Biology subjects

Morvan-Dubois, G.

Publications and source records attributed to Morvan-Dubois, G..

3 recordsLinked to original sources

bioRxiv2025

A sensorimotor instability drives a locomotor transition during fish development

Animals rely on movement to survive -- to explore their environment, find food and mates and avoid danger. During development, changes in body shape, muscle strength and physiological needs drive the continuous adjustment of locomotor patterns. How these changes are orchestrated in a flexible and adaptive manner remains unknown. We explore this question in Danionella cerebrum, a miniature freshwater fish that is emerging as an important vertebrate model in systems neuroscience. We identify a clear transition in locomotion, from continuous to burst-and-coast swimming occurring around 3 weeks of age. We demonstrate that this transition is an energy saving strategy, and that it reflects an insta-bility in the sensorimotor process governing speed regulation. Rather than a preprogrammed developmental switch, it is therefore directly tied to the animal swimming strength. We confirmed this finding by manipulating sensory feedback in order to induce a similar transition at fixed developmental stages. Together, our results illustrate a dynamic interplay between body, brain, and environment during development, offering new insights into the principles governing adaptive locomotion.

biophysics↗

bioRxiv2025

Logarithmic coding leads to adaptive stabilization in the presence of sensorimotor delays

Animals respond to sensory stimuli with motor actions, which in turn generate new sensory inputs. This sensorimotor loop is constrained by time delays that impose a trade-off between responsiveness and stability. Additionally, as the relationship between a motor command and the corresponding sensory feedback is context-dependent, the response must be adapted in real time. It is generally believed that this adaptation process relies on an internal model that is continuously updated through prediction error minimization. Here, we experimentally reveal an alternative strategy based on a simpler feedback mechanism that does not require any internal model. We developed a virtual reality system for the miniature transparent fish Danionella cerebrum that enables in vivo brain-wide imaging during fictive navigation. By systematically manipulating the feedback parameters, we dissected the motor control process that allows the animal to stabilize its position using optic flow. The sensorimotor loop can be fully described by a single delay differential equation, whose solutions quantitatively capture the observed behavior across all experimental conditions. Both behavioral and neural data indicate that the observed adaptive response arises from the logarithmic nonlinearities at the sensory (Weber-Fechner law) and motor (Hennemans size principle) ends. These fundamental properties of the nervous system, conserved across species and sensory modalities, have traditionally been interpreted in terms of efficient coding. Our findings unveil a distinct functional role for such nonlinear transformations: ensuring stability in sensorimotor control despite inherent delays and sensory uncertainty.

neuroscience↗

bioRxiv2019

Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells

Glioblastoma cell ability to adapt their functioning to microenvironment changes is a source of the extensive intra-tumor heterogeneity characteristic of this devastating malignant brain tumor. A systemic view of the metabolic pathways underlying glioblastoma cell functioning states is lacking. We analyzed public single cell RNA-sequencing data from glioblastoma surgical resections, which offer the closest available view of tumor cell heterogeneity as encountered at the time of patients diagnosis. Unsupervised analyses revealed that information dispersed throughout the cell transcript repertoires encoded the identity of each tumor and masked information related to cell functioning states. Data reduction based on an experimentally-defined signature of transcription factors overcame this hurdle. It allowed cell grouping according to their tumorigenic potential, regardless of their tumor of origin. The approach relevance was validated using an independent dataset of glioblastoma tissue transcriptomes, patient-derived cell lines and orthotopic xenografts. Overexpression of genes coding for amino acid and lipid metabolism enzymes involved in anti-oxidative, energetic and cell membrane processes characterized cells with high tumorigenic potential. Modeling of their expression network highlighted the very long chain polyunsaturated fatty acid synthesis pathway at the core of the network. Expression of its most downstream enzymatic component, ELOVL2, was associated with worsened patient survival, and required for cell tumorigenic properties in vivo. Our results demonstrate the power of signature-driven analyses of single cell transcriptomes to obtain an integrated view of metabolic pathways at play within the heterogeneous cell landscape of patient tumors.

cancer biology↗