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#dynamics

48 posts11 participants2 posts today
Fabrizio Musacchio

In our recent #JournalClub, I presented Genkin et al. (2025), who decode #DecisionMaking in the #PremotorCortex of #macaques as low-dimensional #latent #dynamics shared across #NeuralPopulations. Their generative model links tuning curves, spike-time variability, and stimulus-dependent potential landscapes to a common internal decision variable. I summarized and discussed their findings in this blog post:

📝doi.org/10.1038/s41586-025-091
🌍fabriziomusacchio.com/blog/202

#CompNeuro#Neuroscience#Cortex
Rxiv mechanobio

📰 "Rapid Single-Cell Measurement of Transient Transmembrane Water Flow under Osmotic Gradient"
arxiv.org/abs/2508.00104 #Physics.Bio-Ph #Dynamics #Cell

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arXiv.orgRapid Single-Cell Measurement of Transient Transmembrane Water Flow under Osmotic GradientWhile aquaporin (AQP) gating dynamically regulates transmembrane water permeability for cellular homeostasis, its mechanisms remain poorly understood compared to ion channels. A central challenge is the lack of methods to measure water flow through AQPs with the spatiotemporal resolution and sensitivity equivalent to patch-clamp recordings of ion fluxes, a limitation stemming from the electrically silent nature of water transport. We introduce a technique to rapidly detect cytoplasmic flows induced by osmotic-gradient-driven transmembrane water transport in single adherent human cancer cells. This approach enables direct measurement of AQP-mediated water transport and provides a powerful tool to investigate AQP function and regulation and cytoplasmic flow dynamics at the single-cell level.
Rxiv mechanobio

📰 "Dynamics of a Data-Driven Low-Dimensional Model of Turbulent Minimal Pipe Flow"
arxiv.org/abs/2408.03135 #Physics.Flu-Dyn #Dynamics #Cell

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arXiv.orgDynamics of a Data-Driven Low-Dimensional Model of Turbulent Minimal Pipe FlowThe simulation of turbulent flow requires many degrees of freedom to resolve all the relevant times and length scales. However, due to the dissipative nature of the Navier-Stokes equations, the long-term dynamics are expected to lie on a finite-dimensional invariant manifold with fewer degrees of freedom. In this study, we build low-dimensional data-driven models of pressure-driven flow through a circular pipe. We impose the `shift-and-reflect' symmetry to study the system in a minimal computational cell (e.g., smallest domain size that sustains turbulence) at a Reynolds number of 2500. We build these models by using autoencoders to parametrize the manifold coordinates and neural ODEs to describe their time evolution. Direct numerical simulations (DNS) typically require on the order of O(105) degrees of freedom, while our data-driven framework enables the construction of models with fewer than 20 degrees of freedom. Remarkably, these reduced order models effectively capture crucial features of the flow, including the streak breakdown. In short-time tracking, these models accurately track the true trajectory for one Lyapunov time, while at long-times, they successfully capture key aspects of the dynamics such as Reynolds stresses and energy balance. Additionally, we report a library of exact coherent states (ECS) found in the DNS with the aid of these low-dimensional models. This approach leads to the discovery of seventeen previously unknown solutions within the turbulent pipe flow system, notably featuring relative periodic orbits characterized by the longest reported periods for such flow conditions.
Rxiv mechanobio

📰 "Nystr\"om Type Exponential Integrators for Strongly Magnetized Charged Particle Dynamics"
arxiv.org/abs/2505.00288 #Physics.Plasm-Ph #Physics.Comp-Ph #Dynamics #Math.Na #Cs.Na #Cell

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arXiv.orgNyström Type Exponential Integrators for Strongly Magnetized Charged Particle DynamicsCalculating the dynamics of charged particles in electromagnetic fields (i.e. the particle pushing problem) is one of the most computationally intensive components of particle-in-cell (PIC) methods for plasma physics simulations. This task is especially challenging when the plasma is strongly magnetized, since in this case the particle motion consists of a wide range of temporal scales from highly oscillatory fast gyromotion to slow macroscopic behavior and the resulting numerical model is very stiff. Current state-of-the-art time integrators used to simulate particle motion have limitations given the severe numerical stiffness of the problem and more efficient methods are of interest. Recently, exponential integrators have been proposed as a promising new approach for these simulations and shown to offer computational advantages over commonly used schemes. Exponential methods can solve linear problems exactly and are A-stable. In this paper, the standard exponential algorithms framework is extended to derive Nyström-type exponential methods that integrate the Newtonian equations of motion as a second-order differential equation. Specific Nyström-type schemes of second and third orders are derived and applied to strongly magnetized particle pushing problems. Numerical experiments are presented to demonstrate that the Nyström-type exponential integrators can provide significant improvement in computational efficiency over the standard exponential methods.
Rxiv mechanobio

📰 "Design, Simulation, and Fabrication of a Hexagonal Microfluidic Platform for Culturing Neurons"
arxiv.org/abs/2508.00425 #Physics.Flu-Dyn #Physics.Bio-Ph #Dynamics #Q-Bio.Nc #Cell

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arXiv.orgDesign, Simulation, and Fabrication of a Hexagonal Microfluidic Platform for Culturing NeuronsDeveloping an organoid computing platform from neurons in vitro demands stable, precisely controlled microenvironments. To address this requirement, we designed, simulated, and fabricated a microfluidic device featuring hexagonal wells ($34.64\,\mathrm{μm}$ side length) in a honeycomb array connected by $20\,\mathrm{μm}$ channels. Computational fluid dynamics (CFD) modeling, validated by high mesh quality ($0.934$ orthogonal quality) and robust convergence, confirmed the architecture supports flow regimes ideal for ensuring cell viability. At target flow rates of $0.1$ - $1\,\mathrm{μL/min}$, simulations revealed the extrapolated pressure differential across the full $50{,}000\,\mathrm{μm}$ device remains within stable operating limits at $177\,\mathrm{kPa}$ (average) and $329\,\mathrm{kPa}$ (maximum). Photolithography successfully produced this architecture, with only minor corner rounding observed at feature interfaces. This work therefore establishes a computationally validated and fabricated platform, paving the way for experimental flow characterization and subsequent neural integration.
Rxiv mechanobio

📰 "Knock-out of Tpm4.2/Actin Filaments Alters Neuronal Signaling, Neurite Outgrowth, and Behavioral Phenotypes in Mice"
doi.org/doi:10.1007/s12035-025
pubmed.ncbi.nlm.nih.gov/407533
#Dynamics #Actin

SpringerLinkKnock-out of Tpm4.2/Actin Filaments Alters Neuronal Signaling, Neurite Outgrowth, and Behavioral Phenotypes in Mice - Molecular NeurobiologyTropomyosins (Tpm) are master regulators of actin dynamics through forming co-polymers with filamentous actin. Despite the well-understood function of muscle Tpms in the contractile apparatus of muscle cells, much less is known about the diverse physiological function of cytoplasmic Tpms in eukaryotic cells. Here, we investigated the role of the Tpm4.2 isoform in neuronal processes including signaling, neurite outgrowth, and receptor recycling using primary neurons from Tpm4.2 knock-out mice. Live imaging of calcium and electrophysiology data demonstrated increased frequency, yet reduced strength of single neuron spikes. Calcium imaging further showed an increase in neuronal networks. In vitro assays of Tpm4.2 knock-out neurons displayed impaired recycling of the AMPA neurotransmitter receptor subunit GluA1. Morphometric analysis of neurite growth showed increased dendritic complexity and altered dendritic spine morphology in Tpm4.2 knock-out primary neurons. Behavioral analysis of Tpm4.2 knock-out mice displayed heightened anxiety in the open field test, while the elevated plus maze displayed heightened anxiety only in females. Our study depicts the multi-faceted role of the Tpm4.2 isoform and its co-polymer F-actin population in neurons, with potential implications for better understanding diseases of the nervous system which involve actin cytoskeleton dysfunction.
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