Biology subjects

Duriez, A.

Publications and source records attributed to Duriez, A..

3 recordsLinked to original sources

bioRxiv2026

Fluorescence imaging-induced phospholipid oxidation drives membrane phase separation by shifting miscibility boundaries

Fluorescence microscopy is a widely used tool for visualizing membrane organization in model and cellular systems; however, photoexcitation during imaging can generate reactive oxygen species, thereby altering membrane structure. Here, we show that fluorescence imaging actively drives membrane phase separation through photo-induced phospholipid oxidation. Using giant unilamellar vesicles, we observed that illumination of initially homogeneous membranes triggers the emergence of coexisting liquid-ordered and liquid-disordered domains. Chemical analysis by thin layer chromatography and mass spectrometry revealed the formation of a complex mixture of oxidized lipid species following excitation, characterized by stepwise oxygen additions to unsaturated phospholipids and multiple degradation products. These modifications increase lipid polarity and disrupt acyl chain packing, reducing favorable interactions with saturated phospholipids. As a result, membranes near the miscibility boundary become prone to demixing upon illumination, indicating that photo-induced lipid oxidation effectively shifts the miscibility boundary. Consistent with this model, light-induced phase separation is highly sensitive to membrane composition, with maximal effects observed near the liquid-liquid miscibility boundary. Electroformation substrate further modulated this effect, suggesting that pre-existing oxidative conditions sensitize membranes to subsequent photo-induced changes. Together, these findings demonstrate that excitation light can introduce artifacts in membrane phase behaviour. More broadly, subtle chemical modifications of phospholipids can shift membrane miscibility and reorganize membrane structure.

biochemistry↗

bioRxiv2026

Cell-type-specific cortical feedback coordinates hierarchical credit assignment

Learning is thought to arise from synaptic modifications across brain-wide circuits, yet how these networks coordinate plasticity to support complex behaviour is not known. Inspired by deep learning, we introduce a theory of hierarchical credit assignment in which pathway-specific cortical feedback drives dendrite-dependent burst plasticity across the cortex. We show that this principle enables learning in dynamic settings, complex visual recognition, and goal-directed tasks, mechanistically linking credit assignment to cell-type-specific regulation of dendritic excitation-inhibition balance. Our framework provides a unified account of diverse experimental phenomena -- including cell-type-specific modulation of synaptic plasticity, learning-dependent changes in interneurons, and neuron-specific dendritic error signals. Furthermore, the theory predicts that interneurons constrain the dimensionality of error feedback, offering a functional rationale for cortex-wide gradients in interneuron density. Together, these findings reveal how distinct cortical cell types cooperatively coordinate learning, bridging the gap between synaptic plasticity, circuit-level computation, and behaviour.

neuroscience↗

bioRxiv2023

Homeostatic Reinforcement Theory Accounts for Sodium Appetitive State- and Taste- Dependent Dopamine Responding.

Seeking and consuming nutrients is essential to survival and maintenance of life. Dynamic and volatile environments require that animals learn complex behavioral strategies to obtain the necessary nutritive substances. While this has been classically viewed in terms of homeostatic regulation, where complex nutrient seeking behaviors are triggered by physiological need, recent theoretical work proposed that such strategies are a result of reinforcement learning processes. This theory also proposed that phasic dopamine (DA) signals play a key role in signaling potentially need-fulfilling outcomes. To examine potential links between homeostatic and reinforcement learning processes, we focus on sodium appetite as sodium depletion triggers state and taste dependent changes in behavior and DA signaling evoked by sodium-related stimuli. We find that both the behavior and the dynamics of DA signaling underlying sodium appetite can be accounted for by extending principles of homeostatic regulation into a reinforcement learning framework (HRRL). We first optimized HRRL-based agents to model sodium-seeking behavior measured in rats. Agents successfully reproduced the state and the taste dependence of behavioral responding for sodium as well as for lithium and potassium salts. We then show that these same agents can account for the regulation of DA signals evoked by sodium tastants in a taste and state dependent manner. Our models quantitatively describe how DA signals evoked by sodium decrease with satiety and increase with deprivation suggesting that phasic DA signals and sodium consumption are down regulated prior to animals reaching satiety. Lastly, our HRRL agents also account for the behavioral and neurophysiological observations that suggest mice cannot distinguish between sodium and lithium containing salts. Our HRRL agents exhibited an equal preference for sodium versus lithium containing solutions, and underestimated the nutritional value of sodium when lithium was concurrently available. We propose that animals use orosensory signals as predictors of the internal impact of the consumed good and our results pose clear targets for future experiments. In sum, this work suggests that appetite-dirven behavior may be driven by reinforcement learning mechanisms that are dynamically tuned by homeostatic need.

neuroscience↗