1,286 research outputs found

    Cell assembly dynamics of sparsely-connected inhibitory networks: a simple model for the collective activity of striatal projection neurons

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    Striatal projection neurons form a sparsely-connected inhibitory network, and this arrangement may be essential for the appropriate temporal organization of behavior. Here we show that a simplified, sparse inhibitory network of Leaky-Integrate-and-Fire neurons can reproduce some key features of striatal population activity, as observed in brain slices [Carrillo-Reid et al., J. Neurophysiology 99 (2008) 1435{1450]. In particular we develop a new metric to determine the conditions under which sparse inhibitory networks form anti-correlated cell assemblies with time-varying activity of individual cells. We found that under these conditions the network displays an input-specific sequence of cell assembly switching, that effectively discriminates similar inputs. Our results support the proposal [Ponzi and Wickens, PLoS Comp Biol 9 (2013) e1002954] that GABAergic connections between striatal projection neurons allow stimulus-selective, temporally-extended sequential activation of cell assemblies. Furthermore, we help to show how altered intrastriatal GABAergic signaling may produce aberrant network-level information processing in disorders such as Parkinson's and Huntington's diseases.Comment: 22 pages, 9 figure

    Exact firing time statistics of neurons driven by discrete inhibitory noise

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    Neurons in the intact brain receive a continuous and irregular synaptic bombardment from excitatory and inhibitory pre-synaptic neurons, which determines the firing activity of the stimulated neuron. In order to investigate the influence of inhibitory stimulation on the firing time statistics, we consider Leaky Integrate-and-Fire neurons subject to inhibitory instantaneous post-synaptic potentials. In particular, we report exact results for the firing rate, the coefficient of variation and the spike train spectrum for various synaptic weight distributions. Our results are not limited to stimulations of infinitesimal amplitude, but they apply as well to finite amplitude post-synaptic potentials, thus being able to capture the effect of rare and large spikes. The developed methods are able to reproduce also the average firing properties of heterogeneous neuronal populations.Comment: 20 pages, 8 Figures, submitted to Scientific Report

    Death and rebirth of neural activity in sparse inhibitory networks

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    In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of the neural activity, as expected, but it can also promote neural reactivation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition (neurons' death). However, the random pruning of the connections is able to reverse the action of inhibition, i.e. in a sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of the neurons (neurons' rebirth). Thus the number of firing neurons reveals a minimum at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by the neurons with higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving an analytic mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, the system passes from a perfectly regular evolution to an irregular bursting dynamics. In this latter regime the model provides predictions consistent with experimental findings for a specific class of neurons, namely the medium spiny neurons in the striatum.Comment: 19 pages, 10 figures, submitted to NJ

    Biological relevance of spiking neural networks

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    Structural stability of the two-fold singularity

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    At a two-fold singularity, the velocity vector of a flow switches discontinuously across a codimension one switching manifold, between two directions that both lie tangent to the manifold. Particularly intricate dynamics arises when the local flow curves toward the switching manifold from both sides, a case referred to as the Teixeira singularity. The flow locally performs two different actions: it winds around the singularity by crossing repeatedly through, and passes through the singularity by sliding along, the switching manifold. The case when the number of rotations around the singularity is infinite has been analyzed in detail. Here we study the case when the flow makes a finite, but previously unknown, number of rotations around the singularity between incidents of sliding. We show that the solution is remarkably simple: the maximum and minimum numbers of rotations made anywhere in the flow differ only by one and increase incrementally with a single parameter -the angular jump in the flow direction across the switching manifold at the singularity

    Field Trials for the Empirical Characterization of the Low Voltage Grid Access Impedance From 35 kHz to 500 kHz

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    The access impedance of low-voltage (LV) power networks is a major factor related to the performance of the narrow-band power line communications (NB-PLCs) and, in a wider sense, to electromagnetic compatibility (EMC) performance. Up to date, there is still a lack of knowledge about the frequency-dependent access impedance for frequencies above 9 kHz and up to 500 kHz, which is the band where the NB-PLC operates. The access impedance affects the transmission of the NB-PLC signal, and it determines the propagation of the non-intentional emissions that may disturb other electrical devices, including malfunctioning or reduced lifetime of equipment. This paper presents the results of field measurements of the LV access impedance up to 500 kHz in different scenarios, with measurement locations close to end users and near transformers. The results provide useful information to analyze the characteristics of the LV access impedance, including variation with frequency, ranges of values for different frequency bands, and analysis of specific phenomena. Moreover, the results reveal a diverse frequency-dependent behavior of the access impedance in different scenarios, depending on the grid topology, the number of end users (that is, number and type of connected loads), and the type of transformation center. Overall, the results of this paper offer a better understanding of the transmission of NB-PLC signals and EMC-related phenomena.The authors would like to thank Iberdrola for the availability and the collaboration of authorized staff for carrying out the field trials

    The imprint of neutrinos on clustering in redshift-space

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    (abridged) We investigate the signatures left by the cosmic neutrino background on the clustering of matter, CDM+baryons and halos in redshift-space using a set of more than 1000 N-body and hydrodynamical simulations with massless and massive neutrinos. We find that the effect neutrinos induce on the clustering of CDM+baryons in redshift-space on small scales is almost entirely due to the change in σ8\sigma_8. Neutrinos imprint a characteristic signature in the quadrupole of the matter (CDM+baryons+neutrinos) field on small scales, that can be used to disentangle the effect of σ8\sigma_8 and MνM_\nu. We show that the effect of neutrinos on the clustering of halos is very different, on all scales, to the one induced by σ8\sigma_8. We find that the effects of neutrinos of the growth rate of CDM+baryons ranges from ∼0.3%\sim0.3\% to 2%2\% on scales k∈[0.01,0.5] hMpc−1k\in[0.01, 0.5]~h{\rm Mpc}^{-1} for neutrinos with masses Mν⩽0.15M_\nu \leqslant 0.15 eV. We compute the bias between the momentum of halos and the momentum of CDM+baryon and find it to be 1 on large scales for all models with massless and massive neutrinos considered. This point towards a velocity bias between halos and total matter on large scales that it is important to account for in order to extract unbiased neutrino information from velocity/momentum surveys such as kSZ observations. We show that baryonic effects can affect the clustering of matter and CDM+baryons in redshift-space by up to a few percent down to k=0.5 hMpc−1k=0.5~h{\rm Mpc}^{-1}. We find that hydrodynamics and astrophysical processes, as implemented in our simulations, only distort the relative effect that neutrinos induce on the anisotropic clustering of matter, CDM+baryons and halos in redshift-space by less than 1%1\%. Thus, the effect of neutrinos in the fully non-linear regime can be written as a transfer function with very weak dependence on astrophysics.Comment: 19 pages, 12 figure

    Synchronous vs Asynchronous Chain Motion in α-Synuclein Contact Dynamics

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    α-Synuclein (α-syn) is an intrinsically unstructured 140-residue neuronal protein of uncertain function that is implicated in the etiology of Parkinson’s disease. Tertiary contact formation rate constants in α-syn, determined from diffusion-limited electron-transfer kinetics measurements, are poorly approximated by simple random polymer theory. One source of the discrepancy between theory and experiment may be that interior-loop formation rates are not well approximated by end-to-end contact dynamics models. We have addressed this issue with Monte Carlo simulations to model asynchronous and synchronous motion of contacting sites in a random polymer. These simulations suggest that a dynamical drag effect may slow interior-loop formation rates by about a factor of 2 in comparison to end-to-end loops of comparable size. The additional deviations from random coil behavior in α-syn likely arise from clustering of hydrophobic residues in the disordered polypeptide
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