Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SloMo (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Cultures and cultural production
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 : 1923190.0 €

Slow motion is widely employed in popular media such as emotional movie scenes or in the broad-casting of momentous bodily and physical actions. Slow motion functions as a counterpoint to the perceived acceleration of life, and non-profit organisations and meditation practices promote its virtues. Slow motion is used as a beneficial rehearsal strategy in music, dance, and other movement-based arts and sports. This research proposal shifts existing boundaries by hypothesizing that the time-stretching mechanism of slow motion is a) associated with high emotional significance, b) beneficial for interpersonal coordination, c) relevant in cross-modal approaches with augmented feedback such as the sonification of human movements, d) reduces cognitive working memory load in learning. It is assumed that music as a temporal-motional art is central for the study of these processes, since music consists of structured time at different hierarchical levels and deeply “moves” people. The musical surface structure (on a note-to-note level) allows synchronisations at higher tempi compared to deeper structural levels (such as strong beats in a measure or phrases). Music may thus transform perceptions of motion and time. The proposed project contains three main phases, first addressing the perception of slow motion in music and dance in relation to the attentional, emotional and aesthetic effects on the audience. In the second phase, performance qualities are studied, addressing cognitive load, imagery, and interpersonal coordination at slow tempi. High-speed cameras, a 3D motion capture system and physiological measures are used to analyse the psychological and bodily processes involved. The final phase aims at the creation of three applications, including a learning app for portable devices, a film with super slow motion sequences based on the studies, and sonifications of Tai Chi movements. These applications present the aesthetic dimensions of slow motion to a wider audience.

Mots-clés : psychology of music,systematic musicology,music perception and cognition,performance
Projet ERC : SmartEater (Horizon 2020, appel 2018, Proof of concept grants)
Entité participante : Salzburg University of Applied Sciences — Pays : Autriche — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 88750.0 €

Smartphones are ubiquitous in all age groups and socioeconomic levels and digitalization of various life domains is in full progress. While there are several areas where skepticism is justified, the personal health domain still holds high promises, particularly when applied in specific settings. The proposed mHealth app SmartEater provides intelligent mobile logging of stress, and eating behavior as a basis for intervention and follow-up care in clinics treating eating disorders and obesity. Current apps require frequent and cumbersome entries, resulting in low user adherence and poor data quality. Evidence for their usefulness is often missing. Further, therapeutic content is not personalized. In SmartEater, users repeatedly enter data on experienced craving for foods and stress. SmartEater then ‘learns’ from the user through sophisticated machine learning algorithms: data from smartphone usage patterns (e.g. screen-on time, calls, messages, internet traffic) and sensor data (e.g. movement, background noise) are combined to substitute for manual user input, thereby progressively reducing user burden. Temporal pattern analysis of individual time-series allows prediction of stress and craving bouts into the near future. Such predictions allows the app to respond to upcoming eating 'crises’ e.g. overeating/binge eating and launch situation-appropriate tips that have been developed individually for the user during in-patient treatment. SmartEater will be routed in psychological models of eating behavior and rigorously tested in the described population to evaluate efficacy. Due to the sensitive nature of such data, SmartEater enforces strict privacy protection. Targeted markets include health insurances which profit from improved patient health and successful transfer into daily life after professional treatment as well as clinics with an eating/weight disorder focus in German speaking coutries.

Mots-clés : smartphone app,prediction,stress,eating,ehealth,mhealth,machine learning,eating disorders,obesity
Projet ERC : NEOMENTO (Horizon 2020, appel 2017, Proof of concept grants)
Entité participante : German Center for Neurodegenerative Diseases — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : DZNE
Type d'entité : Recherche
Financement ERC de l'entité : 148403.0 €

Social anxiety disorder (SAD) – the most common type of anxiety disorders – has severe emotional, financial and social consequences for patients, their families and their social network. Affecting about 7% of Europeans at some point in their life, SAD produces substantial societal cost due to long lasting treatments and extensive periods of reduced working capacity. To address this important problem, the project will establish an innovative system for treating SAD by exploiting the proven therapeutic potential of advanced Virtual Reality (VR) technology. SAD is predominantly treated with cognitive behavioural therapy, in which patients are repeatedly exposed to fear-provoking, social situations. However, patients often have to wait very long before treatment becomes available, exposure is rarely applied with the necessary intensity due to resource limitations, and objective measurement of treatment efficacy and dynamic adjustment of therapeutic scenarios is hardly possible. These problems can be overcome with VR based, controlled exposure to virtual renditions of fear provoking situations, which has been shown to surpass traditional therapies in terms of treatment efficacy, patient acceptance, and economic efficiency. Given that advanced VR technology has become very affordable, a widespread application of VR for the treatment of SAD is now within reach. The proposed project will fuse the applicant’s extensive VR expertise with established principles for VR based therapy to create an innovative system for the treatment of SAD. This system will, for the first time, combine interactive 3D environments with external physiological measures (e.g eye tracking data) and real-time data analyses techniques to provide a precise, flexible and time and cost-efficient therapeutic approach. Established collaborations with clinical partners will allow for continuous testing and refinement of the system, thus ensuring that market readiness can be achieved within the funding period.

Mots-clés : virtual reality,exposure therapy,anxiety disorders,software development,physiological markers
Projet ERC : SocialNAc (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : University of Geneva — Pays : Suisse — Rôle : PI
Acronyme de l'entité : UNIGE
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1996424.0 €

Social behavior is defined as any modality of communication and interaction between two or more conspecifics. These behaviors, which include affiliative and antagonistic interactions, are exhibited by all sexually reproducing species, they are characterized by high-level complexity of communication through multiple sensory modalities and they are essential for survival. Humans and other animals living in groups continuously experience situations in which they need to select appropriate behavioral responses upon exposure to conspecifics. At the very basis of this social behavior, an individual needs to decide for example whether to approach (positive or appetitive) or avoid (negative or aversive) other individuals. Here, using mice, we will investigate the brain circuits and synaptic mechanisms involved in conspecific approach and avoidance behavior. The Nucleus Accumbens (NAc) is a key region of the mesocorticolimbic circuits for evaluating appetitive and aversive information. Recent studies have revealed the importance of NAc in social behavior, but which neurons within this structure are relevant and how they contribute to conspecific interaction is largely unknown. We hypothesize that different populations of neurons within the NAc orchestrate and integrate different types of socially relevant information to initiate the appropriate behavioral response. Using in vivo and ex vivo recordings and circuit-specific optogenetic manipulations in specific social interaction conditions, we will investigate how the NAc integrates information about conspecifics and how it incorporates learned associations to initiate conspecific approach or avoidance. This study will thus identify and functionally characterize the circuit and synaptic mechanisms controlling socially appetitive and aversive stimuli, and hence pave the way for a causal understanding of the processes underlying disruption of complex social behaviors in psychiatric disorders.

Mots-clés : social interactions,synaptic plasticity,nucleus accumbens
Projet ERC : ApeAttachment (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 1495000.0 €

Social bonding success in life impacts on health, survival and fitness. It is proposed that early and later social experience as well as heritable factors determine social bonding abilities in adulthood, although the relative influence of each is unclear. In humans, the resulting uncertainty likely impedes psychological and psychiatric assessment and therapy. One problem hampering progress for human studies is that social bonding success is hard to objectively quantify, particularly in adults. I propose to directly address this problem by determining the key influences on social bonding abilities in chimpanzees, our closest living relative, where social bonding success can be objectively quantified, and is defined as number of affiliative relationships maintained over time with high rates of affiliation. Objectives. This project will quantify the relative impact of early and later social experience as well as heritable factors on social hormone levels, social cognition and social bonding success in 270 wild and captive chimpanzees, using both cohort and longitudinal data. This will reveal the degree of plasticity in social cognition and bonding behaviour throughout life. Finally, it will evaluate the potential for using endogenous hormone levels as non-invasive biomarkers of social bonding success, as well as identifying social contexts that act as strong natural social hormone releasers. Outcomes. This project will expose what makes some better at social bonding than others. Specifically, it will show the extent to which later social experience can compensate for early social experience or heritable factors in terms of adult social bonding success, the latter being a key factor in determining health and happiness in life. This project also offers the potential for using hormonal biomarkers in clincial settings, as objective assessment of changes in relationships over time, and in therapy by engaging in social behaviours that act as strong social hormone releasers.

Mots-clés : early attachment,adult attachment,oxytocin,mentalizing,pragmatic communication,social bonds,chimpanzees
Projet ERC : YinYang (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Champalimaud Foundation — Pays : Portugal — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 1952188.0 €

Social interactions can take different courses depending on the internal state of the participants. For instance, a sexually receptive female mouse will allow a male’s attempt to mount her, but a non-receptive female will fight or flee the same male. Here, we propose to determine how neuronal circuits in the female mouse brain support flexible, state-dependent interactions with male conspecifics. It is known that female receptivity depends on the ventrolateral region of the ventromedial hypothalamus. Within this region there is a population of neurons that expresses receptors for the sex hormone progesterone (PR+ neurons), whose levels cycle with reproductive state. In pilot experiments, we found that PR+ neurons are not homogeneous: some respond during receptive behaviors but others respond during defensive or aggressive behaviors. Our main objective is to determine how female hypothalamic PR+ neurons participate in state-dependent behavioral responses to males. Our hypothesis is that two subpopulations of PR+ neurons are differentially modulated by the reproductive cycle and that each sub-population activates a different downstream circuit, one specialized for receptive and the other for defensive behaviors. Our specific aims are to: (1) characterize the functional selectivity of individual female PR+ neurons across the reproductive cycle; (2) map the connectivity of PR+ neurons to their output targets; (3) test the impact of different PR+ output pathways by genetically activating and silencing them; and (4) determine how reproductive hormones modulate the synaptic and intrinsic functional properties of PR+ neurons. These studies will elucidate the neuronal circuit mechanisms of a biologically essential female behavior. More broadly, this work will reveal mechanisms by which neuronal circuits can support flexible state-dependent adaptive behaviors.

Mots-clés : mice,sexual behavior,social behaviou,optogenetics,calcium imaging
Projet ERC : COLSOC (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : Comite national francais du c.t.i.f. — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 37500.0 €

Social protection has been one of the most popular instruments for promoting human development across the globe. However, the great majority of the global population is not or only partly covered by social protection. Especially in developing countries it is often the very poorest who do not receive essential social benefits. This is highly problematic since inclusive social protection is assumed to be a key factor for national productivity, global economic growth and domestic stability. Social protection in many developing countries can be traced back to colonial times. Surprisingly, the influence of colonialism has been a blind spot for existing theories and empirical studies of comparative social policy. In this project it is argued that the colonial legacy in terms of the imperial strategy of the colonial power, the characteristics of the colonized society and the interplay between the two is crucial in explaining early and contemporary social protection. Hence, the main objective of this project is to systematically understand how colonialism has shaped the remarkable differences in social protection and its postcolonial outcomes. Given the paucity of our information and understanding of social protection in former colonies, an interactive dataset on the characteristics, origins and outcomes of social protection will be developed including comprehensive data on former British and French colonies from the beginning of the 20th century until today. The dataset will be backed by insights derived from four case studies elucidating the causal mechanisms between the colonial legacy and early and contemporary social protection. The proposed project breaks new ground by improving our understanding of why social protection in some developing countries has led to more inclusive societies while reinforcing existing inequalities in others. Such an understanding is a prerequisite in informing the contemporary struggle against poverty and social inequality.
Projet ERC : RELEVANCE (Horizon 2020, appel 2019, Synergy grants)
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 : 2777250.0 €

Social species, and specifically human and nonhuman primates, rely heavily on conspecifics for survival. Considerable time is spent watching each other’s behavior because this is often the most relevant source of information for preparing adaptive social responses. The project RELEVANCE aims to understand how the brain evolved special structures to process highly relevant social stimuli like bodies and to reveal how social vision sustains adaptive behaviour. This requires a novel way of thinking about biological information processing, currently among the brains’ most distinctive and least understood characteristic that accounts for the biggest difference between brains and computers. The project will develop a mechanistic and computational understanding of the visual processing of bodies and interactions and show how this processing sustains higher abilities such as understanding intention, action and emotion. Relevance will accomplish this by integrating advanced methods from multiple disciplines: psychophysics and high-field functional imaging in combination with virtual reality and neural stimulation in humans; electrophysiology with optogenetics and laminar recordings in monkeys. Crosstalk between human and monkey methods will establish homologies between the species, revealing cornerstones of the theory. In a radical departure from current practice, we will develop novel deep neural network models that unify the data. These models will not only capture detailed mechanisms of neural processing of complex social stimuli and its dynamics, but also reproduce the modulation of brain activity during active behavior. RELEVANCE will reveal novel ways of understanding and diagnosing social communication deficits in neuropsychiatry, and suggest novel hypotheses about their genetic basis. It will motivate novel principles and architectures for processing of socially relevant information in computer and robotic systems.

Mots-clés : social vision,body representation,high level vision,neural modeling
Projet ERC : MOLEMAT (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Basque Center for Materials, Applications and Nanostructures — Pays : Espagne — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 1878085.0 €

Societal pressure to develop inexpensive yet efficient solar energy conversion requires a new approach. Recently emerged organic-inorganic perovskites, offer to harvest light at cost effective price. Perovskites hold merits to the existing materials, however, a fundamental challenge for high performance devices is to optimize the crystals for maximize charge carrier generation and minimize recombination losses. Their widespread use is, however, limited by insufficient stability, scalability and reproducibility. We have recently developed new concepts to fabricate efficient and stable perovskite solar cells at lab scale that are potentially up-scalable to industrial production. MOLEMAT will accomplish this by, pioneering innovative methods and will demonstrate that molecularly engineered materials enable the tuning of the charge transport and interface. Our interdisciplinary approach, combining materials science, chemistry, device physics and engineering, will not only lead to improvements in the performance and stability of perovskite solar cell beyond 24% at lab scale, but will also provide deep insights in the functioning of solar cells. The success of MOLEMAT will rapidly advance the field by enabling reproducible and stable performance adding a significant value with respect to current state of the art. However, for making it marketable product, several developments are required and the MOLEMAT targets will provide relevant answers to three key limitations: encapsulation, stability and cost competitive materials. MOLEMAT envisages the development of 30×30 cm2 modules, with a power conversion efficiency of c.a 18% and a lifetime of 10+ years. MOLEMAT is divided into two parallel research directions, a fundamental research line, dealing with rational design of materials and to gain its understanding. Simultaneously an applied research line targets the development of module by the identification of scale up process to pave the way for its industrialization.

Mots-clés : photovoltaics,perovskites,electro optical properties
Projet ERC : AutoCode (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : Technion – Israel Institute of Technology — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Software synthesis aims to automate the creation of software by generating parts of software from a higher-level description. Until recently it was believed to be impossible to practically synthesize software beyond very small fragments. However, synthesis based on learning from existing large code-bases (“Big Code”) is making synthesis into a practical reality . The purpose of this PoC is to develop a platform that would lead to commercialization of our technology to improve programming productivity and code quality. We target two closely related applications: (1) Providing automatic assistance in programming tasks by learning from existing code, and (2) Providing on-line assessment of code quality as it is being developed using learned models. These applications have the potential to dramatically reduce time-to-market of new software, and improve its quality and security.

Mots-clés : programming questions,semantic code search,big code,program analysis,static analysis,computer programming