Biology subjects

Bauduin, S.

Publications and source records attributed to Bauduin, S..

4 recordsLinked to original sources

bioRxiv2025

Social dysfunction relates to altered default mode network functional integrity across neuropsychiatric disorders: A replication and generalization study

BackgroundSocial dysfunction is an early manifestation of neuropsychiatric disorders that may relate to altered Default Mode Network (DMN) integrity. This study aimed to replicate previous findings linking social dysfunction with diminished resting-state DMN functional connectivity and altered task-based DMN functional activation in response to emotional faces across schizophrenia (SZ), Alzheimers disease (AD), and healthy controls (HC), and to extend these findings to major depressive disorder (MDD). MethodsResting-state fMRI and task-based fMRI data on implicit facial emotional processing were acquired in an overlapping cohort (resting-state fMRI: N=167; SZ=32, MDD=44, AD=29, HC=62. Task-based fMRI: N=152; SZ=30, MDD=42, AD=26, HC=54). Additionally, mega-analyses (N=317 for resting-state fMRI; N=291 for task-based fMRI) of the current and a prior independent sample were conducted. Social dysfunction was indexed with the Social Functioning Scale (SFS) and the De Jong-Gierveld Loneliness (LON) scale. ResultsThe association between higher mean SFS+LON social dysfunction scores and diminished DMN connectivity within the dorsomedial prefrontal cortex across SZ/AD/HC participants was replicated, and extended to MDD patients. Similar observations within the dorsomedial and rostromedial prefrontal cortex were found in the mega-analysis. Associations between social dysfunction and DMN activation in response to sad and happy faces were not replicated or found in the mega-analysis. ConclusionsDiminished dorsomedial prefrontal cortex DMN connectivity emerged as a transdiagnostic neurobiological marker for social dysfunction, suggesting a potential treatment target for precision medicine approaches. DMN functional responses to emotional faces may not be a sensitive biomarker for social dysfunction.

neuroscience↗

bioRxiv2023

Bringing circuit theory into spatial occupancy models to assess landscape connectivity

Connectivity shapes species distribution across fragmented landscapes. Assessing landscape resistance to dispersal is challenging because dispersal events are rare and difficult to detect especially for elusive species. To address these issues, spatial occupancy models have been developed to integrate the resistance surface concept of landscape ecology and model patch occupancy dynamics through colonization and extinction while accounting for imperfect species detection. However, the most recent approach is based on least-cost path distances which assume that individuals disperse along the optimal route. Here, we develop a new spatial occupancy model that incorporates commute distances derived from circuit theory to model dispersal across sites. Our approach allows for explicit estimation of landscape connectivity and direct measure of uncertainty from detection/non-detection data. To illustrate our approach, we study the recolonisation of two carnivores in France, and quantify the degree to which rivers facilitate Eurasian otter (Lutra lutra) dispersal and highways impede Eurasian lynx (Lynx lynx) recolonisation. Overall, spatial occupancy models provide a flexible framework to acccommodate any distance metric designed to align with species dispersal ecology. Open Research StatementData and code used in this research are available on Zenodo at https://zenodo.org/record/8376577

ecology↗

bioRxiv2021

Eurasian lynx populations in Western Europe: What prospects for the next 50 years?

Persistence of populations may be uncertain for large carnivore species, especially for those established in human-dominated landscapes. Here, we studied the Eurasian lynx in Western Europe established in the Upper Rhine meta-population (i.e., Jura, Vosges-Palatinian and Black Forest populations) and the Alpine population. These populations are currently considered endangered or critically endangered due to high anthropogenic mortality, small population size and low genetic diversity, and isolation. We assessed lynx persistence over a 50-year time horizon by implementing a spatially-explicit individual-based model, while accounting for road mortality and habitat selection. Forecasts showed a steady growth rapidly reaching a more stable phase for the Alpine and Jura populations, and a more heterogeneous positive growth with less precision for the Vosges-Palatinian and Black Forest populations. Exchanges of individuals between populations were limited, the Jura population playing the role of a crossroad. Finally, the persistence of lynx in Western Europe seems likely on a large scale over the next 50 years. Indeed, simulations showed high female occupancy as well as average lynx density over the core areas of the four studied populations. Nevertheless, these results should be interpreted with the model limitations in mind, concerning the absence of movement barriers and inbreeding depression.

ecology↗

bioRxiv2020

From individual behavior and pack dynamics to population responses: An individual-based approach to model the wolf social life cycle

The occurrence of wolf populations in human-dominated landscapes is challenging worldwide because of conflicts with human activities. Modeling is an important tool to predict wolf dynamics and expansion, and help in decision making concerning management and conservation. However, some individual behaviors and pack dynamics of the wolf life cycle are still unclear to ecologists. Here we present an individual-based model (IBM) to project wolf populations while exploring the lesser-known processes of the wolf life cycle. IBMs are bottom-up models that simulate the fate of individuals interacting with each other, with population-level properties emerging from the individual-level simulations. IBMs are particularly adapted to represent social species such as the wolf that exhibits complex individual interactions. Our IBM predicts wolf demography including fine-scale individual behavior and pack dynamics based on up-to-date scientific literature. We explore four processes of the wolf life cycle whose consequences on population dynamics are still poorly understood: the pack dissolution following the loss of a breeder, the adoption of young dispersers by packs, the establishment of new packs through budding, and the different types of breeder replacement. While running different versions of the IBM to explore these processes, we also illustrate the modularity and flexibility of our model, an asset to model wolf populations experiencing different ecological and demographic conditions. The different parameterization of pack dissolution, territory establishment by budding, and breeder replacement processes influence the most the projections of wolf populations. As such, these processes require further field investigation to be better understood. The adoption process has a lesser impact on model predictions. Being coded in R to facilitate its understanding, we expect that our model will be used and further adapted by ecologists for their own specific applications.

ecology↗