Role of spike-frequency adaptation in shaping neuronal response to dynamic stimuli

Spike-frequency adaptation is the reduction of a neuron’s firing rate to a stimulus of constant intensity. In the locust, the Lobula Giant Movement Detector (LGMD) is a visual interneuron that exhibits rapid adaptation to both current injection and visual stimuli. Here, a reduced compartmental model of the LGMD is employed to explore adaptation’s role in selectivity for stimuli whose intensity changes with time. We show that supralinearly increasing current injection stimuli are best at driving a high spike count in the response, while linearly increasing current injection stimuli (i.e., ramps) are best at attaining large firing rate changes in an adapting neuron. This result is extended with in vivo experiments showing that the LGMD’s response to translating stimuli having a supralinear velocity profile is larger than the response to constant or linearly increasing velocity translation. Furthermore, we show that the LGMD’s preference for approaching versus receding stimuli can partly be accounted for by adaptation. Finally, we show that the LGMD’s adaptation mechanism appears well tuned to minimize sensitivity for the level of basal input. This article is part of a special issue on Neuronal Dynamics of Sensory Coding.     

Non-Gaussian noise optimized spiking activity of Hodgkin–Huxley neurons on random complex networks

In this paper, we numerically study how the NGN's deviation q from Gaussian noise (q = 1) affects the spike coherence and synchronization of 60 coupled Hodgkin–Huxley (HH) neurons driven by a periodic sinusoidal stimulus on random complex networks. It is found that the effect of the deviation depends on the network randomness p (the fraction of random shortcuts): for larger p (p > 0.15), the spiking regularity keeps being improved with increasing q; while, for smaller p (p < 0.15), the spiking regularity can reach the best performance at an optimal intermediate q value, indicating the occurrence of “deviation-optimized spike coherence”. The synchronization becomes enhanced with decreasing q, and the enhancing extent for a random HH neuron network is stronger than for a regular one. These behaviors show that the spike coherence and synchronization of the present HH neurons on random networks can be more strongly enhanced by various other types of external noise than by Gaussian noise, whereby the neuron firings may behave more periodically in time and more synchronously in space. Our results provide the constructive roles of the NGN on the spiking activity of the present system of HH neuron networks.     

Frequency-dependent response of SI RA-class neurons to vibrotactile stimulation of the receptive field

Three types of experiment were carried out on anesthetized monkeys and cats. In the first, spike discharge activity of rapidly adapting (RA) SI neurons was recorded extracellularly during the application of different frequencies of vibrotactile stimulation to the receptive field (RF). The second used the same stimulus conditions to study the response of RA-I (RA) cutaneous mechanoreceptive afferents. The third used optical intrinsic signal (OIS) imaging and extracellular neurophysiological recording methods together, in the same sessions, to evaluate the relationship between the SI optical and RA neuron spike train responses to low- vs high-frequency stimulation of the same skin site. RA afferent entrainment was high at all frequencies of stimulation. In contrast, SI RA neuron entrainment was much lower on average, and was strongly frequency-dependent, declining in near-linear fashion from 6 to 200 Hz. Even at 200 Hz, however, unambiguous frequencyfollowing responses were present in the spike train activity of some SI RA neurons. These entrainment results support the "periodicity hypothesis" of Mountcastle et al. ( J Neurophysiol 32: 452-484, 1969) that the capacity to discriminate stimulus frequency over the range 5-50 Hz is attributable to the ability of SI RA pyramidal neurons to discharge action potentials in consistent temporal relationship to stimulus motion, and raise the possibility that perceptual frequency discriminative capacity at frequencies between 50 and 200 Hz might be accounted for in the same way. An increase in vibrotactile stimulus frequency within the range 6-200 Hz consistently resulted in an increase in RA afferent mean spike firing rate (M FR). SI RA neuron M FR also increased as frequency increased between 6 and 50 Hz, but declined as stimulus frequency was increased over the range 50-200 Hz. At stimulus frequencies > 100 Hz, and at positions in the RF other than the receptive field center (RF center ), SI RA neuron MFR declined sharply within 0.5-2s of stimulus onset and rebounded transiently upon stimulus termination. In contrast, when the stimulus was applied to the RF center, MFR increased with increasing frequency and tended to remain well maintained throughout the period of high-frequency stimulation. The evidence obtained in "combined" OIS imaging and extracellular microelectrode recording experiments suggests that SI RA neurons with an RF center that corresponds to the stimulated skin site occupy small foci within the much larger SI region activated by same-site cutaneous flutter stimulation, while for the RA neurons located elsewhere in the large SI region activated by a flutter stimulus, the stimulus site and RF center are different.     

Asymmetric response properties of rapidly adapting mechanoreceptive fibers in the rat glabrous skin

Previous histological and neurophysiological studies have shown that the innervation density of rapidly adapting (RA) mechanoreceptive fibers increases towards the fingertip. Since the psychophysical detection threshold depends on the contribution of several RA fibers, a high innervation density would imply lower thresholds. However, our previous human study showed that psychophysical detection thresholds for the Non-Pacinian I channel mediated by RA fibers do not improve towards the fingertip. By recording single-unit spike activity from rat RA fibers, here we tested the hypothesis that the responsiveness of RA fibers is asymmetric in the proximo-distal axis which may counterbalance the effects of innervation density. RA fibers (n?=?32) innervating the digital glabrous skin of rat hind paw were stimulated with 40-Hz sinusoidal mechanical bursts at five different stimulus locations relative to the receptive field (RF) center (two distal, one RF center, two proximal). Different contactor sizes (area: 0.39, 1.63, 2.96?mm²) were used. Rate-intensity functions were constructed based on average firing rates, and the absolute spike threshold and the entrainment threshold were obtained for each RA fiber. Thresholds for proximal stimulus locations were found to be significantly higher than those for distal stimulus locations, which suggests that the mechanical stimulus is transmitted better towards the proximal direction. The effect of contactor size was not significant. Mechanical impedance of the rat digital glabrous skin was further measured and a lumped-parameter model was proposed to interpret the relationship between the asymmetric response properties of RA fibers and the mechanical properties of the skin.     

Robust emergence of small-world structure in networks of spiking neurons

Spontaneous activity in biological neural networks shows patterns of dynamic synchronization. We propose that these patterns support the formation␣of a small-world structure—network connectivity␣optimal for distributed information processing. We␣present numerical simulations with connected Hindmarsh–Rose neurons in which, starting from random connection distributions, small-world networks evolve as a result of applying an adaptive rewiring rule. The rule connects pairs of neurons that tend fire in synchrony, and disconnects ones that fail to synchronize. Repeated application of the rule leads to small-world structures. This mechanism is robustly observed for bursting and irregular firing regimes.     

The adaptive response of Escherichia coli O157 in an environment with changing pH

AIMS: To predict and validate survival of non-acid adapted Escherichia coli O157 in an environment mimicking the human stomach. METHODS AND RESULTS: Survival was predicted mathematically from inactivation rates at various, but constant pH values. Predictions were subsequently validated experimentally in a pH-controlled fermentor. Contrary to prediction, acid-sensitive cultures of E. coli O157 survived for a long period of time and died as rapidly as acid-resistant cultures. Experimental results showed that in an environment with changing pH, acid-sensitive cultures became acid-resistant within 17 min. Cyclo fatty acids was reported to be a factor in acid resistance. As synthesis of cyclo fatty acids does not require de novo enzyme synthesis and thus requires little time to develop, we analysed the membrane fatty acid composition of E. coli O157 during adaptation. No changes in membrane fatty acid composition were observed. CONCLUSIONS: Acid adaptation of E. coli O157 can occur during passage of the human gastric acid barrier, which can take up to 4 h. SIGNIFICANCE AND IMPACT OF THE STUDY: The ability of acid-adapted bacteria to survive the human stomach is an important virulence factor. The ability of non-acid adapted E. coli O157 to adapt within a very short period of time under extreme conditions further contributes to the virulence of E. coli O157.     

Application of artificial intelligence technique for modelling elastic properties of 2D nanoscale material

A novel computational approach is proposed to investigate the shear modulus of graphene nanostructures. In this approach, the factors that affect the shear modulus of graphene structures are analysed using an integrated artificial intelligence (AI) cluster comprising molecular dynamics (MD) and gene expression programming. The MD-based-AI approach has the ability to formulate the explicit relationship of shear modulus graphene nanostructure with respect to aspect ratio, temperature, number of atomic planes and vacancy defects. In addition, the shear modulus of graphene predicted using an integrated MD-based-AI model is in good agreement with that of experimental results obtained from the literature. The sensitivity and parametric analysis were further conducted to find out specific influence and variation of each of the input system parameters on the shear modulus of two graphene structures. It was found that the number of defects has the most dominating influence on the shear modulus of graphene nanostructure.     

乌拉坦对青、老年猫视皮层神经元反应特性的影响(英文)

以前的电生理研究结果显示, 老年哺乳动物视皮层细胞的自发反应及对视觉刺激的诱发反应比青年动物的显著增加, 而对光栅刺激的方位和运动方向选择性却显著下降。然而, 这种视皮层细胞功能的老年性改变是否因青、老年猫细胞对不同麻醉水平的敏感性差异引起尚不清楚。为探讨该问题, 以常用的麻醉药——乌拉坦(Urethane)为实验对象, 通过改变其麻醉剂量分别记录青、老年猫初级视皮层细胞对不同方位和运动方向光栅刺激的调谐反应。研究结果显示, 在基础麻醉量的基础上, 累积增加 50 mg 和 100 mg 乌拉坦对青、老年猫视皮层细胞的自发反应和诱发反应以及对光栅刺激方位和运动方向的选择性不产生显著影响, 累积增加 150 mg 乌拉坦会导致青、老年猫视皮层细胞对视觉刺激的反应性下降, 但下降的幅度相似。以上研究结果表明, 不同剂量的乌拉坦对青、老年动物视皮层细胞的反应性具有相似的影响。     

Dynamics of networks of randomly connected excitatory and inhibitory spiking neurons

Recent advances in the understanding of the dynamics of populations of spiking neurones are reviewed. These studies shed light on how a population of neurones can follow arbitrary variations in input stimuli, how the dynamics of the population depends on the type of noise, and how recurrent connections influence the dynamics. The importance of inhibitory feedback for the generation of irregularity in single cell behaviour is emphasized. Examples of computation that recurrent networks with excitatory and inhibitory cells can perform are then discussed. Maintenance of a network state as an attractor of the system is discussed as a model for working memory function, in both object and spatial modalities. These models can be used to interpret and make predictions about electrophysiological data in the awake monkey.     

On the stationary state of a network of inhibitory spiking neurons

The background activity of a cortical neural network is modeled by a homogeneous integrate-and-fire network with unreliable inhibitory synapses. For the case of fast synapses, numerical and analytical calculations show that the network relaxes into a stationary state of high attention. The majority of the neurons has a membrane potential just below the threshold; as a consequence the network can react immediately – on the time scale of synaptic transmission- on external pulses. The neurons fire with a low rate and with a broad distribution of interspike intervals. Firing events of the total network are correlated over short time periods. The firing rate increases linearly with external stimuli. In the limit of infinitely large networks, the synaptic noise decreases to zero. Nevertheless, the distribution of interspike intervals remains broad. Action Editor: Misha Tsodyks     

Correlation properties of heartbeat dynamics

In this study, we investigate correlation properties of fluctuations in heart interbeat (RR) time series in a broad range of physiological and pathological conditions. Using detrended fluctuation analysis (DFA) method we determined short-term (alpha (1)) and long-term (alpha (2)) scaling exponent. In addition, we calculated standard deviation of RR intervals (SDRR) as the simplest variability measure. We found that the difference between alpha (1) and alpha (2) is related to RR interval length. At the shortest RR intervals, which correspond to extreme physiological and pathological conditions, we found the highest reduction of variability and the biggest difference between scaling exponents. In this case, DFA reveals a white noise over short scales (alpha (1 )about 0.5) and strongly correlated noise over large scales (alpha (2) about 1.5). With an increase in RR interval, accompanied by increased variability (increase in parasympathetic control), the difference between alpha (1) and alpha (2) decreases. The difference between scaling exponents disappeared in a state of efficient autonomic control. We suggest that the complexity in heart rhythm is achieved through coupling between intrinsically controlled heart rhythm and autonomic control, and that the model of stochastic resonance mechanism could be applied to this system.     

Dynamics of spiking neurons connected by both inhibitory and electrical coupling

We study the dynamics of a pair of intrinsically oscillating leaky integrate-and-fire neurons (identical and noise-free) connected by combinations of electrical and inhibitory coupling. We use the theory of weakly coupled oscillators to examine how synchronization patterns are influenced by cellular properties (intrinsic frequency and the strength of spikes) and coupling parameters (speed of synapses and coupling strengths). We find that, when inhibitory synapses are fast and the electrotonic effect of the suprathreshold portion of the spike is large, increasing the strength of weak electrical coupling promotes synchrony. Conversely, when inhibitory synapses are slow and the electrotonic effect of the suprathreshold portion of the spike is small, increasing the strength of weak electrical coupling promotes antisynchrony (see Fig. 10). Furthermore, our results indicate that, given a fixed total coupling strength, either electrical coupling alone or inhibition alone is better at enhancing neural synchrony than a combination of electrical and inhibitory coupling. We also show that these results extend to moderate coupling strengths.     

Changes in mechanical properties of bone within the mandibular condyle with age

The purpose of the study was to compare indentation modulus (IM) and hardness of condylar bone in young and adult dogs. In addition we desired to examine histologic sections for bone formation activity in the two groups. Mandibular condyles were obtained from adult (1- to 2-year-old) and young (approximately 5-m old) dogs. Two sections/condyle were obtained and one was processed for histomorphometry and the other for mechanical analyses. Indents were made on moist condylar trabecular bone to a depth of 500 nm at a loading rate of 10 nm/s using a custom-made hydration system to obtain IM and hardness. Histomorphometric analyses measured the bone volume/total volume (BV/TV%) and ratio of labeled to unlabeled bone within the condyle. Data were analyzed using a repeated-measures factorial analysis of variance and Tukey-Kramer method. Overall, the IM of the adult condyles (10.0+/-3.4 GPa, Mean+/-SD) were significantly (P<0.0001) higher than in young dogs (5.6+/-2.6 GPa). There was a greater bone mass in the young (60.2%) versus the adult condyles (42%). Also, significantly more labeled bone in the young (66.1%) condylar bone suggested higher bone forming activity than in adult condyles (27.5%). With age there is a change in mass and material properties in the trabecular bone of the mandibular condyle in dogs.     

Visual response properties of neck motor neurons in the honeybee

Recent behavioural studies have demonstrated that honeybees use visual feedback to stabilize their gaze. However, little is known about the neural circuits that perform the visual motor computations that underlie this ability. We investigated the motor neurons that innervate two neck muscles (m44 and m51), which produce stabilizing yaw movements of the head. Intracellular recordings were made from five (out of eight) identified neuron types in the first cervical nerve (IK1) of honeybees. Two motor neurons that innervate muscle 51 were found to be direction-selective, with a preference for horizontal image motion from the contralateral to the ipsilateral side of the head. Three neurons that innervate muscle 44 were tuned to detect motion in the opposite direction (from ipsilateral to contralateral). These cells were binocularly sensitive and responded optimally to frontal stimulation. By combining the directional tuning of the motor neurons in an opponent manner, the neck motor system would be able to mediate reflexive optomotor head turns in the direction of image motion, thus stabilising the retinal image. When the dorsal ocelli were covered, the spontaneous activity of neck motor neurons increased and visual responses were modified, suggesting an ocellar input in addition to that from the compound eyes.     

Passive cable properties of hippocampal CA3 pyramidal neurons

The passive electrical cable properties of CA3 pyramidal neurons from guinea pig hippocampal slices were investigated by applying current steps and recording the voltage transients from 25 CA3 neurons, using a single intracellular microelectrode and a 3-kHz time-share system. Two independent methods were used for estimating the equivalent electrotonic length of the dendrites, L, and the dendritic to somatic conductance ratio, . The first method is similar to that used by Gorman and Mirolli (1972) and gave an average L of 0.96; the average was 2.44. The second method is derived here for the first time and assumes a finite-length cable with lumped soma. It is an exact solution for L and , using the slopes and intercepts of the first two peeled exponentials. The average L was 0.94; the average was 1.51. The results, using both methods, are in close agreement. The average membrane time constant for all 25 CA3 neurons was 23.6 ms, suggesting a large (23,600 cm²) average membrane resistivity. It is concluded that CA3 neurons are electronically short.This work was supported by Grants NS 11535 and NS 15772 from the National Institute of Neurological and Communicative Disorders and Stroke, National Institutes of Health, U.S. Public Health Service.     

Computation of spiking activity for a stochastic spatial neuron model: effects of spatial distribution of input on bimodality and CV of the ISI distribution

We obtain computational results for a new extended spatial neuron model in which the neuronal electrical depolarization from resting level satisfies a cable partial differential equation and the synaptic input current is also a function of space and time, obeying a first order linear partial differential equation driven by a two-parameter random process. The model is first described explicitly with the inclusion of all biophysical parameters. Simplified equations are obtained with dimensionless space and time variables. A standard parameter set is described, based mainly on values appropriate for cortical pyramidal cells. When the noise is small and the mean voltage crosses threshold, a formula is derived for the expected time to spike. A simulation algorithm, involving one-dimensional random processes is given and used to obtain moments and distributions of the interspike interval (ISI). The parameters used are those for a near balanced state and there is great sensitivity of the firing rate around the balance point. This sensitivity may be related to genetically induced pathological brain properties (Rett's syndrome). The simulation procedure is employed to find the ISI distribution for some simple patterns of synaptic input with various relative strengths for excitation and inhibition. With excitation only, the ISI distribution is unimodal of exponential type and with a large coefficient of variation. As inhibition near the soma grows, two striking effects emerge. The ISI distribution shifts first to bimodal and then to unimodal with an approximately Gaussian shape with a concentration at large intervals. At the same time the coefficient of variation of the ISI drops dramatically to less than 1/5 of its value without inhibition.     

Simulation of networks of spiking neurons: A review of tools and strategies

We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin–Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks. Action Editor: Barry J. Richmond     

Effects of temperature on properties of flight neurons in the locust

High ambient temperatures increase the wing-beat frequency in flying locusts, Locusta migratoria. We investigated parameters of circuit and cellular properties of flight motoneurons at temperatures permissive for flight (20–40 °C). As the thoracic temperature increased motoneuronal conduction velocity increased from an average of 4.40 m/s at 25 °C to 6.73 m/s at 35 °C, and the membrane time constant decreased from 11.45 ms to 7.52 ms. These property changes may increase locust wing-beat frequency by affecting the temporal summation of inputs to flight neurons in the central circuitry. Increases in thoracic temperature from 25–35 °C also resulted in a hyperpolarization of the resting membrane potentials of flight motoneurons from an average of-41.1 mV to -47.5 mV, and a decrease of input resistances from an average of 3.45 M to 2.00 M. Temperature affected the measured input resistance both by affecting membrane properties, and by altering synaptic input. We suggest that the increase in conduction velocity Q₁₀=1.53) and the decrease of membrane time constant (Q₁₀=0.62) would more than account for the wing-beat frequency increase (Q₁₀=1.15). Hyperpolarization of the resting membrane potential (Q₁₀=1.18) and reduction in input resistance (Q₁₀=0.54) may be involved in automatic compensation of temperature effects.Abbreviations ANOVA analysis of variance - CPG central pattern generator - DL dorsal longitudinal muscles - EMG electromyographic - MN motoneuron - PSP post synaptic potential - Q₁₀ temperature coefficient - RMP resting membrane potential - S.D. standard deviation - SR stretch receptor