of effective algorithms. It has to be underlined that they were not studied before.
The practical importance of these problems will be verified by the accompanying work on generic programming concepts
for approximation algorithms. These concepts will form the basis of universal library that will include Web algorithms and
algorithms for physical applications.
Summary
The goal of this proposal is the development and study of practical approximation algorithms. We will base our study on
theoretical models that can describe requirements for algorithms that make them practically efficient. We plan to develop an
efficient and useful programming library of approximation algorithms.
Our research on approximation algorithms will be concentrated on two main topics:
- multi-problem optimization, when the solution has to be composed out of different problems that need to interact,
- interplay between regular and random structure of network that could allow construction of good approximation algorithms.
The above concepts try to capture the notion of effective algorithms. It has to be underlined that they were not studied before.
The practical importance of these problems will be verified by the accompanying work on generic programming concepts
for approximation algorithms. These concepts will form the basis of universal library that will include Web algorithms and
algorithms for physical applications.
Max ERC Funding
1 000 000 €
Duration
Start date: 2010-11-01, End date: 2015-10-31
Project acronym RECONTEXT
Project From neurons to behaviour: Context representation and memory reconsolidation in the entorhinal hippocampal system
Researcher (PI) Christian Doeller
Host Institution (HI) STICHTING KATHOLIEKE UNIVERSITEIT
Call Details Starting Grant (StG), LS5, ERC-2010-StG_20091118
Summary One of the most intriguing topics in neuroscience and memory research today is ‘reconsolidation’: the phenomenon that a brief reminder renders an already consolidated memory labile again and that this fragile memory requires de novo protein synthesis to be reconsolidated. However, the functional role and the neural mechanisms of reconsolidation in humans are unclear. Another exciting line of research in neuroscience, based on the discovery of spatially tuned hippocampal place and entorhinal grid cells in rodents, suggests that during first exposure to an environment a spatial map-like representation is formed in the entorhinalhippocampal system and it has been proposed that events are then encoded onto this map in their spatial context. By combining the understanding of these two fields of animal research, translating it to systems neuroscience in humans and building on my recent discovery that place-cell and grid-cell like representations exist in humans, I will test the novel idea that these hippocampal and entorhinal representations of spatial context are a clue to understand the mechanisms of memory reconsolidation in humans. To examine this, I will use virtual-reality technologies combined with functional neuroimaging in humans. I will test the prediction that context reexposure leads to a reactivation of consolidated memories in neocortex and investigate the role of entorhinal-hippocampal context representations during memory reconsolidation. I will also examine the functional role and the mechanisms of a dynamic memory representation: How is new information integrated into reactivated memories? Finally, I will investigate conjunctive representations of cortical memories in the hippocampal formation. My eventual aim is to produce a coherent understanding of brain function from neural representations to systems-level involvement in behaviour which might help to understand the neural mechanisms underlying memory impairments in neuro-degenerative diseases.
Summary
One of the most intriguing topics in neuroscience and memory research today is ‘reconsolidation’: the phenomenon that a brief reminder renders an already consolidated memory labile again and that this fragile memory requires de novo protein synthesis to be reconsolidated. However, the functional role and the neural mechanisms of reconsolidation in humans are unclear. Another exciting line of research in neuroscience, based on the discovery of spatially tuned hippocampal place and entorhinal grid cells in rodents, suggests that during first exposure to an environment a spatial map-like representation is formed in the entorhinalhippocampal system and it has been proposed that events are then encoded onto this map in their spatial context. By combining the understanding of these two fields of animal research, translating it to systems neuroscience in humans and building on my recent discovery that place-cell and grid-cell like representations exist in humans, I will test the novel idea that these hippocampal and entorhinal representations of spatial context are a clue to understand the mechanisms of memory reconsolidation in humans. To examine this, I will use virtual-reality technologies combined with functional neuroimaging in humans. I will test the prediction that context reexposure leads to a reactivation of consolidated memories in neocortex and investigate the role of entorhinal-hippocampal context representations during memory reconsolidation. I will also examine the functional role and the mechanisms of a dynamic memory representation: How is new information integrated into reactivated memories? Finally, I will investigate conjunctive representations of cortical memories in the hippocampal formation. My eventual aim is to produce a coherent understanding of brain function from neural representations to systems-level involvement in behaviour which might help to understand the neural mechanisms underlying memory impairments in neuro-degenerative diseases.
Max ERC Funding
1 474 872 €
Duration
Start date: 2011-03-01, End date: 2016-02-29
Project acronym ROSETTA
Project Rosetta s Way Back to the Source:
Towards Reverse Engineering of Complex Software
Researcher (PI) Hendrik Jaap Bos
Host Institution (HI) STICHTING VU
Call Details Starting Grant (StG), PE6, ERC-2010-StG_20091028
Summary We propose a research program (Rossetta) towards reverse engineering of complex software that is available only in binary form. Most of the commercial software industry assumes that compilation (the translation of source code to binary code), is irreversible in practice for real applications. The research question for Rosetta is whether this irreversibility assumption is reasonable. If successful, the project will have a major impact on the software industry.
The challenge is daunting, because binary code after compilation lacks most of the visible structure and semantic information that is available at the source code level. There is no definition of data structures, no helpful names of variables and functions, no semantic information, and no indication of what chunks of instructions are supposed to do.
However, the Rosetta project has a clear methodology for source recovery. Reverse engineering is approached as an iterative process with an initial focus on recovering data structures, followed by recovery of code. We combine static and dynamic techniques with usage monitoring and machine learning. A key insight is that even if all visible structure has been removed from the data in memory, the structures will still be *used* in a way that corresponds to the source code. By observing the use of data and application of machine learning techniques, we will recover both the data and the source.
We store all information that we uncover in the Rosetta database. The database provides a handle on both the data structures and large sections of the code (and at various levels of abstraction). We believe that our methods will allow reverse engineering of very complex commercial software. Doing so will be our main criterion for success. In addition, however, we propose to demonstrate the usefulness of our analysis by automatically hardening software (to make it resilient against many types of attack) without requiring any access to the source co
Summary
We propose a research program (Rossetta) towards reverse engineering of complex software that is available only in binary form. Most of the commercial software industry assumes that compilation (the translation of source code to binary code), is irreversible in practice for real applications. The research question for Rosetta is whether this irreversibility assumption is reasonable. If successful, the project will have a major impact on the software industry.
The challenge is daunting, because binary code after compilation lacks most of the visible structure and semantic information that is available at the source code level. There is no definition of data structures, no helpful names of variables and functions, no semantic information, and no indication of what chunks of instructions are supposed to do.
However, the Rosetta project has a clear methodology for source recovery. Reverse engineering is approached as an iterative process with an initial focus on recovering data structures, followed by recovery of code. We combine static and dynamic techniques with usage monitoring and machine learning. A key insight is that even if all visible structure has been removed from the data in memory, the structures will still be *used* in a way that corresponds to the source code. By observing the use of data and application of machine learning techniques, we will recover both the data and the source.
We store all information that we uncover in the Rosetta database. The database provides a handle on both the data structures and large sections of the code (and at various levels of abstraction). We believe that our methods will allow reverse engineering of very complex commercial software. Doing so will be our main criterion for success. In addition, however, we propose to demonstrate the usefulness of our analysis by automatically hardening software (to make it resilient against many types of attack) without requiring any access to the source co
Max ERC Funding
1 339 000 €
Duration
Start date: 2011-05-01, End date: 2016-04-30
