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Burst firing is a neural code in an insect auditory system  [PDF]
Hugo G. Eyherabide,Ariel Rokem,Andreas V. M. Herz,Ines Samengo
Quantitative Biology , 2008, DOI: 10.3389/neuro.10.003.2008
Abstract: Various classes of neurons alternate between high-frequency discharges and silent intervals. This phenomenon is called burst firing. To analyze burst activity in an insect system, grasshopper auditory receptor neurons were recorded in vivo for several distinct stimulus types. The experimental data show that both burst probability and burst characteristics are strongly influenced by temporal modulations of the acoustic stimulus. The tendency to burst, hence, is not only determined by cell-intrinsic processes, but also by their interaction with the stimulus time course. We study this interaction quantitatively and observe that bursts containing a certain number of spikes occur shortly after stimulus deflections of specific intensity and duration. Our findings suggest a sparse neural code where information about the stimulus is represented by the number of spikes per burst, irrespective of the detailed interspike-interval structure within a burst. This compact representation cannot be interpreted as a firing-rate code. An information-theoretical analysis reveals that the number of spikes per burst reliably conveys information about the amplitude and duration of sound transients, whereas their time of occurrence is reflected by the burst onset time. The investigated neurons encode almost half of the total transmitted information in burst activity.
Conversion of Phase Information into a Spike-Count Code by Bursting Neurons  [PDF]
Inés Samengo,Marcelo A. Montemurro
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0009669
Abstract: Single neurons in the cerebral cortex are immersed in a fluctuating electric field, the local field potential (LFP), which mainly originates from synchronous synaptic input into the local neural neighborhood. As shown by recent studies in visual and auditory cortices, the angular phase of the LFP at the time of spike generation adds significant extra information about the external world, beyond the one contained in the firing rate alone. However, no biologically plausible mechanism has yet been suggested that allows downstream neurons to infer the phase of the LFP at the soma of their pre-synaptic afferents. Therefore, so far there is no evidence that the nervous system can process phase information. Here we study a model of a bursting pyramidal neuron, driven by a time-dependent stimulus. We show that the number of spikes per burst varies systematically with the phase of the fluctuating input at the time of burst onset. The mapping between input phase and number of spikes per burst is a robust response feature for a broad range of stimulus statistics. Our results suggest that cortical bursting neurons could play a crucial role in translating LFP phase information into an easily decodable spike count code.
Small-World Connections to Induce Firing Activity and Phase Synchronization in Neural Networks

QIN Ying-Hua,LUO Xiao-Shu,

中国物理快报 , 2009,
Abstract: We investigate how the firing activity and the subsequent phase synchronization of neural networks with small-world topological connections depend on the probability p of adding-links. Network elements are described by two-dimensional map neurons (2DMNs) in a quiescent original state. Neurons burst for a given coupling strength when the topological randomness p increases, which is absent in a regular-lattice neural network. The bursting activity becomes frequent and synchronization of neurons emerges as topological randomness further increases. The maximal firing frequency and phase synchronization appear at a particular value of p. However, if the randomness p further increases, the firing frequency decreases and synchronization is apparently destroyed.
Global Profiling of DNA Replication Timing and Efficiency Reveals that Efficient Replication/Firing Occurs Late during S-Phase in S. pombe  [PDF]
Majid Eshaghi, R. Krishna M. Karuturi, Juntao Li, Zhaoqing Chu, Edison T. Liu, Jianhua Liu
PLOS ONE , 2007, DOI: 10.1371/journal.pone.0000722
Abstract: Background During S. pombe S-phase, initiation of DNA replication occurs at multiple sites (origins) that are enriched with AT-rich sequences, at various times. Current studies of genome-wide DNA replication profiles have focused on the DNA replication timing and origin location. However, the replication and/or firing efficiency of the individual origins on the genomic scale remain unclear. Methodology/Principal Findings Using the genome-wide ORF-specific DNA microarray analysis, we show that in S. pombe, individual origins fire with varying efficiencies and at different times during S-phase. The increase in DNA copy number plotted as a function of time is approximated to the near-sigmoidal model, when considering the replication start and end timings at individual loci in cells released from HU-arrest. Replication efficiencies differ from origin to origin, depending on the origin's firing efficiency. We have found that DNA replication is inefficient early in S-phase, due to inefficient firing at origins. Efficient replication occurs later, attributed to efficient but late-firing origins. Furthermore, profiles of replication timing in cds1Δ cells are abnormal, due to the failure in resuming replication at the collapsed forks. The majority of the inefficient origins, but not the efficient ones, are found to fire in cds1Δ cells after HU removal, owing to the firing at the remaining unused (inefficient) origins during HU treatment. Conclusions/Significance Taken together, our results indicate that efficient DNA replication/firing occurs late in S-phase progression in cells after HU removal, due to efficient late-firing origins. Additionally, checkpoint kinase Cds1p is required for maintaining the efficient replication/firing late in S-phase. We further propose that efficient late-firing origins are essential for ensuring completion of DNA duplication by the end of S-phase.
Synchronization of Firing in Cortical Fast-Spiking Interneurons at Gamma Frequencies: A Phase-Resetting Analysis  [PDF]
Nathan W. Gouwens ,Hugo Zeberg ,Kunichika Tsumoto,Takashi Tateno,Kazuyuki Aihara,Hugh P. C. Robinson
PLOS Computational Biology , 2010, DOI: 10.1371/journal.pcbi.1000951
Abstract: Fast-spiking (FS) cells in the neocortex are interconnected both by inhibitory chemical synapses and by electrical synapses, or gap-junctions. Synchronized firing of FS neurons is important in the generation of gamma oscillations, at frequencies between 30 and 80 Hz. To understand how these synaptic interactions control synchronization, artificial synaptic conductances were injected in FS cells, and the synaptic phase-resetting function (SPRF), describing how the compound synaptic input perturbs the phase of gamma-frequency spiking as a function of the phase at which it is applied, was measured. GABAergic and gap junctional conductances made distinct contributions to the SPRF, which had a surprisingly simple piecewise linear form, with a sharp midcycle break between phase delay and advance. Analysis of the SPRF showed how the intrinsic biophysical properties of FS neurons and their interconnections allow entrainment of firing over a wide gamma frequency band, whose upper and lower frequency limits are controlled by electrical synapses and GABAergic inhibition respectively.
Binding by Asynchrony: The Neuronal Phase Code  [PDF]
Zoltan Nadasdy
Frontiers in Neuroscience , 2010, DOI: 10.3389/fnins.2010.00051
Abstract: Neurons display continuous subthreshold oscillations and discrete action potentials (APs). When APs are phase-locked to the subthreshold oscillation, we hypothesize they represent two types of information: the presence/absence of a sensory feature and the phase of subthreshold oscillation. If subthreshold oscillation phases are neuron-specific, then the sources of APs can be recovered based on the AP times. If the spatial information about the stimulus is converted to AP phases, then APs from multiple neurons can be combined into a single axon and the spatial configuration reconstructed elsewhere. For the reconstruction to be successful, we introduce two assumptions: that a subthreshold oscillation field has a constant phase gradient and that coincidences between APs and intracellular subthreshold oscillations are neuron-specific as defined by the “interference principle.” Under these assumptions, a phase-coding model enables information transfer between structures and reproduces experimental phenomenons such as phase precession, grid cell architecture, and phase modulation of cortical spikes. This article reviews a recently proposed neuronal algorithm for information encoding and decoding from the phase of APs (Nadasdy, 2009). The focus is given to the principles common across different systems instead of emphasizing system specific differences.
Minimal qudit code for a qubit in the phase-damping channel  [PDF]
Stefano Pirandola,Stefano Mancini,Samuel L. Braunstein,David Vitali
Physics , 2007, DOI: 10.1103/PhysRevA.77.032309
Abstract: Using the stabilizer formalism we construct the minimal code into a D-dimensional Hilbert space (qudit) to protect a qubit against phase damping. The effectiveness of this code is then studied by means of input-output fidelity.
Two phase flow models in DxUNSp code platform
Catalin NAE
INCAS Bulletin , 2011, DOI: 10.13111/2066-8201.2011.3.3.10
Abstract: The aim of this work is to find an efficient implementation for a two phase flow model in an existing URANS CFD code platform (DxUNSp), initially based on unsteady URANS equations with a k- turbulence model and various other extensions, ranging from a broad selection of wall laws up to a very efficient LES model. This code has the capability for development for nonreacting/reacting multifluid flows for research applications and is under continuous progress. It is intend to present mainly three aspects of this implementation for unstructured mesh based solvers, for high Reynolds compressible flows: the importance of the 5/7 equation model, performance with respect to a basic test cases and implementation details of the proposed schemes. From a numerical point of view, we propose a new approximation schemes of this system based on the VFRoe-ncv.
Robustness of a topological phase: Topological color code in parallel magnetic field  [PDF]
Saeed S. Jahromi,Mehdi Kargarian,S Farhad Masoudi,Kai Phillip Schmidt
Physics , 2012, DOI: 10.1103/PhysRevB.87.094413
Abstract: The robustness of the topological color code, which is a class of error correcting quantum codes, is investigated under the influence of an uniform magnetic field on the honeycomb lattice. Our study relies on two high-order series expansions using perturbative continuous unitary transformations in the limit of low and high fields, exact diagonalization and a classical approximation. We show that the topological color code in a single parallel field is isospectral to the Baxter-Wu model in a transverse field on the triangular lattice. It is found that the topological phase is stable up to a critical field beyond which it breaks down to the polarized phase by a first-order phase transition. The results also suggest that the topological color code is more robust than the toric code, in the parallel magnetic field.
Iterative Code-Aided ML Phase Estimation and Phase Ambiguity Resolution  [cached]
Henk Wymeersch,Marc Moeneclaey
EURASIP Journal on Advances in Signal Processing , 2005, DOI: 10.1155/asp.2005.981
Abstract: As many coded systems operate at very low signal-to-noise ratios, synchronization becomes a very difficult task. In many cases, conventional algorithms will either require long training sequences or result in large BER degradations. By exploiting code properties, these problems can be avoided. In this contribution, we present several iterative maximum-likelihood (ML) algorithms for joint carrier phase estimation and ambiguity resolution. These algorithms operate on coded signals by accepting soft information from the MAP decoder. Issues of convergence and initialization are addressed in detail. Simulation results are presented for turbo codes, and are compared to performance results of conventional algorithms. Performance comparisons are carried out in terms of BER performance and mean square estimation error (MSEE). We show that the proposed algorithm reduces the MSEE and, more importantly, the BER degradation. Additionally, phase ambiguity resolution can be performed without resorting to a pilot sequence, thus improving the spectral efficiency.
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