Does the Integration of Haptic and Visual Cues Reduce the Effect of a Biased Visual Reference Frame on the Subjective Head Orientation?

The selection of appropriate frames of reference (FOR) is a key factor in the elaboration of spatial perception and the production of robust interaction with our environment. The extent to which we perceive the head axis orientation (subjective head orientation, SHO) with both accuracy and precision likely contributes to the efficiency of these spatial interactions. A first goal of this study was to investigate the relative contribution of both the visual and egocentric FOR (centre-of-mass) in the SHO processing. A second goal was to investigate humans' ability to process SHO in various sensory response modalities (visual, haptic and visuo-haptic), and the way they modify the reliance to either the visual or egocentric FORs. A third goal was to question whether subjects combined visual and haptic cues optimally to increase SHO certainty and to decrease the FORs disruption effect.Thirteen subjects were asked to indicate their SHO while the visual and/or egocentric FORs were deviated. Four results emerged from our study. First, visual rod settings to SHO were altered by the tilted visual frame but not by the egocentric FOR alteration, whereas no haptic settings alteration was observed whether due to the egocentric FOR alteration or the tilted visual frame. These results are modulated by individual analysis. Second, visual and egocentric FOR dependency appear to be negatively correlated. Third, the response modality enrichment appears to improve SHO. Fourth, several combination rules of the visuo-haptic cues such as the Maximum Likelihood Estimation (MLE), Winner-Take-All (WTA) or Unweighted Mean (UWM) rule seem to account for SHO improvements. However, the UWM rule seems to best account for the improvement of visuo-haptic estimates, especially in situations with high FOR incongruence. Finally, the data also indicated that FOR reliance resulted from the application of UWM rule. This was observed more particularly, in the visual dependent subject. Conclusions: Taken together, these findings emphasize the importance of identifying individual spatial FOR preferences to assess the efficiency of our interaction with the environment whilst performing spatial tasks

Towards a spatial theory of interaction networks in ecology : methods, concepts and applications

Cette thèse s’intéresse aux liens entre réseaux d’interactions en écologie, espace et temps. On assiste à un changement croissant de représentation d’un communauté d’espèces, d’un ensemble d’espèces à un ensemble d’espèces et leurs interactions : un réseau d’interactions. On s’attachera alors à élaborer les prémisses d’une théorie spatiale des réseaux, en développant des méthodes, des modèles et en les appliquant sur des données écologiques. La thèse s’articule autour de quatre chapitres. Dans un premier chapitre, on se penchera sur le problème de comparaison de réseau en différents points du temps et de l’espace. Nous étendrons les mesures de diversité, jusque-là développées pour des abondances uniquement, aux réseaux avec abondances des espèces et des interactions. Nous nous attacherons à définir des indices à plusieurs niveaux d’agrégation des noeuds dans le réseau et montrerons l’intérêt de la méthode sur des données de réseaux trophiques. Dans un deuxième chapitre, nous nous intéresserons au développement d’une théorie des méta-communautés qui modélise explicitement l’espace comme un réseau spatial et la communauté comme un réseau d’interaction. Nous définirons la notion de capacité de persistance de la méta-communauté. Dans un troisième chapitre, nous nous intéresserons aux problèmes d’inférence d’interactions sur des données de sol d’ADN environnemental le long d’un gradient d’altitude dans les Alpes. Nous montrerons que la méthode proposée permet d’estimer l’influence des variables environnementales et de reconstruire un réseau d'interaction cohérent vis-à-vis de la littérature. Dans un quatrième chapitre, nous nous intéresserons à la combinaison d’abondances provenant de différents marqueurs d’ADN environemental et montrerons l’efficacité de la méthode proposée pour obtenir des meilleurs données d’abondances sur des données de plantes.This thesis focuses on the links between interaction networks, space and time. There is a paradigm shift in community ecology concerning the representation of a species community : from a collection of species towards species and their interactions, represented by an interaction network. We aim to build the bricks for a spatial network theory, by developing new methods, new models and applying it on ecological data. This manuscript contains four chapters. In a first chapter, we extend the diversity indices, built on Hill numbers, to network diversity indices. We define diversity indices across species aggregation levelsand show the interest of this method on a trophic network data set. In a second chapter, we develop a spatially explicit meta-community theory, with various kind of interactions. The theory contains a stochastic and a deterministic meta-community model. We then define the notion of meta-community persistence capacity. In a third chapter, we focus on network reconstruction from environmental DNA data along an environmental gradient.We show that the proposed method allows to evaluate the influence of environmental variables on community and infer a network in agreement with the literature on soil interactions. Finally, in a fourth chapter, we develop a method to combine environmental DNA data coming from different primers and show the efficiency of the method to better estimate plant abundances

Vers une théorie spatiale des réseaux d'interaction en écologie : méthodes, concepts et applications

This thesis focuses on the links between interaction networks, space and time. There is a paradigm shift in community ecology concerning the representation of a species community : from a collection of species towards species and their interactions, represented by an interaction network. We aim to build the bricks for a spatial network theory, by developing new methods, new models and applying it on ecological data. This manuscript contains four chapters. In a first chapter, we extend the diversity indices, built on Hill numbers, to network diversity indices. We define diversity indices across species aggregation levelsand show the interest of this method on a trophic network data set. In a second chapter, we develop a spatially explicit meta-community theory, with various kind of interactions. The theory contains a stochastic and a deterministic meta-community model. We then define the notion of meta-community persistence capacity. In a third chapter, we focus on network reconstruction from environmental DNA data along an environmental gradient.We show that the proposed method allows to evaluate the influence of environmental variables on community and infer a network in agreement with the literature on soil interactions. Finally, in a fourth chapter, we develop a method to combine environmental DNA data coming from different primers and show the efficiency of the method to better estimate plant abundances.Cette thèse s’intéresse aux liens entre réseaux d’interactions en écologie, espace et temps. On assiste à un changement croissant de représentation d’un communauté d’espèces, d’un ensemble d’espèces à un ensemble d’espèces et leurs interactions : un réseau d’interactions. On s’attachera alors à élaborer les prémisses d’une théorie spatiale des réseaux, en développant des méthodes, des modèles et en les appliquant sur des données écologiques. La thèse s’articule autour de quatre chapitres. Dans un premier chapitre, on se penchera sur le problème de comparaison de réseau en différents points du temps et de l’espace. Nous étendrons les mesures de diversité, jusque-là développées pour des abondances uniquement, aux réseaux avec abondances des espèces et des interactions. Nous nous attacherons à définir des indices à plusieurs niveaux d’agrégation des noeuds dans le réseau et montrerons l’intérêt de la méthode sur des données de réseaux trophiques. Dans un deuxième chapitre, nous nous intéresserons au développement d’une théorie des méta-communautés qui modélise explicitement l’espace comme un réseau spatial et la communauté comme un réseau d’interaction. Nous définirons la notion de capacité de persistance de la méta-communauté. Dans un troisième chapitre, nous nous intéresserons aux problèmes d’inférence d’interactions sur des données de sol d’ADN environnemental le long d’un gradient d’altitude dans les Alpes. Nous montrerons que la méthode proposée permet d’estimer l’influence des variables environnementales et de reconstruire un réseau d'interaction cohérent vis-à-vis de la littérature. Dans un quatrième chapitre, nous nous intéresserons à la combinaison d’abondances provenant de différents marqueurs d’ADN environemental et montrerons l’efficacité de la méthode proposée pour obtenir des meilleurs données d’abondances sur des données de plantes

metanetwork : A R package dedicated to handling and representing trophic metanetworks

International audienceTrophic networks describe interactions between species at a given location and time. Due to environmental changes, anthropogenic perturbations or sampling effects, trophic networks may vary in space and time. The collection of network time series or networks in different sites thus constitutes a metanetwork. We present here the R package metanetwork, which will ease the representation, the exploration and the analysis of trophic metanetwork datasets that are increasingly available.Our main methodological advance consists in suitable layout algorithm for trophic networks, which is based on trophic levels and dimension reduction of a graph diffusion kernel. In particular, it highlights relevant features of trophic networks (trophic levels, energetic channels).In addition, we developed tools to handle, compare visually and quantitatively and aggregate those networks. Static and dynamic visualisation functions have been developed to represent large networks. We apply our package workflow to several trophic network data sets

Variability of sleep bruxism—findings from consecutive nights of monitoring

Objectives!#!To determine sleep bruxism (SB) behavior during five consecutive nights and to identify correlations between SB episodes per hour (SB index) and sleep-time masseter-muscle activity (sMMA).!##!Material and methods!#!Thirty-one participants were included in the study. Of these, 10 were classified as sleep bruxers (group SB-1) and nine as non-sleep bruxers (group non-SB). The bruxism status of these 19 patients was identified by means of questionnaires, an assessment of clinical symptoms, and electromyographic/electrocardiographic data (Bruxoff® device). The remaining 12 participants were also identified as bruxers, but based exclusively on data from the Bruxoff device (group SB-2). Data analysis included descriptive statistics and Spearman's correlation to assess the relationship between the SB index and sMMA.!##!Results!#!Participants in group SB-1 showed an overall mean SB index of 3.1 ± 1.6 and a mean total sMMA per night of 62.9 ± 38.3. Participants in group SB-2 had an overall mean SB index of 2.7 ± 1.5 and a mean total sMMA of 56.0 ± 29.3. In the non-SB group, participants showed an overall mean SB index of 0.8 ± 0.5 and a mean total sMMA of 56.8 ± 30.3. Spearman's correlation yielded values of - 0.27 to 0.71 for the correlation between sMMA and SB index.!##!Conclusions!#!The data revealed variable SB activity and the absence of a reliable correlation between sMMA and the SB index.!##!Clinical relevance!#!The high variation in SB activity and lack of correlation between sMMA and the SB index should be considered when diagnosing SB.!##!Trial registration!#!Clinical Trials [NIH], clinical trial no. NCT03039985

Quantifying the overall effect of biotic interactions on species distributions along environmental gradients

Separating environmental effects from those of interspecific interactions on species distributions has always been a central objective of community ecology. Despite years of effort in analysing patterns of species co-occurrences and the developments of sophisticated tools, we are still unable to address this major objective. A key reason is that the wealth of ecological knowledge is not sufficiently harnessed in current statistical models, notably the knowledge on interspecific interactions.Here, we develop ELGRIN, a statistical model that simultaneously combines knowledge on interspecific interactions (i.e., the metanetwork), environmental data and species occurrences to tease apart their relative effects on species distributions. Instead of focusing on single effects of pairwise species interactions, which have little sense in complex communities, ELGRIN contrasts the overall effect of species interactions to that of the environment.Using various simulated and empirical data, we demonstrate the suitability of ELGRIN to address the objectives for various types of interspecific interactions like mutualism, competition and trophic interactions. Data on ecological networks are everyday increasing and we believe the time is ripe to mobilize these data to better understand biodiversity patterns. ELGRIN provides this opportunity to unravel how interspecific interactions actually influence species distributions

Diversity indices for ecological networks: a unifying framework using Hill numbers

International audienc