Décoder la localisation de l'attention visuelle spatiale grâce au signal EEG

L’attention visuo-spatiale peut être déployée à différentes localisations dans l’espace indépendamment de la direction du regard, et des études ont montré que les composantes des potentiels reliés aux évènements (PRE) peuvent être un index fiable pour déterminer si celle-ci est déployée dans le champ visuel droit ou gauche. Cependant, la littérature ne permet pas d’affirmer qu’il soit possible d’obtenir une localisation spatiale plus précise du faisceau attentionnel en se basant sur le signal EEG lors d’une fixation centrale. Dans cette étude, nous avons utilisé une tâche d’indiçage de Posner modifiée pour déterminer la précision avec laquelle l’information contenue dans le signal EEG peut nous permettre de suivre l’attention visuelle spatiale endogène lors de séquences de stimulation d’une durée de 200 ms. Nous avons utilisé une machine à vecteur de support (MVS) et une validation croisée pour évaluer la précision du décodage, soit le pourcentage de prédictions correctes sur la localisation spatiale connue de l’attention. Nous verrons que les attributs basés sur les PREs montrent une précision de décodage de la localisation du focus attentionnel significative (57%, p<0.001, niveau de chance à 25%). Les réponses PREs ont également prédit avec succès si l’attention était présente ou non à une localisation particulière, avec une précision de décodage de 79% (p<0.001). Ces résultats seront discutés en termes de leurs implications pour le décodage de l’attention visuelle spatiale, et des directions futures pour la recherche seront proposées.Visuospatial attention can be deployed to different locations in space independently of ocular fixation, and studies have shown that event-related potential (ERP) components can effectively index whether such covert visuospatial attention is deployed to the left or right visual field. However, it is not clear whether we may obtain a more precise spatial localization of the focus of attention based on the EEG signals during central fixation. In this study, we used a modified Posner cueing task with an endogenous cue to determine the degree to which information in the EEG signal can be used to track visual spatial attention in presentation sequences lasting 200 ms. We used a machine learning classification method to evaluate how well EEG signals discriminate between four different locations of the focus of attention. We then used a multi-class support vector machine (SVM) and a leave-one-out cross-validation framework to evaluate the decoding accuracy (DA). We found that ERP-based features from occipital and parietal regions showed a statistically significant valid prediction of the location of the focus of visuospatial attention (DA = 57%, p < .001, chance-level 25%). The mean distance between the predicted and the true focus of attention was 0.62 letter positions, which represented a mean error of 0.55 degrees of visual angle. In addition, ERP responses also successfully predicted whether spatial attention was allocated or not to a given location with an accuracy of 79% (p < .001). These findings are discussed in terms of their implications for visuospatial attention decoding and future paths for research are proposed

Décodage des mécanismes cérébraux de la prise de décision chez l’humain

Choisir entre plusieurs actions possibles afin d’interagir avec son environnement constitue l’un des piliers fondamentaux du comportement chez l’animal, y compris l’humain, à travers l’évolution. Pour comprendre comment le cerveau détecte, distingue et catégorise l’information qui parvient à nos sens pour prendre une décision informée, plusieurs théories ont émergé dans le domaine des neurosciences cognitives. L’objectif de cette thèse est d’identifier les mécanismes neuronaux à l’origine de la prise de décision chez l’humain afin d’étoffer les connaissances théoriques existantes sur la manière dont notre cerveau parvient à délibérer, puis choisir entre plusieurs alternatives. Afin d’y parvenir, nous avons combiné l’utilisation de techniques électrophysiologiques et d’analyses d’apprentissage machine avancées pour analyser l’activité cérébrale pendant la réalisation de tâches décisionnelles. Dans le premier article, nous avons utilisé l’électroencéphalogramme (EEG) intracrânien pour enregistrer l’activité neuronale de patients épileptiques alors qu’ils devaient choisir librement entre deux actions de valeur égale (droite ou gauche). Nous avons ainsi pu montrer qu’une augmentation soutenue de l’activité neuronale haute fréquence dans un réseau de régions cérébrales frontales et pariétales permettaient de caractériser le processus de délibération lors d’un choix libre chez l’humain. Pour aller plus loin, nous avons ensuite identifié les mécanismes cérébraux à l’origine des choix pris dans des situations plus écologiques où l’évidence sensorielle fluctue dynamiquement au cours du temps. Dans cette deuxième tâche les participants sont libres de répondre à n’importe quel moment pour essayer d’optimiser leur taux de succès en implémentant des règles qui permettent d’ajuster le compromis entre vitesse et précision. En mesurant l’activité MEG de ces participants pendant qu’ils réalisaient une tâche de décision dynamique, nous avons utilisé une technique de réduction de dimensionalité (ACP, Analyse en Composantes Principales) afin d’identifier et de caractériser les composantes spatiales, temporelles et spectrales de l’activité neuronale sous-tendant les processus principaux de la prise de décision. Nous avons montré (1) le rôle d’un réseau de régions sensorimotrices et visuelles dans l’encodage de l’évidence sensorielle lors du processus de délibération entre plusieurs alternatives, ainsi que (2) que l’engagement dans un choix donné est reflété par les oscillations alpha (9-13 Hz) dans du cortex cingulaire postérieur et des régions visuelles (3) que l’exécution du mouvement permettant d’exprimer ce choix est sous-tendu par les oscillations beta (16-24 Hz) au sein des régions motrices et prémotrices et enfin (4) un ajustement du compromis entre vitesse/précision, caractérisé par l’activité haute fréquence dans les aires sous-corticales comprenant les ganglions de la base, le noyaux caudé, le cervelet et le thalamus . Dans leur ensemble, les résultats de cette thèse ont permis d’identifier et de caractériser les composantes spatiales, temporelles et fréquentielles de l’activité neuronale à l’origine de la prise de décision entre plusieurs actions chez l’humain.Choosing between potential actions to interact with the environment is one of the fundamental pillars of behavior in animals, including humans. To understand how the brain detects, discriminates, and categorizes information from the senses to make an informed decision, a class of theories have emerged in the field of cognitive neuroscience. The goal of this thesis is to identify neural mechanisms underlying decision-making in humans to extend theoretical accounts on how the brain can deliberate and chose among multiple alternatives. To do so, we combined electrophysiological recordings and machine learning to analyze brain activity from participants performing decision-making tasks. In the first article, we used intracranial EEG to record neuronal activity from epileptic patients while they had to freely choose between two actions of equal value (right or left saccades). We found a sustained increase in high frequency neuronal activity in a network of frontoparietal areas specific to the deliberation process during free choice in humans. We then set out to identify neuronal mechanisms subserving decisions between actions in conditions approaching ecological situations, in which sensory evidence can dynamically change over time, and participants are free to decide at any time to try and optimize successes per unit time by implementing speed accuracy tradeoff policies. By measuring MEG activity from participants performing such dynamic decision-making task and using a dimensionality reduction technique (PCA, Principal Component Analysis), we revealed and characterized the spatial, temporal, and spectral components of neural activity underlying the key processes contributing to decision-making. We showed that alpha (9-13 Hz) and beta (16-24 Hz) principal components (PCs) are involved in tracking sensory information while participants were deliberating between two options in the sensorimotor, visual, and posterior cingulate cortex. We also highlighted the role of alpha PCs in committing to a particular choice, while beta PCs were associated with motor execution once the decision was made. Finally, high frequency PCs (> 16 Hz) in subcortical areas including the cerebellum, pallidum, caudate nucleus and the thalamus indexed the implementation and adjustments of speed accuracy tradeoff policies when participants to try to optimize successes per unit time. Overall, results from this thesis successfully characterized the spatial, temporal, and spectral components of neuronal activity involved in deciding between actions in humans

Dermal fin rays and scales derive from mesoderm, not neural crest

SummaryNeural crest cells disperse throughout the embryonic head to generate diverse cell types of two classes: non-ectomesenchymal (including melanocytes, peripheral neurons and glia) and ectomesenchymal (skeletogenic, odontogenic, cartilaginous and connective tissue cell fates). In contrast to cranial neural crest, trunk neural crest of amniotes generates only non-ectomesenchymal cell types. Anamniote trunk neural crest, however, has been assumed to generate derivatives of both classes, including osteoblasts of dermal skeletal elements, which includes scales and fin rays. Through genetic lineage tracing in zebrafish, we present the first test of this assumption and find that trunk neural crest does not generate fin osteoblasts; rather, these derive from a late emerging population of paraxial mesoderm. Similarly we show that the mineralising cells of the scales are mesodermally derived, with no contribution from neural crest. Our data suggest that trunk/tail exoskeletal structures evolved through deployment of mesodermally derived mesenchyme, rather than neural crest

Estimation of landslides activities evolution due to land–use and climate change in a Pyrenean valley

International audienceGlobal changes would have impacts worldwide, but their effects should be even more exacerbated in areas particularly vulnerable. Mountainous areas are among these vulnerable territories. Ecological systems are often at a fragile equilibrium, socio-economical activities are often climate-dependent and climate-driven natural hazards can be a major threat for human activities. In order to estimate the capacity of such mountainous valleys to face global changes (climate, but also climate-and human-induced land-use changes), it is necessary to be able to evaluate the evolution of the different threats. The present work shows a method to evaluate the influences of the evolution of both vegetation cover and climate on landslides activities over a whole valley until 2100, to propose adequate solutions for current and future forestry management. Firstly, the assessment of future land use is addressed through the construction of four prospective socioeconomic scenarios up to 2050 and 2100, which are then spatially validated and modeled with LUCC models. Secondly, the climate change inputs of the project correspond to 2 scenarios of emission of greenhouse gases. The used simulations available on the portal DRIAS (http://www.drias-climat.fr) were performed with the GHG emissions scenarios (RCP: Representative concentration pathways, according to the standards defined by the GIEC) RCP 4.5 and RCP 8.5. The impact of land use and climate change is then addressed through the use of these scenarios into hazards computations. For that we use a large-scale slope stability assessment tool ALICE which combines a mechanical stability model (using finite slope analysis), a vegetation module which interfere with the first model, to take into account the effects of vegetation on the mechanical soil properties (cohesion and overload), and an hydrogeologi-cal model. All these elements are interfaced within a GIS-based solution. In that way, future changes in temperature, precipitation and vegetation cover are analyzed, permitting to address the direct and indirect impacts of global change on mountain societies. The whole chain is applied to a 100-km 2 Pyrenean Valley, for the ANR Project SAMCO (Society Adaptation for coping with Mountain risks in a global change COntext), as a first step in the chain for risk assessment for different climate and economical development scenarios, to evaluate the resilience of mountainous areas

Cooperative AI via Decentralized Commitment Devices

Credible commitment devices have been a popular approach for robust multi-agent coordination. However, existing commitment mechanisms face limitations like privacy, integrity, and susceptibility to mediator or user strategic behavior. It is unclear if the cooperative AI techniques we study are robust to real-world incentives and attack vectors. However, decentralized commitment devices that utilize cryptography have been deployed in the wild, and numerous studies have shown their ability to coordinate algorithmic agents facing adversarial opponents with significant economic incentives, currently in the order of several million to billions of dollars. In this paper, we use examples in the decentralization and, in particular, Maximal Extractable Value (MEV) (arXiv:1904.05234) literature to illustrate the potential security issues in cooperative AI. We call for expanded research into decentralized commitments to advance cooperative AI capabilities for secure coordination in open environments and empirical testing frameworks to evaluate multi-agent coordination ability given real-world commitment constraints.Comment: NeurIPS 2023- Multi-Agent Security Worksho

Using Jupyter for reproducible scientific workflows

Funding: This work was financially supported by the OpenDreamKit Horizon 2020 European Research Infrastructure project (676541) and the EPSRC Programme grant on Skyrmionics (EP/N032128/1).Literate computing has emerged as an important tool for computational studies and open science, with growing folklore of best practices. In this work, we report two case studies - one in computational magnetism and another in computational mathematics - where a dedicated software was exposed into the Jupyter environment. This enabled interactive and batch computational exploration of data, simulations, data analysis, and workflow documentation and outcome in Jupyter notebooks. In the first study, Ubermag drives existing computational micromagnetics software through a domain-specific language embedded in Python. In the second study, a dedicated Jupyter kernel interfaces with the GAP system for computational discrete algebra and its dedicated programming language. In light of these case studies, we discuss the benefits of this approach, including progress towards more reproducible and re-usable research results and outputs, notably through the use of infrastructure such as JupyterHub and Binder.PostprintPeer reviewe

P-576: Differential effects of selective cyclooxygenase-2 inhibitors on endothelial function in salt-induced hypertension

In view of the ongoing controversy of potential differences in cardiovascular safety of selective COX-2 inhibitors (coxibs), we compared the effects of two different coxibs and a traditional NSAID on endothelial dysfunction, a well established surrogate of cardiovascular disease, in salt-induced hypertension. Salt-sensitive (DS) and salt-resistant (DR) Dahl rats were treated with a high-sodium diet (4% NaCl) for 56 days. From days 35 to 56, diclofenac (6 mg/kg/d; DS-diclofenac), rofecoxib (2 mg/kg/d; DS-rofecoxib), celecoxib (25 mg/kg/d; DS-celecoxib) or placebo (DS-placebo) were added to the chow. Vascular reactivity of isolated aortic rings was assessed by isometric tension recording. Blood pressure increased with high sodium diet in the DS-groups which was more pronounced after diclofenac and rofecoxib treatment (p<0.005 vs DS-placebo), but slightly blunted by celecoxib (p<0.001 vs DS-placebo). Sodium diet markedly reduced NO-mediated endothelium-dependent relaxations to acetylcholine (ACh, 10−10−10−5 mol/L) in untreated hypertensive rats (p<0.0001 vs DR-placebo). Relaxation to ACh improved after celecoxib (p<0.005 vs DS-placebo and DS-rofecoxib), but remained unchanged after rofecoxib and diclofenac treatment. Vasoconstriction after NOS inhibition with Nω-Nitro-L-Arginine Methyl Ester (10-4 mol/L) was blunted in DS rats (p<0.05 vs DR-placebo), normalized by celecoxib, but not affected by rofecoxib or diclofenac. Protein expression of eNOS was decreased in DS rats with a trend for increased eNOS levels in the DS-celecoxib group (97.8±25.6 vs 54.8±2.8 %, p=0.088 vs DS-placebo). Indicators of oxidative stress, 8-isoprostane levels, were elevated in untreated DS rats on 4% NaCl (6.55±0.58 vs 3.65±1.05 ng/ml, p<0.05) and normalized by celecoxib only (4.29±0.58 ng/ml), while SOD protein expression was decreased in DS rats and not affected by any treatment. Plasma levels of prostaglandines did not change during high sodium diet or any treatment. These data show that celecoxib, but not rofecoxib or diclofenac, improves endothelial dysfunction and reduces oxidative stress, thus pointing to differential effects of coxibs in salt-sensitive hypertension. Am J Hypertens (2004) 17, 243A-243A; doi: 10.1016/j.amjhyper.2004.03.65

Capturing and indexing rehearsals: the design and usage of a digital archive of performing arts

Preserving the cultural heritage of the performing arts raises difficult and sensitive issues, as each performance is unique by nature and the juxtaposition between the performers and the audience cannot be easily recorded. In this paper, we report on an experimental research project to preserve another aspect of the performing arts—the history of their rehearsals. We have specifically designed non-intrusive video recording and on-site documentation techniques to make this process transparent to the creative crew, and have developed a complete workflow to publish the recorded video data and their corresponding meta-data online as Open Data using state-of-the-art audio and video processing to maximize non-linear navigation and hypervideo linking. The resulting open archive is made publicly available to researchers and amateurs alike and offers a unique account of the inner workings of the worlds of theater and opera

Hair Cortisol Concentration in Healthy Children and Adolescents Is Related to Puberty, Age, Gender, and Body Mass Index

Introduction: Hair cortisol concentrations (HCC) have been found to be related to various common childhood diseases, like otitis media, conjunctivitis, respiratory viral infections, and asthma. However, the confounding effects of age, gender, body mass index (BMI), pubertal stage (Tanner stages), socioeconomic status (SES) as well as of some hair maintenance procedures on HCC are still not well examined. Methods: A population-based cohort of 434 children aged between 5 and 18 years was examined for HCC between January 2012 and February 2015 in the context of the Leipzig Research Centre for Civilization Diseases (LIFE) Child study. Thereby, anthropometric data, gender, BMI, SES and pubertal status were assessed. HCC was measured by liquid chromatography mass spectrometry. Results: In the total cohort, HCC levels ranged between 0.95 and 29.86 pg/mg. In prepuberty, boys showed significantly higher HCC than girls (6.54 vs. 3.73 pg/mg, p < 0.05). During puberty HCC values in both genders converged. Higher BMI was significantly associated with higher HCC in both genders. In girls, HCC did not differ depending on Tanner stages. In boys, HCC was significantly higher in Tanner stage 1 than in stages 2–5. Conclusion: Measuring cortisol concentration in hair gives information about long-term release of cortisol. We have found that puberty, gender, and BMI had a profound effect on HCC. As a result, further research should take into account the potentially confounding role of puberty, gender and BMI and may use the results of our study as a reference at determining values of HCC in healthy children

Force measurements in E-cadherin–mediated cell doublets reveal rapid adhesion strengthened by actin cytoskeleton remodeling through Rac and Cdc42

We have used a modified, dual pipette assay to quantify the strength of cadherin-dependent cell–cell adhesion. The force required to separate E-cadherin–expressing paired cells in suspension was measured as an index of intercellular adhesion. Separation force depended on the homophilic interaction of functional cadherins at the cell surface, increasing with the duration of contact and with cadherin levels. Severing the link between cadherin and the actin cytoskeleton or disrupting actin polymerization did not affect initiation of cadherin-mediated adhesion, but prevented it from developing and becoming stronger over time. Rac and Cdc42, the Rho-like small GTPases, were activated when E-cadherin–expressing cells formed aggregates in suspension. Overproduction of the dominant negative form of Rac or Cdc42 permitted initial E-cadherin–based adhesion but affected its later development; the dominant active forms prevented cell adhesion outright. Our findings highlight the crucial roles played by Rac, Cdc42, and actin cytoskeleton dynamics in the development and regulation of strong cell adhesion, defined in terms of mechanical forces