45 research outputs found

    Geometric analysis of noisy perturbations to nonholonomic constraints

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    We propose two types of stochastic extensions of nonholonomic constraints for mechanical systems. Our approach relies on a stochastic extension of the Lagrange-d'Alembert framework. We consider in details the case of invariant nonholonomic systems on the group of rotations and on the special Euclidean group. Based on this, we then develop two types of stochastic deformations of the Suslov problem and study the possibility of extending to the stochastic case the preservation of some of its integrals of motion such as the Kharlamova or Clebsch-Tisserand integrals

    Symmetry reduction of Brownian motion and Quantum Calogero-Moser systems

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    Let QQ be a Riemannian GG-manifold. This paper is concerned with the symmetry reduction of Brownian motion in QQ and ramifications thereof in a Hamiltonian context. Specializing to the case of polar actions we discuss various versions of the stochastic Hamilton-Jacobi equation associated to the symmetry reduction of Brownian motion and observe some similarities to the Schr\"odinger equation of the quantum free particle reduction as described by Feher and Pusztai. As an application we use this reduction scheme to derive examples of quantum Calogero-Moser systems from a stochastic setting.Comment: V2 contains some improvements thanks to referees' suggestions; to appear in Stochastics and Dynamic

    Collisionless kinetic theory of rolling molecules

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    We derive a collisionless kinetic theory for an ensemble of molecules undergoing nonholonomic rolling dynamics. We demonstrate that the existence of nonholonomic constraints leads to problems in generalizing the standard methods of statistical physics. In particular, we show that even though the energy of the system is conserved, and the system is closed in the thermodynamic sense, some fundamental features of statistical physics such as invariant measure do not hold for such nonholonomic systems. Nevertheless, we are able to construct a consistent kinetic theory using Hamilton's variational principle in Lagrangian variables, by regarding the kinetic solution as being concentrated on the constraint distribution. A cold fluid closure for the kinetic system is also presented, along with a particular class of exact solutions of the kinetic equations.Comment: Revised version; 31 pages, 1 figur

    AP2Îł: a new player on adult hippocampal neurogenesis regulation

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    Since the recognition that the mammalian brain retains the ability to generate newborn neurons with functional relevance throughout life, the matrix of molecular regulators that govern adult neurogenesis has been the focus of much interest. In a recent study published in Molecular Psychiatry, we demonstrate Activating Protein 2Îł (AP2Îł), a transcription factor previously implicated in cell fate determination in the developing cortex, as a novel player in the regulation of glutamatergic neurogenesis in the adult hippocampus. Using distinct experimental approaches, we showed that AP2Îł is specifically present in a subpopulation of transient amplifying progenitors, where it acts as a crucial promoter of proliferation and differentiation of adult-born glutamatergic granule neurons. Strikingly, deficiency of AP2Îł in the adult brain compromises the generation of new glutamatergic neurons, with impact on the function of cortico-limbic circuits. Here, we share our view on how AP2Îł integrates the transcriptional orchestration of glutamatergic neurogenesis in the adult hippocampus, and consequently, how it emerges as a novel molecular candidate to study the translation of environmental pressures into alterations of brain neuroplasticity in homeostatic, but also in neuropathological contexts.Bial Foundation (427/14); Northern Portugal Regional Operational Programme (NORTE 2020); European Regional Development Fund (FEDER) (projects NORTE-01-0145-FEDER-000013 e NORTE-01-0145-FEDER-000023); Competitiveness Factors Operational Programme (COMPETE)info:eu-repo/semantics/publishedVersio

    Oligodendrocyte heterogeneity in the mouse juvenile and adult central nervous system

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    Oligodendrocytes have been considered as a functionally homogeneous population in the central nervous system (CNS). We performed single-cell RNA sequencing on 5072 cells of the oligodendrocyte lineage from 10 regions of the mouse juvenile and adult CNS. Thirteen distinct populations were identified, 12 of which represent a continuum from Pdgfra(+) oligodendrocyte precursor cells (OPCs) to distinct mature oligodendrocytes. Initial stages of differentiation were similar across the juvenile CNS, whereas subsets of mature oligodendrocytes were enriched in specific regions in the adult brain. Newly formed oligodendrocytes were detected in the adult CNS and were responsive to complex motor learning. A second Pdgfra(+) population, distinct from OPCs, was found along vessels. Our study reveals the dynamics of oligodendrocyte differentiation and maturation, uncoupling them at a transcriptional level and highlighting oligodendrocyte heterogeneity in the CNS

    Classes and continua of hippocampal CA1 inhibitory neurons revealed by single-cell transcriptomics

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    Understanding any brain circuit will require a categorization of its constituent neurons. In hippocampal area CA1, at least 23 classes of GABAergic neuron have been proposed to date. However, this list may be incomplete; additionally, it is unclear whether discrete classes are sufficient to describe the diversity of cortical inhibitory neurons or whether continuous modes of variability are also required. We studied the transcriptomes of 3,663 CA1 inhibitory cells, revealing 10 major GABAergic groups that divided into 49 fine-scale clusters. All previously described and several novel cell classes were identified, with three previously described classes unexpectedly found to be identical. A division into discrete classes, however, was not sufficient to describe the diversity of these cells, as continuous variation also occurred between and within classes. Latent factor analysis revealed that a single continuous variable could predict the expression levels of several genes, which correlated similarly with it across multiple cell types. Analysis of the genes correlating with this variable suggested it reflects a range from metabolically highly active faster-spiking cells that proximally target pyramidal cells to slower-spiking cells targeting distal dendrites or interneurons. These results elucidate the complexity of inhibitory neurons in one of the simplest cortical structures and show that characterizing these cells requires continuous modes of variation as well as discrete cell classes.</p
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