Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : DARE2APPROACH (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Radboud University Nijmegen — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

How did three soldiers override their initial freezing response to overpower an armed terrorist in the Thalys-train to Paris in 2015? This question is relevant for anyone aiming to optimize approach-avoidance (AA) decisions during threat. It is particularly relevant for patients with anxiety disorders whose persistent avoidance is key to the maintenance of their anxiety. Computational psychiatry has made great progress in formalizing how we make (mal)adaptive decisions. Current models, however, largely ignore the transient psychophysiological state of the decision maker. Parasympathetic state and flexibility in switching between para- and sympathetic states are directly related to freezing, and are known to bias AA-decisions toward avoidance. The central aim of this research program is to forge a mechanistic understanding of how we compute AA-decisions on the basis of those psychophysiological states, and to identify alterations in anxiety patients in order to guide new personalized neurocognitive interventions into their persistent avoidance. I will develop a neurocomputational model of AA-decisions that accounts for transient psychophysiological states, in order to define which decision parameters are altered in active and passive avoidance in anxiety. I will test causal premises of the model using state-of-the-art techniques, including pharmacological and electrophysiological interventions. Based on these insights I will for the first time apply personalized brain stimulation to anxiety patients. Clinically, this project should open the way to effective intervention with fearful avoidance in anxiety disorders that rank among the most common, costly and persistent mental disorders. Theoretically, conceptualizing transient psychophysiological states as causal factor in AA-decision models is essential to understanding passive and active avoidance. Optimizing AA-decisions also holds broad societal relevance given currently increased fearful avoidance of outgroups.

Mots-clés : approach avoidance decisions,fearful avoidance,freezing behavior,psychophysiology,anxiety disorders,brain stimulation
Projet ERC : CONSCIOUS (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Radboud University Nijmegen — Pays : Pays-Bas — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 48325.0 €

How do conscious experiences depend on the brain? The CONSCIOUS project aims to make new progress on this oldest of questions by progressing from establishing correlations between patterns of brain activity and aspects of consciousness, towards developing and testing explanations in terms of neural mechanisms. By following this strategy, I believe the problem of consciousness will be dissolved rather than outright solved – similar to what happened with the study of life, decades ago. One branch of CONSCIOUS will explore what it is like to be conscious ‘at all’. Here, I will make use of the concept of ‘emergence’ – the sense in which a system’s whole can seem to be more than the sum of its parts. I will test the idea that the globally unified character of conscious experiences emerges from neural dynamics, in a similar way to how a flock of birds emerges from the trajectories of the individual birds that make it up. This will involve developing new theoretically principled and practically applicable measures of emergence, and applying them to neurophysiological data reflecting different global states of consciousness. A second branch will explore the nature of specific conscious perceptions, appealing to the influential idea of the brain as a ‘prediction machine’. Here, I will develop novel machine learning models to investigate how particular conscious experiences can be understood as arising from the brain’s ‘best guesses’ of the causes of its sensory inputs. I will use combinations of behavioural experiments and neuroimaging to test the idea that different kinds of neurally-encoded predictions can account for different kinds of perceptual experience. CONSCIOUS is thoroughly multidisciplinary, bridging cognitive neuroscience, philosophy, statistical physics, machine learning, and artificial intelligence. It is only through such an approach that it is possible to make substantial progress towards a satisfying scientific account of conscious experience.

Mots-clés : emergence,predictive processing,active inference,machine learning,artificial intelligence,phenomenology
Projet ERC : InsularAnxiety (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 1498000.0 €

How do emotions guide our behaviour? For an appropriate behavioural response, an individual has to constantly integrate bodily feelings, emotional states, and cues from the environment to evaluate the risks and benefits of a future action. A growing body of evidence indicates that the insular cortex, as part of a distributed neuronal network, plays a key role in influencing emotional behaviour. However, how neuronal circuits within the insular cortex function mechanistically is not known. In this proposal, I will focus on the largely overlooked role of the insular cortex in mediating fear- and anxiety-related behaviours. I will address how the insular cortex processes sensory information of different emotional valence, whether it predicts risk, and how it influences emotional behaviour and decision-making. I will present a research program relying on modern tools to dissect neuronal circuit architecture and function in the mouse, such as viral tracing techniques, optogenetics, behavioural analysis and in vivo two-photon imaging in awake behaving mice. Taking advantage of the technical expertise of my lab, we will reveal the architecture of connectivity-defined insular cortical microcircuits using monosynaptic viral tracing tools. We will address the necessity and sufficiency of connectivity- and cell-type defined microcircuits to express anxiety and learned safety using optogenetic manipulations. In vivo two-photon calcium imaging in awake behaving animals will allow us to examine how representations of sensory cues predicting danger or safety are processed in the insular cortex, which information amygdala afferents carry to the insular cortex, and whether and how neuronal processing in the insular cortex signals risky or safe outcomes. The ultimate goal of this proposal is to provide novel insights into the function and organization of the insular cortex from a network perspective down to the single cell level.

Mots-clés : anxiety,insular cortex,optogenetics,microcircuits,two photon calcium imaging,fear conditioning,viral tracing,decision making,risk prediction,conditioned fear inhibition,emotion regulation
Projet ERC : SynapSeek (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Institute of Science and Technology Austria — Pays : Autriche — Rôle : PI
Acronyme de l'entité : ISTA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1768919.41 €

How do we learn to dance, play an instrument, or a game as complex as chess or go? How do we make a memory? The common answer to these questions is “through synaptic plasticity”, through changing the synaptic connectivity of neural circuits so that representative brain activity can be reliably triggered. Such connectivity changes are governed by rules, i.e., synaptic mechanisms which monitor the activity of their environment and stereotypically strengthen or weaken synapses accordingly. The shape and mode of operation of these rules is still largely unknown: For the more than hundred different connection types in cortical circuits, only a handful of rules has been described at all. Similarly, testing observed rules in simulations of cortical function has only seen limited success. Our slow progress is due to the extraordinary difficulty of measuring and observing synapses without interference. Here, we propose a new approach. By utilizing the growing power of machine learning methods we can deduce synaptic plasticity rules directly. Newly developed search algorithms and sheer computational power allow us to integrate published data and infer synaptic rules in silico. We aim to (1) develop a new mathematical expression of synaptic plasticity rules, experimentally appropriate and flexible enough to be implemented in a Machine Learning framework, dubbed SYNAPSEEK. Next (2), we will apply SYNAPSEEK to deduce the rules for building various neural structures with increasing complexity. Finally (3), we will incorporate additional constraints to SYNAPSEEK to develop synaptic rules that shape network function as much as its structure. Our work will establish, for the first time, canonical sets of synaptic plasticity rules, based on the circuit structure they must produce, and the function they are meant to support. SYNAPSEEK will have immediate and wide ranging applications, from a basic understanding of cortical development to better protocols for Deep Brain Stimulation.

Mots-clés : machine learning,artificial intelligence,synaptic plasticity
Projet ERC : SexYeast (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : University of Lausanne — Pays : Suisse — Rôle : Partner
Acronyme de l'entité : UNIL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 229822.0 €

How does a cell orient in response to a chemical cue? This basic problem is at the core of how cells interact with their environment. Indeed, the ability to move towards the source of a chemical gradient underlies behaviours as diverse as feeding, identifying a foreign invader or building interconnected cellular networks. Furthermore, chemo-orientation forms the basis of gamete recognition, and is thus critical for genome diversification through sexual reproduction. This proposal makes use of one of the simplest eukaryotic models, the fission yeast S. pombe, to systematically dissect the mechanisms of gradient detection. Gradient sensing occurs during sexual reproduction in a speed-dating process for mate pairing, where dynamic cortical polarity patches secrete pheromones and become stabilized in response to those produced by the other mating type. Chemo-detection depends on a minimal kit of conserved eukaryotic proteins, suggesting that a complete understanding of gradient decoding is possible. We will work towards this goal through four specific aims: 1. to establish the rules of gradient decoding, using unbiased image analysis and caged pheromones; 2. to define the architecture of the communication site, by super-resolution and correlative light-electron microscopy; 3. to probe the molecular regulation of cellular speed-dating, which we hypothesize consists of a spatial decoder and dynamic oscillator; 4. to reveal natural modifiers of speed-dating for mate selection, by exploiting the diversity of wild strain isolates. By combining advanced live and correlative imaging with optogenetic, genetic, biochemical and genomic methods, this project will bring a conceptual and molecular understanding to the problem of gradient decoding. Due to the ancient and fundamental nature of gradient orientation, our discoveries will have impact on several fields of research, including those of immunity, wound healing, development, sexual reproduction and evolution.

Mots-clés : chemotropism,pheromone signalling,gpcr signalling,cdc42 gtpase,cell polarisation,fission yeast schizosaccharomyces pombe,fungi,sexual reproduction,mating,natural variation
Projet ERC : MotivatedBehaviors (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Spanish National Research Council — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CSIC
Type d'entité : Recherche
Financement ERC de l'entité : 1735375.0 €

How does cognition regulate innate “low-level” behaviors? While the cognitive functions of the prefrontal cortex (PFC) and hippocampus have been extensively studied, we know much less about their ability to regulate the activity of the various hypothalamic nuclei controlling motivated behaviors (sociability, aggression, mating, feeding). Living in society nonetheless requires that our past experiences and decision-making exert some degree of control over our “basic” behaviors. The lateral septum (LS) -receiving inputs from PFC and hippocampus and projecting primarily to the hypothalamus- is ideally positioned to integrate cognitive information and, in turn, regulate motivated behaviors. Thus I characterized in mice a novel circuit by which hippocampal CA2 projections to LS result in disinhibition of an aggression-promoting nucleus of the hypothalamus. I also showed that vasopressin enhances aggression through presynaptic facilitation of CA2 inputs to LS. Using this study as a blueprint, I will determine the logic by which LS integrates and compute cognitive inputs to regulate other motivated behaviors. As motivated behaviors depend on internal states, I will also explore how modulatory inputs (vasopressin, dopamine, serotonin) from subcortical brain regions to LS can regulate its function. Finally, since hippocampus, PFC and LS are implicated in several psychiatric disorders associated with altered social behaviors (schizophrenia, autism or bipolar disorder), insights into how these regions regulate motivated behaviors are critical for understanding both basic neural mechanisms as well as how disease processes lead to altered social interactions. This project therefore also aims to unravel potential changes occurring in disorders associated with social behavioral deficits with the ultimate goal of providing new therapeutic targets for disease treatment. Thus my study may suggest new approaches to treat abnormal social cognition associated with psychiatric disorders.

Mots-clés : motivated behaviors,vasopressin,social aggression
Projet ERC : TWICEASGOOD (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : Spanish National Research Council — Pays : Espagne — Rôle : Partner
Acronyme de l'entité : CSIC
Type d'entité : Recherche
Financement ERC de l'entité : 38936.25 €

How does sexism affect women’s pathway to political office? Scholars have claimed that voter sexism is over because women candidates win elections at the same rate as men. However, the emergence of a gender equality backlash, misogynistic social media campaigns and the continued under-representation of women in political office globally, indicate a need to re-examine whether sexism acts as a barrier to women’s representation. To better understand political representation, therefore, it is important to understand how and under which conditions sexism by voters, media and political parties, actual and anticipated, can lead women candidates to alter campaign behavior and strategies. For the proposed programme of research in TWICEASGOOD, we reconceptualize the “gender penalty” faced by women candidates to take into account the sexism, threats of violence that they face online, through social media, in the traditional media and in face-to-face encounters. We aim to understand the extent of these types of sexism as well as the ways in which women candidates anticipate and counter them, by being “twice as good”, in order to achieve electoral success. To better understand how encounters of “everyday sexism” on the campaign trail, both online and offline and in the media, shape women’s campaign efforts and chances at electoral success, we propose an ambitious five-year programme of research that captures candidate experiences of sexism and assesses their impact on electoral outcomes. To capture how sexism is experienced “everyday” on the campaign trail, we used a mixed-methods approach, bringing together participant-observation of candidates on the campaign trail in four countries with quantitative media analysis, candidate surveys and a battery of items administered in Round 11 of the European Social Survey to create a cross-national sexism index. This rich data will generate new insights about the causes of women’s continued under-representation in politics.

Mots-clés : women,elections,campaigns,sexism,violence against women in politics,representation,social,media,news media,communication,attitudes
Projet ERC : TWICEASGOOD (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : University of Amsterdam — Pays : Pays-Bas — Rôle : Partner
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 66158.75 €

How does sexism affect women’s pathway to political office? Scholars have claimed that voter sexism is over because women candidates win elections at the same rate as men. However, the emergence of a gender equality backlash, misogynistic social media campaigns and the continued under-representation of women in political office globally, indicate a need to re-examine whether sexism acts as a barrier to women’s representation. To better understand political representation, therefore, it is important to understand how and under which conditions sexism by voters, media and political parties, actual and anticipated, can lead women candidates to alter campaign behavior and strategies. For the proposed programme of research in TWICEASGOOD, we reconceptualize the “gender penalty” faced by women candidates to take into account the sexism, threats of violence that they face online, through social media, in the traditional media and in face-to-face encounters. We aim to understand the extent of these types of sexism as well as the ways in which women candidates anticipate and counter them, by being “twice as good”, in order to achieve electoral success. To better understand how encounters of “everyday sexism” on the campaign trail, both online and offline and in the media, shape women’s campaign efforts and chances at electoral success, we propose an ambitious five-year programme of research that captures candidate experiences of sexism and assesses their impact on electoral outcomes. To capture how sexism is experienced “everyday” on the campaign trail, we used a mixed-methods approach, bringing together participant-observation of candidates on the campaign trail in four countries with quantitative media analysis, candidate surveys and a battery of items administered in Round 11 of the European Social Survey to create a cross-national sexism index. This rich data will generate new insights about the causes of women’s continued under-representation in politics.

Mots-clés : women,elections,campaigns,sexism,violence against women in politics,representation,social,media,news media,communication,attitudes
Projet ERC : REPLAY (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Universität Hamburg — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : UHH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1132116.0 €

How does the brain use past experiences to shape future actions? Over two decades ago, research in rodents has made a remarkable discovery that may provide key answers to this fundamental question. Researchers found that while rats were sleeping, activity in their hippocampus seemingly retraced the animals’ previous trajectories in a maze, only much faster than in real time. This phenomenon, known as replay, has become a major focus of neuroscientists and even artificial intelligence researchers over the past decades. The resulting research demonstrated that replay is prevalent during wakeful resting, related to memory, planning and reward processing, and shares similarities with machine learning algorithms. These findings suggest that replay may be a fundamental mechanism behind memory consolidation and the computation of optimal behavior. Yet, despite the significance of this phenomenon, little is known about replay in the human brain. The major reason for the lack of knowledge are difficulties to measure fast neural processes non-invasively in the human hippocampus. The main goal of the proposed research is to overcome these obstacles, and to provide deeper insights into replay in humans. To achieve this, we will use a novel fMRI analysis method that tests whether the transitions between successive fMRI patterns during rest or sleep exhibit non-random relations to the temporal structure of previous experiences. Using this approach, the proposed research will provide insights into four cognitive and computational aspects of replay in the human brain: (1) the coordination of hippocampal replay with activity in other brain areas, (2) the effects of reward and planning on content and direction of replay, (3) the role of replay during sleep and its relation to sleep spindles, and (4) its role in age-related memory decline. In combination, insights gained from this research promise to greatly enhance our understanding of how memories guide adaptive behavior in humans.

Mots-clés : cognitive neuroscience,cognitive computational neuroscience,fmri,decision making