Mechanism Of Burst Generation Research Articles

Automated identification and characterization method of turbulent bursting from single-point records of the velocity field

A new automated method capable of accurately identifying bursting periods in single-point turbulent velocity field records is presented. Manual selection of the method sensitivity and threshold are necessary for effective discrimination between burst periods and the background turbulent flow fluctuations (burst-free periods). The flow characteristic used for identification is the normalized ‘instantaneous’ TKE dissipation rate levels, calculated using sliding window averaging. Use of the record root mean square and average values for normalization eliminates the need for definition of a physics-based flow-specific threshold. Instead, the suitable sensitivity range and the threshold parameters are selected based on preliminary examination of the velocity records. This, potentially, makes the method applicable for use across various flow fields, especially as it does not require resolving the burst-generation mechanism. The method performance is examined using a field obtained dataset of buoyancy driven turbulent boundary layer flow. Here, the selection of a two-fold increase is used and the sensitivity of the method is examined. Spectral shapes of non-bursting periods show distinguished similarity to those of the Kolmogorov theory, while the bursting period spectral shapes vary significantly. Low-resolution records of temperature fluctuations were observed to exhibit a significant decrease in temperature (scalar) dissipation rate during bursting periods. Based on this observation and additional processing, a statistical examination of temperature (scalar) dissipation rate is presented along with a normalization procedure. Future examination of additional scalar variations, i.e. particulate matter and/or gaseous pollutant concentrations, in connection with turbulent bursting periods can assist in further understanding of bursting generation and scalar transfer processes.

Refractoriness Accounts for Variable Spike Burst Responses in Somatosensory Cortex.

Neurons in the primary somatosensory cortex (S1) respond to peripheral stimulation with synchronized bursts of spikes, which lock to the macroscopic 600-Hz EEG waves. The mechanism of burst generation and synchronization in S1 is not yet understood. Using models of single-neuron responses fitted to unit recordings from macaque monkeys, we show that these synchronized bursts are the consequence of correlated synaptic inputs combined with a refractory mechanism. In the presence of noise these models reproduce also the observed trial-to-trial response variability, where individual bursts represent one of many stereotypical temporal spike patterns. When additional slower and global excitability fluctuations are introduced the single-neuron spike patterns are correlated with the population activity, as demonstrated in experimental data. The underlying biophysical mechanism of S1 responses involves thalamic inputs arriving through depressing synapses to cortical neurons in a high-conductance state. Our findings show that a simple feedforward processing of peripheral inputs could give rise to neuronal responses with nontrivial temporal and population statistics. We conclude that neural systems could use refractoriness to encode variable cortical states into stereotypical short-term spike patterns amenable to processing at neuronal time scales (tens of milliseconds).

Bounded stability of the quiet standing posture: An intermittent control model

The paper presents a control model of body sway in quiet standing, which aims at achieving bounded stability by means of an intermittent control mechanism. Control bursts are generated when the current state vector exits an area of uncertainty around the reference point in the phase plane. This area is determined by the limited resolution of proprioceptive signals and the burst generation mechanism is predictive in the sense that it incorporates a rough, but working knowledge (internal model) of the biomechanics of the human inverted pendulum. We show that such a model, in spite of its simplicity and of the fact that it relies on very noisy measurements, is robust and can explain in a detailed way the measured sway patterns.

Network Mechanism for Burst Generation

We report on the mechanism of burst generation by populations of intrinsically spiking neurons, when a certain threshold in coupling strength is exceeded. These ensembles synchronize at relatively low coupling strength and lose synchronization at stronger coupling via spatiotemporal intermittency. The latter transition triggers fast repetitive spiking, which results in synchronized bursting. We present evidence that this mechanism is generic for various network topologies from regular to small-world and scale-free ones, different types of coupling and neuronal model.

Analysis of spontaneous bursting activity in random neural networks

Developing networks can generate bursting activity despite the absence of pacemaker cells and inhibitory synapses. Bursts are generated by positive feedback through excitatory connections and terminated by a slow depression of network excitability. Similar activity has been observed in cultures of spinal neurons containing inhibitory synapses. Is burst generation in these cultures operating according to the mechanism proposed for developing networks? To answer this question without perturbing the activity, we analyzed the burst pattern of individual neurons in active cultures. We observed a correlation between burst size and preceding interburst interval and a rapid rise and progressive decrease in firing rate during a burst. These findings are consistent with the mechanism of burst generation proposed for developing networks.

Persistent sodium current, membrane properties and bursting behavior of pre-bötzinger complex inspiratory neurons in vitro.

We measured persistent Na(+) current and membrane properties of bursting-pacemaker and nonbursting inspiratory neurons of the neonatal rat pre-Bötzinger complex (pre-BötC) in brain stem slice preparations with a rhythmically active respiratory network in vitro. In whole-cell recordings, slow voltage ramps (</=100 mV/s) inactivated the fast, spike-generating Na(+) current and yielded N-shaped current-voltage relationships with nonmonotonic, negative-slope regions between -60 and -35 mV when the voltage-sensitive component was isolated. The underlying current was a TTX-sensitive persistent Na(+) current (I(NaP)) since the inward current was present at slow voltage ramp speeds (3.3-100 mV/s) and the current was blocked by 1 microM TTX. We measured the biophysical properties of I(NaP) after subtracting the voltage-insensitive "leak" current (I(Leak)) in the presence of Cd(2+) and in some cases tetraethylammonium (TEA). Peak I(NaP) ranged from -50 to -200 pA at a membrane potential of -30 mV. Decreasing the speed of the voltage ramp caused time-dependent I(NaP) inactivation, but this current was present at ramp speeds as low as 3.3 mV/s. I(NaP) activated at -60 mV and obtained half-maximal activation near -40 mV. The subthreshold voltage dependence and slow inactivation kinetics of I(NaP), which closely resemble those of I(NaP) mathematically modeled as a burst-generation mechanism in pacemaker neurons of the pre-BötC, suggest that I(NaP) predominantly influences bursting dynamics of pre-BötC inspiratory pacemaker neurons in vitro. We also found that the ratio of persistent Na(+) conductance to leak conductance (g(NaP)/g(Leak)) can distinguish the phenotypic subpopulations of bursting pacemaker and nonbursting inspiratory neurons: pacemaker neurons showed g(NaP)/g(Leak) > g(NaP)/g(Leak) in nonpacemaker cells (P < 0.0002). We conclude that I(NaP) is ubiquitously expressed by pre-BötC inspiratory neurons and that bursting pacemaker behavior within the heterogeneous population of inspiratory neurons is achieved with specific ratios of these two conductances, g(NaP) and g(Leak).

Bursting Neurons Signal Input Slope

Brief bursts of high-frequency action potentials represent a common firing mode of pyramidal neurons, and there are indications that they represent a special neural code. It is therefore of interest to determine whether there are particular spatial and temporal features of neuronal inputs that trigger bursts. Recent work on pyramidal cells indicates that bursts can be initiated by a specific spatial arrangement of inputs in which there is coincident proximal and distal dendritic excitation (Larkum et al., 1999). Here we have used a computational model of an important class of bursting neurons to investigate whether there are special temporal features of inputs that trigger bursts. We find that when a model pyramidal neuron receives sinusoidally or randomly varying inputs, bursts occur preferentially on the positive slope of the input signal. We further find that the number of spikes per burst can signal the magnitude of the slope in a graded manner. We show how these computations can be understood in terms of the biophysical mechanism of burst generation. There are several examples in the literature suggesting that bursts indeed occur preferentially on positive slopes (Guido et al., 1992; Gabbiani et al., 1996). Our results suggest that this selectivity could be a simple consequence of the biophysics of burst generation. Our observations also raise the possibility that neurons use a burst duration code useful for rapid information transmission. This possibility could be further examined experimentally by looking for correlations between burst duration and stimulus variables.

Modeling N-methyl-D-aspartate-induced bursting in dopamine neurons.

Burst firing of dopaminergic neurons of the substantia nigra pars compacta can be induced in vitro by the glutamate agonist N-methyl-D-aspartate. It has been suggested that the interburst hyperpolarization is due to Na+ extrusion by a ouabain-sensitive pump [Johnson et al. (1992) Science 258, 665-667]. We formulate and explore a theoretical model, with a minimal number of currents, for this novel mechanism of burst generation. This minimal model is further developed into a more elaborate model based on observations of additional currents and hypotheses about their spatial distribution in dopaminergic neurons [Hounsgaard (1992) Neuroscience 50, 513-518; Llinás et al. (1984) Brain Res. 294, 127-132]. Using the minimal model, we confirm that interaction between the regenerative, inward N-methyl-D-aspartate-mediated current and the outward Na(+)-pump current is sufficient to generate the slow oscillation (approximately 0.5 Hz) underlying the burst. The negative-slope region of the N-methyl-D-aspartate channel's current-voltage relation is indispensable for this slow rhythm generation. The time-scale of Na(+)-handling determines the burst's slow frequency. Moreover, we show that, given the constraints of sodium handling, such bursting is best explained mechanistically by using at least two spatial, cable-like compartments: a soma where action potentials are produced and a dendritic compartment where the slow rhythm is generated. Our result is consistent with recent experimental evidence that burst generation originates in distal dendrites [Seutin et al. (1994) Neuroscience 58, 201-206]. Responses of the model to a number of electrophysiological and pharmacological stimuli are consistent with known responses observed under similar conditions. These include the persistence of the slow rhythm when the tetrodotoxin-sensitive Na+ channel is blocked and when the soma is voltage-clamped at -60 mV. Using our more elaborate model, we account for details of the observed frequency adaptation in N-methyl-D-aspartate-induced bursting, the origin of multiple spiking and bursting mechanisms, and the interaction between two different bursting mechanisms. Besides reproducing several well established firing patterns, this model also suggests that new firing modes, not yet recorded, might also occur in dopaminergic neurons. This model provides mechanistic insights and explanations into the origin of a variety of experimentally observed membrane potential firing patterns in dopaminergic neurons, including N-methyl-D-aspartate-induced bursting and its dendritic origin. Such a model, capable of reproducing a number of realistic behaviors of dopaminergic neurons, could be useful in further studies of the basal ganglia-thalamocortical motor circuit. It may also shed light on bursting that involves N-methyl-D-aspartate channel activity in other neuron types.

Decameter solar type III bursts: Data classification with use of cluster analysis

The many-parametric data on decametric type III bursts containing more than 1000 events were classified with use of cluster analysis, i.e., the pattern recognition procedure. For the classification such parameters have been used as intensity, duration and degree of circular polarization derived from burst time profiles. The automatic classification has resulted in division of daily samples of type III bursts into classes of bursts, more homogeneous statistically, which can be associated with different components of type III radiation distinguished by their physical origin. For the classes obtained, statistically reliable dependences of the mean intensity on source position can be found which allow one to conclude about the source structure and evolution, as well as about the characteristics defined by a burst generation mechanism and propagation effects.

Burst firing in dopamine neurons induced by N-methyl-D-aspartate: role of electrogenic sodium pump.

Dopamine-containing neurons of the mammalian midbrain are required for normal behavior and movements. In vivo they fire action potentials in bursts, but in vitro they discharge regularly spaced action potentials. Burst firing in vitro has now been shown to be robustly induced by the glutamate agonist N-methyl-D-aspartate (NMDA) although not by the non-NMDA agonists kainate or quisqualate. The hyperpolarization between bursts of action potentials results from electrogenic sodium ion extrusion by a ouabain-sensitive pump. This mechanism of burst generation in mammalian neurons may be important in the pathophysiology of schizophrenia and Parkinson's disease.

Bifurcations and bursting in two-dimensional Poiseuille flow

The bifurcations to two-dimensional unsteady behavior of a large amplitude equilibrium shear wave train in two-dimensional Poiseuille flow are studied by direct simulation of the time evolution of the full Navier–Stokes equations. It is found that the wave train becomes unstable at Re∼5600, and sheds a limit cycle which, at higher Re, seems to undergo further transitions to more complex behaviors. It is shown that the site of the original bifurcation is in the neighborhood of the walls and that it shows some characteristics suggestive of the burst generation mechanism in the boundary layer.

A field-effect transistor analog for the study of burst-generating neurons

An electronic analog based on the four-branch Hodgkin-Huxley equivalent circuit for the cell membrane is described. Two additional branches are included to realize the subthreshold membrane potential oscillations underlying burst generation. The analog is used to study the mechanism of burst generation, the progressive widening of the action potentials as a burst develops, and the possible effects of the accumulation of K+ions outside the cell membrane.