Average Firing Research Articles

Forest road and fuelbreak siting with respect to reference fire intensities

Forest roads and permanent fuelbreaks are an important part of fire suppression infrastructure, but due to maintenance and environmental costs many forest agencies seek to reduce the extent of these networks. The question of which roads should be retained or where fuelbreaks should be established is contentious, and few quantified methods exist to aid management decisions. This study uses GIS procedures and develops a metric for road network vulnerability, which may be used to determine the relative effectiveness of a road network or a particular fuelbreak as a fire control line. The method constructs ‘reference fire’ intensities, and compares the fire intensity at roadsides or fuelbreaks with the overall forest average. In the case study area in Victoria’s Central Highlands (southeast Australia), average fire intensities on the forest road network are found to closely match the forest average, indicating that roads in their current locations are not skewed towards more dangerous parts of the forest. The fuelbreak network however is likely to face fire intensities substantially greater than those in the average forest area.

Approximate Invariance of Metabolic Energy per Synapse during Development in Mammalian Brains

During mammalian development the cerebral metabolic rate correlates qualitatively with synaptogenesis, and both often exhibit bimodal temporal profiles. Despite these non-monotonic dependencies, it is found based on empirical data for different mammals that regional metabolic rate per synapse is approximately conserved from birth to adulthood for a given species (with a slight deviation from this constancy for human visual and temporal cortices during adolescence). A typical synapse uses about glucose molecules per second in primate cerebral cortex, and about five times of that amount in cat and rat visual cortices. A theoretical model for brain metabolic expenditure is used to estimate synaptic signaling and neural spiking activity during development. It is found that synaptic efficacy is generally inversely correlated with average firing rate, and, additionally, synapses consume a bulk of metabolic energy, roughly during most of the developmental process (except human temporal cortex ). Overall, these results suggest a tight regulation of brain electrical and chemical activities during the formation and consolidation of neural connections. This presumably reflects strong energetic constraints on brain development.

Effect of duration of synaptic activity on spike rate of a Hodgkin-Huxley neuron with delayed feedback

A recurrent loop consisting of a single Hodgkin-Huxley neuron influenced by a chemical excitatory delayed synaptic feedback is considered. We show that the behavior of the system depends on the duration of the activity of the synapse, which is determined by the activation and deactivation time constants of the synapse. For the fast synapses, those for which the effect of the synaptic activity is small compared to the period of firing, depending on the delay time, spiking with single and multiple interspike intervals is possible and the average firing rate can be smaller or larger than that of the open loop neuron. For slow synapses for which the synaptic time constants are of order of the period of the firing, the self-excitation increases the firing rate for all values of the delay time. We also show that for a chain consisting of few similar oscillators, if the synapses are chosen from different time constants, the system will follow the dynamics imposed by the fastest element, which is the oscillator that receives excitations via a slow synapse. The generalization of the results to other types of relaxation oscillators is discussed and the results are compared to those of the loops with inhibitory synapses as well as with gap junctions.

Membrane Properties and the Balance between Excitation and Inhibition Control Gamma-Frequency Oscillations Arising from Feedback Inhibition

Computational studies as well as in vivo and in vitro results have shown that many cortical neurons fire in a highly irregular manner and at low average firing rates. These patterns seem to persist even when highly rhythmic signals are recorded by local field potential electrodes or other methods that quantify the summed behavior of a local population. Models of the 30–80 Hz gamma rhythm in which network oscillations arise through ‘stochastic synchrony’ capture the variability observed in the spike output of single cells while preserving network-level organization. We extend upon these results by constructing model networks constrained by experimental measurements and using them to probe the effect of biophysical parameters on network-level activity. We find in simulations that gamma-frequency oscillations are enabled by a high level of incoherent synaptic conductance input, similar to the barrage of noisy synaptic input that cortical neurons have been shown to receive in vivo. This incoherent synaptic input increases the emergent network frequency by shortening the time scale of the membrane in excitatory neurons and by reducing the temporal separation between excitation and inhibition due to decreased spike latency in inhibitory neurons. These mechanisms are demonstrated in simulations and in vitro current-clamp and dynamic-clamp experiments. Simulation results further indicate that the membrane potential noise amplitude has a large impact on network frequency and that the balance between excitatory and inhibitory currents controls network stability and sensitivity to external inputs.

Experience-dependent firing rate remapping generates directional selectivity in hippocampal place cells

When rodents engage in irregular foraging in an open-field environment, hippocampal principal cells exhibit place-specific firing that is statistically independent of the direction of traverse through the place field. When the path is restricted to a track, however, in-field rates differ substantially in opposite directions. Frequently, the representations of the track in the two directions are essentially orthogonal. We show that this directionally selective firing is not hard-wired, but develops through experience-dependent plasticity. During the rats' first pass in each direction, place fields were highly directionally symmetric, whereas over subsequent laps, the firing rates in the two directions gradually but substantially diverged. We conclude that, even on a restricted track, place cell firing is initially determined by allocentric position, and only later, the within-field firing rates change in response to differential sensory information or behavioral cues in the two directions. In agreement with previous data, place fields near local cues, such as textures on the track, developed less directionality than place fields on a uniform part of the track, possibly because the local cues reduced the net difference in sensory input at a given point. Directionality also developed in an open environment without physical restriction of the animal's path, when rats learned to run along a specified path. In this case, directionality developed later than on the running track, only after the rats began to run in a stereotyped manner. Although the average population firing rates exhibited little if any change over laps in either direction, the direction-specific firing rates in a given place field were up-or down-regulated with about equal probability and magnitude, which was independent in the two directions, suggesting some form of competitive mechanism (e.g., LTP/LTD) acting coherently on the set of synapses conveying external information to each cell.

Closed-Loop Measurements of Iso-Response Stimuli Reveal Dynamic Nonlinear Stimulus Integration in the Retina

Neurons often integrate information from multiple parallel signaling streams. How a neuron combines these inputs largely determines its computational role in signal processing. Experimental assessment of neuronal signal integration, however, is often confounded by cell-intrinsic nonlinear processes that arise after signal integration has taken place. To overcome this problem and determine how ganglion cells in the salamander retina integrate visual contrast over space, we used automated online analysis of recorded spike trains and closed-loop control of the visual stimuli to identify different stimulus patterns that give the same neuronal response. These iso-response stimuli revealed a threshold-quadratic transformation as a fundamental nonlinearity within the receptive field center. Moreover, for a subset of ganglion cells, the method revealed an additional dynamic nonlinearity that renders these cells particularly sensitive to spatially homogeneous stimuli. This function is shown to arise from a local inhibition-mediated dynamic gain control mechanism.

Modelling the potential for prescribed burning to mitigate carbon emissions from wildfires in fire-prone forests of Australia

Prescribed fire can potentially reduce carbon emissions from unplanned fires. This potential will differ among ecosystems owing to inherent differences in the efficacy of prescribed burning in reducing unplanned fire activity (or ‘leverage’, i.e. the reduction in area of unplanned fire per unit area of prescribed fire). In temperate eucalypt forests, prescribed burning leverage is relatively low and potential for mitigation of carbon emissions from unplanned fires via prescribed fire is potentially limited. Simulations of fire regimes accounting for non-linear patterns of fuel dynamics for three fuel types characteristic of eucalypt forests in south-eastern Australia supported this prediction. Estimated mean annual fuel consumption increased with diminishing leverage and increasing rate of prescribed burning, even though average fire intensity (prescribed and unplanned fires combined) decreased. The results indicated that use of prescribed burning in these temperate forests is unlikely to yield a net reduction in carbon emissions. Future increases in burning rates under climate change may increase emissions and reduce carbon sequestration. A more detailed understanding of the efficacy of prescribed burning and dynamics of combustible biomass pools is required to clarify the potential for mitigation of carbon emissions in temperate eucalypt forests and other ecosystems.

Neural learning circuits utilizing nano-crystalline silicon transistors and memristors.

Properties of neural circuits are demonstrated via SPICE simulations and their applications are discussed. The neuron and synapse subcircuits include ambipolar nano-crystalline silicon transistor and memristor device models based on measured data. Neuron circuit characteristics and the Hebbian synaptic learning rule are shown to be similar to biology. Changes in the average firing rate learning rule depending on various circuit parameters are also presented. The subcircuits are then connected into larger neural networks that demonstrate fundamental properties including associative learning and pulse coincidence detection. Learned extraction of a fundamental frequency component from noisy inputs is demonstrated. It is then shown that if the fundamental sinusoid of one neuron input is out of phase with the rest, its synaptic connection changes differently than the others. Such behavior indicates that the system can learn to detect which signals are important in the general population, and that there is a spike-timing-dependent component of the learning mechanism. Finally, future circuit design and considerations are discussed, including requirements for the memristive device.

Corrigendum to: Factors influencing large wildland fire suppression expenditures

There is an urgent and immediate need to address the excessive cost of large fires. Here, we studied large wildland fire suppression expenditures by the US Department of Agriculture Forest Service. Among 16 potential non-managerial factors, which represented fire size and shape, private properties, public land attributes, forest and fuel conditions, and geographic settings, we found only fire size and private land had a strong effect on suppression expenditures. When both were accounted for, all the other variables had no significant effect. A parsimonious model to predict suppression expenditures was suggested, in which fire size and private land explained 58% of variation in expenditures. Other things being equal, suppression expenditures monotonically increased with fire size. For the average fire size, expenditures first increased with the percentage of private land within burned area, but as the percentage exceeded 20%, expenditures slowly declined until they stabilised when private land reached 50% of burned area. The results suggested that efforts to contain federal suppression expenditures need to focus on the highly complex, politically sensitive topic of wildfires on private land.

Effects of fatigue on motor unit firing rate versus recruitment threshold relationships

The purpose of this study was to examine the influence of fatigue on the average firing rate versus recruitment threshold relationships for the vastus lateralis (VL) and vastus medialis. Nineteen subjects performed ten maximum voluntary contractions of the dominant leg extensors. Before and after this fatiguing protocol, the subjects performed a trapezoid isometric muscle action of the leg extensors, and bipolar surface electromyographic signals were detected from both muscles. These signals were then decomposed into individual motor unit action potential trains. For each subject and muscle, the relationship between average firing rate and recruitment threshold was examined using linear regression analyses. For the VL, the linear slope coefficients and y-intercepts for these relationships increased and decreased, respectively, after fatigue. For both muscles, many of the motor units decreased their firing rates. With fatigue, recruitment of higher threshold motor units resulted in an increase in slope for the VL.

Representation of Perceptually Invisible Image Motion in Extrastriate Visual Area MT of Macaque Monkeys

Why does the world appear stable despite the visual motion induced by eye movements during fixation? We find that the answer must reside in how visual motion signals are interpreted by perception, because MT neurons in monkeys respond to the image motion caused by eye drifts in the presence of a stationary stimulus. Several features suggest a visual origin for the responses of MT neurons during fixation: spike-triggered averaging yields a peak image velocity in the preferred direction that precedes spikes by ∼60 ms; image velocity during fixation and firing rate show similar peaks in power at 4-5 Hz; and average MT firing during a period of fixation is related monotonically to the image speed along the preferred axis of the neurons 60 ms earlier. The percept caused by the responses of MT neurons during fixation depends on the distribution of activity across the population of neurons of different preferred speeds. For imposed stimulus motion, the population response peaks for neurons that prefer the actual target speed. For small image motions caused by eye drifts during fixation, the population response is large, but is noisy and does not show a clear peak. This representation of image motion in MT would be ignored if perception interprets the population response in the context of a prior of zero speed. Then, we would see a stable scene despite MT responses caused by eye drifts during fixation.

Spiking patterns of a minimal neuron to ELF sinusoidal electric field

Neuron as the main information carrier in neural systems is able to generate diverse spiking trains in response to different stimuli. Neuronal spiking patterns are related to the information processing in neural system. This paper investigates the dynamical behaviors of a two-dimensional minimal neuron model exposed to externally-applied extremely low frequency (ELF) sinusoidal electric field (EF). By numerical stimulation, it is found that neuron can exhibit different spiking patterns such as p:q mode-locking (i.e. a periodic oscillation defined as p action potentials generated by q cycle stimulations) and chaotic behaviors, depending on the values of stimulus frequencies. Transitions between different spiking patterns during exposure to the external EF are explored by interspike intervals (ISIs) and average firing rate. It is found that frequencies of the external EF can act as a bifurcation parameter, whose small change can cause the transition in neuronal behaviors. It is shown that a rich bifurcation structure including period-adding without chaos and mode-locking alternated with chaos suggests frequency discrimination of the neuronal firing patterns. Our results can provide a useful insight into the organization of similar bifurcation structures in excitable systems such as neurons under periodic forcing. Through detail analysis of the spiking patterns, we have explained how neuron’s information (spiking patterns) encodes the stimulus information (frequency), and vice versa.

Understanding Shifts in Wildfire Regimes as Emergent Threshold Phenomena

Ecosystems driven by wildfire regimes are characterized by fire size distributions resembling power laws. Existing models produce power laws, but their predicted exponents are too high and fail to capture the exponent's variation with geographic region. Here we present a minimal model of fire dynamics that describes fire spread as a stochastic birth-death process, analogous to stochastic population growth or disease spread and incorporating memory effects from previous fires. The model reproduces multiple regional patterns in fire regimes and allows us to classify different regions in terms of their proximity to a critical threshold. Transitions across this critical threshold imply abrupt and pronounced increases in average fire size. The model predicts that large regions in Canada are currently close to this transition and might be driven beyond the threshold in the future. We illustrate this point by analyzing the time series for large fires (>199 ha) from the Canadian Boreal Plains, found to have shifted from a subcritical regime to a critical regime in the recent past. By contrast to its predecessor, the model also suggests that a critical transition, and not self-organized criticality, underlies forest fire dynamics, with implications for other ecological systems exhibiting power-law-like patterns, in particular for their sensitivity to environmental change and control efforts.

Dentate gyrus granule cell firing patterns can induce mossy fiber long‐term potentiation in vitro

Hippocampal granule cells transmit information about behaviorally-relevant stimuli to CA3 pyramidal cells via mossy fiber synapses. These synapses express a form of long-term potentiation (mfLTP) that is non-Hebbian and does not require NMDA receptors. mfLTP is thought to be induced and expressed presynaptically, hence, the major determinant of whether mfLTP occurs is activity in the granule cells. However, it remains unclear whether mfLTP can be induced by activity patterns that granule cells exhibit in vivo, and-if so-what context generates these patterns. To address these issues, we examined granule cell activity from in vivo recordings from rats during performance of a delayed nonmatch-to-sample (DNMS) task and found that granule cells exhibit a wide range of spike patterns. In vitro slice experiments in mice demonstrated that some, but not all, of these patterns of activity could induce mfLTP. By further defining the activity thresholds for mfLTP in hippocampal slices, we found that mfLTP can only be induced by spike patterns that fire in high frequency bursts with a low average firing frequency. Using this information, we then screened for suprathreshold bursts of activity during the DNMS task. In a subset of cells, suprathreshold bursts occurred preferentially during the sampling phase of the task. If suprathreshold bursting took place later, during the delay phase, task performance was disrupted. We conclude that mfLTP can be induced by granule cell spike patterns during a memory task, and that the timing of mfLTP induction can predict task performance.

Central chemoreceptor modulation of breathing via multipath tuning in medullary ventrolateral respiratory column circuits

Ventrolateral respiratory column (VRC) circuits that modulate breathing in response to changes in central chemoreceptor drive are incompletely understood. We employed multielectrode arrays and spike train correlation methods to test predictions of the hypothesis that pre-Bötzinger complex (pre-BötC) and retrotrapezoid nucleus/parafacial (RTN-pF) circuits cooperate in chemoreceptor-evoked tuning of ventral respiratory group (VRG) inspiratory neurons. Central chemoreceptors were selectively stimulated by injections of CO(2)-saturated saline into the vertebral artery in seven decerebrate, vagotomized, neuromuscularly blocked, and artificially ventilated cats. Among sampled neurons in the Bötzinger complex (BötC)-to-VRG region, 70% (161 of 231) had a significant change in firing rate after chemoreceptor stimulation, as did 70% (101 of 144) of the RTN-pF neurons. Other responsive neurons (24 BötC-VRG; 11 RTN-pF) had a change in the depth of respiratory modulation without a significant change in average firing rate. Seventy BötC-VRG chemoresponsive neurons triggered 189 offset-feature correlograms (96 peaks; 93 troughs) with at least one responsive BötC-VRG cell. Functional input from at least one RTN-pF cell could be inferred for 45 BötC-VRG neurons (19%). Eleven RTN-pF cells were correlated with more than one BötC-VRG target neuron, providing evidence for divergent connectivity. Thirty-seven RTN-pF neurons, 24 of which were chemoresponsive, were correlated with at least one chemoresponsive BötC-VRG neuron. Correlation linkage maps and spike-triggered averages of phrenic nerve signals suggest transmission of chemoreceptor drive via a multipath network architecture: RTN-pF modulation of pre-BötC-VRG rostral-to-caudal excitatory inspiratory neuron chains is tuned by feedforward and recurrent inhibition from other inspiratory neurons and from "tonic" expiratory neurons.

Neuron-Specific Stimulus Masking Reveals Interference in Spike Timing at the Cortical Level

The auditory system is capable of robust recognition of sounds in the presence of competing maskers (e.g., other voices or background music). This capability arises despite the fact that masking stimuli can disrupt neural responses at the cortical level. Since the origins of such interference effects remain unknown, in this study, we work to identify and quantify neural interference effects that originate due to masking occurring within and outside receptive fields of neurons. We record from single and multi-unit auditory sites from field L, the auditory cortex homologue in zebra finches. We use a novel method called spike timing-based stimulus filtering that uses the measured response of each neuron to create an individualized stimulus set. In contrast to previous adaptive experimental approaches, which have typically focused on the average firing rate, this method uses the complete pattern of neural responses, including spike timing information, in the calculation of the receptive field. When we generate and present novel stimuli for each neuron that mask the regions within the receptive field, we find that the time-varying information in the neural responses is disrupted, degrading neural discrimination performance and decreasing spike timing reliability and sparseness. We also find that, while removing stimulus energy from frequency regions outside the receptive field does not significantly affect neural responses for many sites, adding a masker in these frequency regions can nonetheless have a significant impact on neural responses and discriminability without a significant change in the average firing rate. These findings suggest that maskers can interfere with neural responses by disrupting stimulus timing information with power either within or outside the receptive fields of neurons.

Dispatches

Dispatches

Single-Unit Responses Selective for Whole Faces in the Human Amygdala

The human amygdala is critical for social cognition from faces, as borne out by impairments in recognizing facial emotion following amygdala lesions [1] and differential activation of the amygdala by faces [2-5]. Single-unit recordings in the primate amygdala have documented responses selective for faces, their identity, or emotional expression [6, 7], yet how the amygdala represents face information remains unknown. Does it encode specific features of faces that are particularly critical for recognizing emotions (such as the eyes), or does it encode the whole face, a level of representation that might be the proximal substrate for subsequent social cognition? We investigated this question by recording from over 200 single neurons in the amygdalae of seven neurosurgical patients with implanted depth electrodes [8]. We found that approximately half of all neurons responded to faces or parts of faces. Approximately 20% of all neurons responded selectively only to the whole face. Although responding most to whole faces, these neurons paradoxically responded more when only a small part of the face was shown compared to when almost the entire face was shown. We suggest that the human amygdala plays a predominant role in representing global information about faces, possibly achieved through inhibition between individual facial features.

Mechanisms of repetition suppression in models, monkeys, and humans: A case for greater efficiency through enhanced synchronization

Experience with visual objects leads to later improvements in identification speed and accuracy (“repetition priming”), but generally leads to reductions in neural activity in single-cell recording studies in monkeys and fMRI studies in humans (“repetition suppression”). While the cell mechanisms that lead to these activity reductions are unclear, previous studies have implicated relatively local, automatic cortical mechanisms, and slice physiological recordings have identified several candidate short- and long-term plasticity mechanisms. I will show that these plasticity mechanisms when incorporated into a simplified neocortical circuit model are capable of re-producing changes in stimulus selectivity due to repetition as seen in single-cell recording studies in monkey area TE: “scaling” with relatively short-term repetitions and “sharpening” over longer periods of experience. However, these simulations when based on average firing rate fail to provide an account of behavioral priming. In contrast, simulations that retain the spiking property of neurons can potentially account for both repetition suppression and priming by allowing more synchronized and temporally coordinated activity at lower overall rates. I will review the current state of evidence in support of this proposal from monkey single-cell and LFP recordings and human MEG. I will also present new data from intracranial EEG recordings of human epilepsy patients showing that stimulus repetition at both short and long time scales leads to larger amplitude activity fluctuations at low frequencies (<15 Hz). These results indicate that greater neural synchronization accompanies lower overall activity levels following stimulus repetition, constituting a novel efficiency mechanism.

Acute Effects of Nicotine Amplify Accumbal Neural Responses during Nicotine-Taking Behavior and Nicotine-Paired Environmental Cues

Nicotine self-administration (SA) is maintained by several variables, including the reinforcing properties of nicotine-paired cues and the nicotine-induced amplification of those cue properties. The nucleus accumbens (NAc) is implicated in mediating the influence of these variables, though the underlying neurophysiological mechanisms are not yet understood. In the present study, Long-Evans rats were trained to self-administer nicotine. During SA sessions each press of a lever was followed by an intravenous infusion of nicotine (30 µg/kg) paired with a combined light-tone cue. Extracellular recordings of single-neuron activity showed that 20% of neurons exhibited a phasic change in firing during the nicotine-directed operant, the light-tone cue, or both. The phasic change in firing for 98% of neurons was an increase. Sixty-two percent of NAc neurons additionally or alternatively showed a sustained decrease in average firing during the SA session relative to a presession baseline period. These session decreases in firing were significantly less prevalent in a group of neurons that were activated during either the operant or the cue than in a group of neurons that were nonresponsive during those events (referred to as task-activated and task-nonactivated neurons, respectively). Moreover, the session decrease in firing was dose-dependent for only the task-nonactivated neurons. The data of the present investigation provide supportive correlational evidence for two hypotheses: (1) excitatory neurophysiological mechanisms mediate the NAc role in cue-maintenance of nicotine SA, and (2) a differential nicotine-induced inhibition of task-activated and task-nonactivated neurons mediates the NAc role in nicotine-induced amplification of cue effects on nicotine SA.