196,300 research outputs found

    Nicola da Monteforte

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    Breve profilo dello scultore beneventano Nicola da Monteforte

    Chiese e società nella storia di Monteforte d’Alpone

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    Rigorosa ricostruzione storica della vicenda delle antiche chiese di Monteforte d'Alpone. Il volume contiene un Cd con 3 saggi dell'autore

    Dynamical Entropy Production in Spiking Neuron Networks in the Balanced State

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    We demonstrate deterministic extensive chaos in the dynamics of large sparse networks of theta neurons in the balanced state. The analysis is based on numerically exact calculations of the full spectrum of Lyapunov exponents, the entropy production rate, and the attractor dimension. Extensive chaos is found in inhibitory networks and becomes more intense when an excitatory population is included. We find a strikingly high rate of entropy production that would limit information representation in cortical spike patterns to the immediate stimulus response

    Dynamic Flux Tubes Form Reservoirs of Stability in Neuronal Circuits

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    Neurons in cerebral cortical circuits interact by sending and receiving electrical impulses called spikes. The ongoing spiking activity of cortical circuits is fundamental to many cognitive functions including sensory processing, working memory, and decision making. London et al. [Sensitivity to Perturbations In Vivo Implies High Noise and Suggests Rate Coding in Cortex, Nature (London) 466, 123 (2010).NATUAS0028-083610.1038/nature09086] recently argued that even a single additional spike can cause a cascade of extra spikes that rapidly decorrelate the microstate of the network. Here, we show theoretically in a minimal model of cortical neuronal circuits that single-spike perturbations trigger only a very weak rate response. Nevertheless, single-spike perturbations are found to rapidly decorrelate the microstate of the network, although the dynamics is stable with respect to small perturbations. The coexistence of stable and unstable dynamics results from a system of exponentially separating dynamic flux tubes around stable trajectories in the network’s phase space. The radius of these flux tubes appears to decrease algebraically with neuron number N and connectivity K, which implies that the entropy of the circuit’s repertoire of state sequences scales as Nln⁡(KN)

    Inflow/outflow pressure boundary conditions for smoothed particle hydrodynamics simulations of incompressible flows

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    Open Boundary treatment is a well-known issue in the Smoothed Particle Hydrodynamics (SPH) method, mainly when the truly Incompressible (ISPH) approach is employed. In the paper a novel method is proposed to set pressure boundary conditions in the computational domain inlets and outlets, without requiring the velocity profile assignment. The new technique allows to treat in the same way inflow and outflow sections, effectively dealing with the release of new particles at inlets and the deactivation of the ones leaving the domain through the outlets. Several 3D numerical tests, both in the laminar and turbulent regimes, are carried out to validate the proposed numerical scheme considering steady and oscillating pressure boundary conditions
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