67 research outputs found
Shaping bursting by electrical coupling and noise
Gap-junctional coupling is an important way of communication between neurons
and other excitable cells. Strong electrical coupling synchronizes activity
across cell ensembles. Surprisingly, in the presence of noise synchronous
oscillations generated by an electrically coupled network may differ
qualitatively from the oscillations produced by uncoupled individual cells
forming the network. A prominent example of such behavior is the synchronized
bursting in islets of Langerhans formed by pancreatic \beta-cells, which in
isolation are known to exhibit irregular spiking. At the heart of this
intriguing phenomenon lies denoising, a remarkable ability of electrical
coupling to diminish the effects of noise acting on individual cells.
In this paper, we derive quantitative estimates characterizing denoising in
electrically coupled networks of conductance-based models of square wave
bursting cells. Our analysis reveals the interplay of the intrinsic properties
of the individual cells and network topology and their respective contributions
to this important effect. In particular, we show that networks on graphs with
large algebraic connectivity or small total effective resistance are better
equipped for implementing denoising. As a by-product of the analysis of
denoising, we analytically estimate the rate with which trajectories converge
to the synchronization subspace and the stability of the latter to random
perturbations. These estimates reveal the role of the network topology in
synchronization. The analysis is complemented by numerical simulations of
electrically coupled conductance-based networks. Taken together, these results
explain the mechanisms underlying synchronization and denoising in an important
class of biological models
The role of ongoing dendritic oscillations in single-neuron dynamics
The dendritic tree contributes significantly to the elementary computations a neuron performs while converting its synaptic inputs into action potential output. Traditionally, these computations have been characterized as temporally local, near-instantaneous mappings from the current input of the cell to its current output, brought about by somatic summation of dendritic contributions that are generated in spatially localized functional compartments. However, recent evidence about the presence of oscillations in dendrites suggests a qualitatively different mode of operation: the instantaneous phase of such oscillations can depend on a long history of inputs, and under appropriate conditions, even dendritic oscillators that are remote may interact through synchronization. Here, we develop a mathematical framework to analyze the interactions of local dendritic oscillations, and the way these interactions influence single cell computations. Combining weakly coupled oscillator methods with cable theoretic arguments, we derive phase-locking states for multiple oscillating dendritic compartments. We characterize how the phase-locking properties depend on key parameters of the oscillating dendrite: the electrotonic properties of the (active) dendritic segment, and the intrinsic properties of the dendritic oscillators. As a direct consequence, we show how input to the dendrites can modulate phase-locking behavior and hence global dendritic coherence. In turn, dendritic coherence is able to gate the integration and propagation of synaptic signals to the soma, ultimately leading to an effective control of somatic spike generation. Our results suggest that dendritic oscillations enable the dendritic tree to operate on more global temporal and spatial scales than previously thought
Theory of disk accretion onto supermassive black holes
Accretion onto supermassive black holes produces both the dramatic phenomena
associated with active galactic nuclei and the underwhelming displays seen in
the Galactic Center and most other nearby galaxies. I review selected aspects
of the current theoretical understanding of black hole accretion, emphasizing
the role of magnetohydrodynamic turbulence and gravitational instabilities in
driving the actual accretion and the importance of the efficacy of cooling in
determining the structure and observational appearance of the accretion flow.
Ongoing investigations into the dynamics of the plunging region, the origin of
variability in the accretion process, and the evolution of warped, twisted, or
eccentric disks are summarized.Comment: Mostly introductory review, to appear in "Supermassive black holes in
the distant Universe", ed. A.J. Barger, Kluwer Academic Publishers, in pres
Limitations of perturbative techniques in the analysis of rhythms and oscillations
Perturbation theory is an important tool in the analysis of oscillators and their response to external stimuli. It is predicated on the assumption that the perturbations in question are âsufficiently weakâ, an assumption that is not always valid when perturbative methods are applied. In this paper, we identify a number of concrete dynamical scenarios in which a standard perturbative technique, based on the infinitesimal phase response curve (PRC), is shown to give different predictions than the full model. Shear-induced chaos, i.e., chaotic behavior that results from the amplification of small perturbations by underlying shear, is missed entirely by the PRC. We show also that the presence of âstickyâ phaseâspace structures tend to cause perturbative techniques to overestimate the frequencies and regularity of the oscillations. The phenomena we describe can all be observed in a simple 2D neuron model, which we choose for illustration as the PRC is widely used in mathematical neuroscience
Skeletal Morphology of Opius dissitus and Biosteres carbonarius (Hymenoptera: Braconidae), with a Discussion of Terminology
The Braconidae, a family of parasitic wasps, constitute a major taxonomic challenge with an estimated diversity of 40,000 to 120,000 species worldwide, only 18,000 of which have been described to date. The skeletal morphology of braconids is still not adequately understood and the terminology is partly idiosyncratic, despite the fact that anatomical features form the basis for most taxonomic work on the group. To help address this problem, we describe the external skeletal morphology of Opius dissitus Muesebeck 1963 and Biosteres carbonarius Nees 1834, two diverse representatives of one of the least known and most diverse braconid subfamilies, the Opiinae. We review the terminology used to describe skeletal features in the Ichneumonoidea in general and the Opiinae in particular, and identify a list of recommend terms, which are linked to the online Hymenoptera Anatomy Ontology. The morphology of the studied species is illustrated with SEM-micrographs, photos and line drawings. Based on the examined species, we discuss intraspecific and interspecific morphological variation in the Opiinae and point out character complexes that merit further study
Neuron-glial Interactions
Although lagging behind classical computational neuroscience, theoretical and computational approaches are beginning to emerge to characterize different aspects of neuron-glial interactions. This chapter aims to provide essential knowledge on neuron-glial interactions in the mammalian brain, leveraging on computational studies that focus on structure (anatomy) and function (physiology) of such interactions in the healthy brain. Although our understanding of the need of neuron-glial interactions in the brain is still at its infancy, being mostly based on predictions that await for experimental validation, simple general modeling arguments borrowed from control theory are introduced to support the importance of including such interactions in traditional neuron-based modeling paradigms.Junior Leader Fellowship Program by âla Caixaâ Banking Foundation (LCF/BQ/LI18/11630006
Neuron-Glial Interactions
Although lagging behind classical computational neuroscience, theoretical and
computational approaches are beginning to emerge to characterize different
aspects of neuron-glial interactions. This chapter aims to provide essential
knowledge on neuron-glial interactions in the mammalian brain, leveraging on
computational studies that focus on structure (anatomy) and function
(physiology) of such interactions in the healthy brain. Although our
understanding of the need of neuron-glial interactions in the brain is still at
its infancy, being mostly based on predictions that await for experimental
validation, simple general modeling arguments borrowed from control theory are
introduced to support the importance of including such interactions in
traditional neuron-based modeling paradigms.Comment: 43 pages, 2 figures, 1 table. Accepted for publication in the
"Encyclopedia of Computational Neuroscience," D. Jaeger and R. Jung eds.,
Springer-Verlag New York, 2020 (2nd edition
A Neuron-Glial Perspective for Computational Neuroscience
International audienceThere is growing excitement around glial cells, as compelling evidence point to new, previously unimaginable roles for these cells in information processing of the brain, with the potential to affect behavior and higher cognitive functions. Among their many possible functions, glial cells could be involved in practically every aspect of the brain physiology in health and disease. As a result, many investigators in the field welcome the notion of a Neuron-Glial paradigm of brain function, as opposed to Ramon y Cayal's more classical neuronal doctrine which identifies neurons as the prominent, if not the only, cells capable of a signaling role in the brain. The demonstration of a brain-wide Neuron-Glial paradigm however remains elusive and so does the notion of what neuron-glial interactions could be functionally relevant for the brain computational tasks. In this perspective, we present a selection of arguments inspired by available experimental and modeling studies with the aim to provide a biophysical and conceptual platform to computational neuroscience no longer as a mere prerogative of neuronal signaling but rather as the outcome of a complex interaction between neurons and glial cells
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