Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : PrAud (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Maastricht University — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1824962.5 €

How do we understand the complex, noisy, and often incomplete sounds that reach our ears? Sounds are not perceived in isolation. The context in which we encounter them allows predicting what we may hear next. How is contextual sound processing implemented in the brain? From the sensory periphery to the cortex, complex information is extracted from the acoustic content of sounds. This feedforward processing is complemented by extensive feedback (FB) processing. Current research suggests that FB confers flexibility to auditory perception, by generating predictions of the input and supplementing noisy or missing information with contextual information. So far, limitations in coverage and spatial resolution of non-invasive imaging methods have prohibited grounding contextual sound processing onto the fundamental computational units of the human brain, resulting in an incomplete understanding of its biological underpinnings. Here, I propose to use ultra-high-field (UHF) functional magnetic resonance imaging (fMRI) to study how expectations shape human hearing. The high spatial resolution and coverage of UHF-fMRI will allow examining fundamental brain units: small subcortical structures and layers of cortex. I will investigate how responses change when acoustic information needs to be prioritized in an uncertain or noisy soundscape. Complementing UHF-fMRI measurements with magnetoencephalography (MEG), I will derive a neurobiological model of contextual sound processing at high spatial and temporal resolution. By comparing this model to state-of-the-art artificial intelligence, I will generalize it to naturalistic settings. This project links algorithmic and at a mesoscopic implementation levels to reveal the neurobiological mechanisms supporting hearing in context. The resulting model will allow testing hypotheses of aberrant contextual processing in phantom hearing (tinnitus and auditory hallucinations).

Mots-clés : audition,contextual processing,predictive coding,ultra high field fmri,cortical layers,subcortical processing,computational modelling
Projet ERC : PrAud (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Radboud University Nijmegen — Pays : Pays-Bas — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 75037.5 €

How do we understand the complex, noisy, and often incomplete sounds that reach our ears? Sounds are not perceived in isolation. The context in which we encounter them allows predicting what we may hear next. How is contextual sound processing implemented in the brain? From the sensory periphery to the cortex, complex information is extracted from the acoustic content of sounds. This feedforward processing is complemented by extensive feedback (FB) processing. Current research suggests that FB confers flexibility to auditory perception, by generating predictions of the input and supplementing noisy or missing information with contextual information. So far, limitations in coverage and spatial resolution of non-invasive imaging methods have prohibited grounding contextual sound processing onto the fundamental computational units of the human brain, resulting in an incomplete understanding of its biological underpinnings. Here, I propose to use ultra-high-field (UHF) functional magnetic resonance imaging (fMRI) to study how expectations shape human hearing. The high spatial resolution and coverage of UHF-fMRI will allow examining fundamental brain units: small subcortical structures and layers of cortex. I will investigate how responses change when acoustic information needs to be prioritized in an uncertain or noisy soundscape. Complementing UHF-fMRI measurements with magnetoencephalography (MEG), I will derive a neurobiological model of contextual sound processing at high spatial and temporal resolution. By comparing this model to state-of-the-art artificial intelligence, I will generalize it to naturalistic settings. This project links algorithmic and at a mesoscopic implementation levels to reveal the neurobiological mechanisms supporting hearing in context. The resulting model will allow testing hypotheses of aberrant contextual processing in phantom hearing (tinnitus and auditory hallucinations).

Mots-clés : audition,contextual processing,predictive coding,ultra high field fmri,cortical layers,subcortical processing,computational modelling
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 London — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 26463.61 €

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 Exeter — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2241473.96 €

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 : Max Planck Society — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 271005.0 €

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
Projet ERC : REPLAY (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : University of Oxford — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 13385.0 €

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
Projet ERC : HumanPlacenta (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : University of Cambridge — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : U. Cambridge
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 95693.91 €

How does the human placenta develop and how is this influenced by the maternal uterine microenvironment? These are the central questions addressed in my proposal. Normal growth and development of the fetus depends on the placenta, the extra-embryonic organ derived from trophectoderm. Successful pregnancy depends on the earliest stages of development when placental extravillous trophoblast cells (EVT) infiltrate the uterine mucosa, the decidua. EVT invade the decidua to transform the uterine spiral arteries into a dilated vessel capable of high conductance. Deficient arterial remodelling by EVT results in miscarriage, pre-eclampsia, fetal growth restriction and stillbirth. However, excessive invasion into the uterine wall is also potentially dangerous. Thus, to achieve a successful pregnancy, a territorial boundary is drawn with a balance between fetal EVT invasion and maternal decidual cells. Understanding the molecular and cellular mechanisms underlying these maternal/fetal interactions has been challenging due both to practical and ethical limitations and lack of reliable in vitro models. I have recently derived 3D culture systems (organoids) from human decidua and placenta that will provide the essential tools. I will use these organoids combined with single cell genomics, Crispr/Cas9 genome editing and tissue engineering to study: (i) the molecular mechanisms that specify the EVT lineage (ii) the role of paracrine signalling from maternal decidual glands in regulating placental development (iii) cell-cell interactions between decidua and EVT by creating an artificial model of decidua made from tailored collagen scaffolds seeded with stromal, glandular and immune cells. My proposal capitalises on the remarkable ability of organoid cultures to faithfully model human physiology. The human uterine environment in early pregnancy is crucial for reproductive success and development of an in vitro model of placentation will have a wide-ranging impact.

Mots-clés : human placenta,reproduction,trophoblast,differentiation
Projet ERC : COTCA (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : University of Nottingham — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1885268.0 €

How has foreign occupation shaped culture? What has been the lasting cultural legacy of foreign occupation in those societies where it represented the usual state of affairs for much of the modern era? These are key questions which, in light of ongoing cases of occupation around the world, remain crucial in the 21st century. Cultures of Occupation in Twentieth-century Asia (COTCA) will answer these questions by analysing how occupation―be it under colonial, wartime or Cold War powers―gave rise to unique visual, auditory and spatial regimes in East and Southeast Asia. The core objective of this important project is to produce a paradigm shift in the study of occupation, and to challenge the 'collaboration'/'resistance' dichotomy which has defined the field thus far. It will adopt a transnational, intertextual and comparative approach to the study of cultural expression produced under occupation from the 1930s to the 1970s. It will also break new methodological ground by drawing on and contributing to recent developments in visual, auditory and spatial history as a means of highlighting intersections and cultural convergences across different types of occupation. By doing so, COTCA will, for the first time, determine what occupation looked, sounded and felt like in twentieth-century Asia. The COTCA team will consist of the PI, 2 postdoctoral researchers and 3 PhD students, and will run along 3 streams: (i) Representations of occupation; (ii) sounds of occupation; and (iii) spaces of occupation. Case studies based on hitherto rarely examined examples will be undertaken in each stream. These include: A visual history of Japanese-occupied China; soundscapes of the US naval bases in the Philippines; and, spaces of occupation in late-colonial Malaya. COTCA will also build a Digital Archive which will enable researchers to trace the development of narratives, tropes and motifs common to 'occupation' cultural expression in Asia across national and temporal borders.

Mots-clés : occupation,cultural expression,east asia,southeast asia
Projet ERC : MEDIACHINA (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Stockholm University — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1716970.0 €

How is political accountability and firm performance in an autocracy affected by media? This project will analyse how economic and political outcomes in China are affected by social and traditional media. It will also use media content to measure factors that are otherwise difficult to observe, such as political networks and the trade-off between political and economic goals in Chinese firms. An explosion of social media use in China has produced an information shock to society and its leaders, also supplying a data shock to researchers, which is magnified by the digitization of traditional media content, and coupled with new methods for analysing this type of data, originating from the in big data and machine-learning literatures. As a result, a large set of previously unanswerable questions are now open for research. In Qin, Strömberg and Wu (2016) we document this information shock, using a data set of over 13 billion social media posts from Sina Weibo (the Chinese equivalent of Twitter). We show that millions of posts concern sensitive topics such as organized protests and explicit accusations of top leaders of corruption. Traditional media is silent on these issues. We argue that the likely reason for the lighter censoring of social media is that the central government finds the information useful for monitoring officials, firms, and citizen unrest. In this project, I will analyze the effect of this information shock on protests and strikes, the sales of counterfeit and substandard medicines, the promotion of local leaders, and coverage of censored events in traditional media. Together with a set of collaborator, I will study the effects of social media using the staggered introduction of Sina Weibo across geographic regions. I will also study the content, entry and exit of general-interest newspapers that are all controlled by different politicians. This is to investigate the trade-off between political and economic goals and political connections.

Mots-clés : political economics,media,china
Projet ERC : PHENOVIGOUR (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1495182.0 €

How organismal traits are inherited in offspring is a long-standing, open question. Hybrids between unrelated individuals of plants or animals often show greater vigour, disease resistance, and fertility. The genetic mechanisms behind the deviation of hybrids from the parental phenotype have been widely studied. However, hybrid vigour remains difficult to predict qualitatively and quantitatively. A key bottleneck is that it remains difficult to explain why different traits are inherited differently. I will overcome this bottleneck to explain trait inheritance and predict hybrid vigour in crop plants from a phenotypic stand point. I will do this by bridging old evolutionary principles with modern models of ecological theory, via the following three objectives: 1. Determining whether in hybrids the degree of trait deviation from the parental phenotype increases with the degree of trait integration; 2. Testing whether modelling relationships between traits can quantitatively explain hybrid vigour; and 3. Building a predictive model of hybrid performance in the field. My project will build on a combination of comparative, experimental and modelling approaches, and a large collection of available phenotypic data in crop plants. In addition, I will use cutting-edge phenotyping facilities to test underlying hypotheses on two experimental species: maize (Zea mays) and sorghum (Sorghum bicolor). The novel hypothesis is that deviation of a trait in a hybrid is the geometric result of the nonlinear effects of traits at lower levels of integration. The objectives are designed to provide a timely breakthrough in the fundamental understanding of variation in trait inheritance. Further, my approach will also enable predictive models of hybrid performance in crop plants to be developed, which would be an outstanding tool for breeders.

Mots-clés : hybrid,heterosis,trait relationships,phenotypic integration,nonlinearity,trait inheritance,allometry,trade off,predictive model