Coding Efficiency of Fly Motion Processing Is Set by Firing Rate,Not Firing Precision

To comprehend the principles underlying sensory information processing, it is important to understand how the nervous system deals with various sources of perturbation. Here, we analyze how the representation of motion information in the fly''s nervous system changes with temperature and luminance. Although these two environmental variables have a considerable impact on the fly''s nervous system, they do not impede the fly to behave suitably over a wide range of conditions. We recorded responses from a motion-sensitive neuron, the H1-cell, to a time-varying stimulus at many different combinations of temperature and luminance. We found that the mean firing rate, but not firing precision, changes with temperature, while both were affected by mean luminance. Because we also found that information rate and coding efficiency are mainly set by the mean firing rate, our results suggest that, in the face of environmental perturbations, the coding efficiency is improved by an increase in the mean firing rate, rather than by an increased firing precision.     

Firing up mitochondrial activities with PTPMT1

Pagliarini et al (2005) recently identified a new mitochondrial specific protein tyrosine phosphatase, PTPMT1. This report comments on its consequences for mitochondrial function and on its potential to act as a therapeutic target in diabetes and cancer.     

Persistent Firing and Adaptation in Optic-Flow-Sensitive Descending Neurons

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Effects of Mean Firing on Neural Information Rate

We investigated the effect of mean firing on the information rate of a spiking motion-sensitive neuron in the fly (H1-cell). In the control condition, the cell was stimulated repeatedly by identical zero-symmetrical white-noise motion. The mean firing rate was manipulated by adding a constant velocity offset either in the same area of the receptive field where the dynamic stimulus was displayed or in a separate one. We determined the information rate in the resulting spike trains in the time domain as the difference between the total and the noise entropy rate and found that the information rate increases with increasing mean firing under both stimulus conditions.     

Firing patterns in the adaptive exponential integrate-and-fire model

For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations.     

Burst Firing in Bee Gustatory Neurons Prevents Adaptation

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Interpretation of the Repetitive Firing of Nerve Cells

Eccentric cells of Limulus respond with repetitive firing to sustained depolarizing currents. Following stimulation with a step of current, latency is shorter than first interval and later intervals increase progressively. A shock of intensity twice threshold can evoke firing 25 msec. after an impulse. But in the same cell, a current step twice rheobase evokes a second impulse more than 50 msec. after the first, and current intensity must be raised to over five times rheobase to obtain a first interval of about 25 msec. Repetitive firing was evoked by means of trains of shocks. With stimuli of moderate intensity, firing was evoked by only some of the shocks and intervals between successive impulses increased with time. This is ascribed to accumulation of refractoriness with successive impulses. Higher frequencies of firing are obtained with shocks of intensity n x threshold than with constant currents of intensity n x rheobase. It is concluded that prolonged currents depress the processes leading to excitation and that (in the cells studied) repetitive firing is controlled both by the after-effects of firing (refractoriness) and by the depressant effects of sustained stimuli (accommodation). Development of subthreshold "graded activity" is an important process leading to excitation of eccentric cells, but is not the principal factor determining frequency of firing in response to constant currents.     

Firing responses of bursting neurons with delayed feedback

Thalamic neurons, which play important roles in the genesis of rhythmic activities of the brain, show various bursting behaviors, particularly modulated by complex thalamocortical feedback via cortical neurons. As a first step to explore this complex neural system and focus on the effects of the feedback on the bursting behavior, a simple loop structure delayed in time and scaled by a coupling strength is added to a recent mean-field model of bursting neurons. Depending on the coupling strength and delay time, the modeled neurons show two distinct response patterns: one entrained to the unperturbed bursting frequency of the neurons and one entrained to the resonant frequency of the loop structure. Transitions between these two patterns are explored in the model’s parameter space via extensive numerical simulations. It is found that at a fixed loop delay, there is a critical coupling strength at which the dominant response frequency switches from the unperturbed bursting frequency to the loop-induced one. Furthermore, alternating occurrence of these two response frequencies is observed when the delay varies at fixed coupling strength. The results demonstrate that bursting is coupled with feedback to yield new dynamics, which will provide insights into such effects in more complex neural systems.     

Mechanisms Explaining Transitions between Tonic and Phasic Firing in Neuronal Populations as Predicted by a Low Dimensional Firing Rate Model

Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.     

大鼠急性分离下丘脑神经元的自发性放电特性

目的和方法：采用电流钳技术,观察SD大鼠急性分离下丘脑神经元的自发性放电。结果：放电形式包括不放电、连续的单个放电和簇状放电等3种,但放电过程中出现一些阈下电位,这些闯下电位会明显影响神经元的放电过程,使放电表现为规则或不规则,规则放电通常由缓慢的去极化电位触发,而不规则放电常出现较多的阈下电位。结论：急性分离神经元具有与脑片和培养神经元不完全相同的放电特性,对此展开研究,有利于揭示下丘脑参与机体稳态的调控机制。     

Firing activity in slow-adapting pulmonary receptors during normal respiration

The firing activity pattern of 50 slow-adapting pulmonary receptors (SAPR) was investigated in anesthetized cats under conditions of normal respiration and quasi-static and dynamic lung inflation. A non-linear relationship was found between change in activity rate and lung capacity during inspiration in 74% of SAPR; the rate rose in proportion to an increase in lung volume in a further 16%, and changes in the rate during the respiratory cycle followed a different atypical pattern in the remaining 10%. A non-linear relationship persisted between rate and volume during quasi-static inflation of the lungs in40% of the SAPR investigated (linear in 50% of cases). During dynamic inflation, nonlinear and linear SAPR numbered 70% and 20% respectively. Summated flow of impulses from all SAPR investigated stood in a non-linear relationship to lung volume during normal breathing. Reasons for the different relationships between the activity rate of individual SAPR and lung volume during normal pulmonary ventilation and during inflation of the lungs are discussed together with possible synaptic connections between pulmonary afferents and bulbar respiratory neurons.A. A. Bogomolets Institute of Physiology, Academy of Sciences of the Ukrainian SSR, Kiev. Translated from Neirofiziologiya, Vol. 20, No. 4, pp. 518–525, July–August, 1988.     

Firing synchronization and temporal order in noisy neuronal networks

Noise-induced complete synchronization and frequency synchronization in coupled spiking and bursting neurons are studied firstly. The effects of noise and coupling are discussed. It is found that bursting neurons are easier to achieve firing synchronization than spiking ones, which means that bursting activities are more important for information transfer in neuronal networks. Secondly, the effects of noise on firing synchronization in a noisy map neuronal network are presented. Noise-induced synchronization and temporal order are investigated by means of the firing rate function and the order index. Firing synchronization and temporal order of excitatory neurons can be greatly enhanced by subthreshold stimuli with resonance frequency. Finally, it is concluded that random perturbations play an important role in firing activities and temporal order in neuronal networks.     

Firing rates of neurons with random excitation and inhibition

The expectation of the interspike interval for a Stein model neuron receiving Poisson excitation and inhibition is determined by solving a differential difference equation with both forward and backward differences. The method of solution relies on an asymptotic expansion at large initial hyperpolarizations. The asymptotic solution is continued to near threshold depolarization whereupon the boundary condition is employed along with recursion relations to obtain the complete solution. The dependency of the mean firing rate on excitation at fixed inhibition and on inhibition at fixed excitation is investigated as well as the threshold dependence at fixed input rates. The results are discussed in relation to those for intracellular current injection and synaptic input to real neurons.     

交流外电场下映射神经元放电节律的分析

神经元不同的放电节律承载着不同的刺激信息。文章基于神经元映射模型,研究低频交流电场对神经元放电节律的影响。在外部刺激下映射模型表现出丰富的放电模式,包括周期簇放电、周期峰放电、交替放电和混沌放电。神经元对刺激频率和振幅的变化极为敏感,随着频率的增大,放电节律表现出从簇放电到峰放电和混沌放电的反向加周期分岔序列;在周期节律转迁过程中存在一种新的交替节律,其放电序列为两种周期放电模式的交替,峰峰间期序列具有整数倍特征。外电场的频率影响细胞内、外离子振荡周期,导致神经元放电与刺激信号同步,对放电节律的影响更为明显。研究结果揭示了交流外电场对神经元放电节律的作用规律,有助于探寻外电场对生物神经系统兴奋性的影响和神经系统疾病的致病机理。     

Subsampling Variance for 2,4-DNT in Firing Point Soils

At 105-mm howitzer firing points, 2,4-DNT is detectable in the surface soils, but field sampling and laboratory subsampling uncertainty can be large during quantitation. The 2,4-DNT is in particulate form, within fibers or slivers of the nitrocellulose-based propellant. The slender fibers range up to 7.5 mm in length with masses of several 100 μ g. Size fractionation of a firing point soil revealed that most of the 2,4-DNT was in the 0.595- to 2.00-mm size range, although the bulk of the soil was less than 0.6 mm prior to grinding. Machine grinding for five minutes was needed to pulverize the propellant fibers sufficiently so that estimates of 2,4-DNT were reproducible in replicate analytical subsamples. To determine 2,4-DNT, we have adopted the practice of grinding firing point soils for five one-minute intervals, with time for heat dissipation between grinds, prior to obtaining individual or replicate 10-g subsamples.