Computer simulation of after-inhibition in crayfish slowly adapting stretch receptor neuron

Reproducible Quantitative Stimulation Allows New Analysis of Crayfish Muscle Receptor Organ Responses

The crustacean muscle receptor organ (MRO) has provided a particularly accessible preparation for the study of sensory coding, which has been widely used in introductory laboratory courses incorporating extracellular recording from sensory nerves in living preparations. We describe three innovations to the standard laboratory exercise using the MRO: (1) a new form of suction electrode to facilitate extracellular recording; (2) a new, Arduino-driven actuator to allow reproducible and quantifiable mechanical stimulation of the MRO; and (3) a new approach to the crayfish abdomen preparation that allows linear extension of the MRO muscles. These novel approaches allow the collection of data sets comprised of sensory cell spike trains under software control as important mechanical stimulus parameters are varied systematically through software. This additional level of user control facilitates a more robust quantitative approach to the analysis of MRO sensory neuron spike trains, which is facilitated by training in data analysis using python.

The amplitude and phase responses of the firing rates of some motoneuron models

A vertebrate motoneuron receives an enormous amount of synaptic activity from descending pathways, from spinal cord interneurons and directly from mechanoreceptor afferents. The intrinsic characteristics of the motoneuron will determine how its output spike train will encode the activities of all its inputs. Therefore, the essence of the intrinsic motoneuron characteristics should be well studied and modelled if the roles of the motoneuron as a processing or encoding element are to be well understood. Mathematical models of motoneurons have been described in the literature and tested mostly under static conditions. To increase the reality of the validation of such models, the objective of the present work is to test a few selected models described in the literature using sinusoidal injected current of different frequencies. The resulting frequency responses are compared with data available in the literature from cat type F motoneurons. Discrepancies between some of the models' responses and real motoneuron data suggest that improvements are needed in the modelling of the afterhyperpolarization mechanism.

Elastic porous tube model of reactive hyperaemia

Reactive hyperaemia is the term given to the temporary increase in blood flow that follows release of an occlusion of the arterial supply. Measurement of reactive hyperaemia in the leg below the knee is useful in assessment of the vascular system, as resting flows remain unaffected even in the presence of quite severe occlusive arterial disease. An elastic porous tube representation of the vascular system is used to develop equations for the variation of the mean pressure, flow and vessel calibre in the vascular system. The tube represents the arteries and large arterioles, which respond passively to changes in pressure. Leakage through the tube walls represents flow into the small arterioles, which respond actively to the rise in pressure following release of the occlusion by constricting (the myogenic response). The capillaries are represented by rigid tubes, and the venous system is represented by a single compliant vessel. The model predicts variations in the flow, pressure and vessel calibre that are in agreement with experimental observations, and identifies that the pressure gradient is important in determining the initial transient increase in the flow following release of the occlusion. The subsequent development in the flow is governed by the small arteriolar flow, which is determined by the magnitude and duration of the myogenic response.

Integrated myogenic and metabolic control of vascular tone in skeletal muscle during autoregulation of blood flow

The hypothesis that autoregulation of blood flow in cat skeletal muscle is due to metabolic factors related to blood flow that interact with force-sensitive myogenic mechanisms is tested by means of a mathematical model. The vascular bed is assumed to consist of the reactive series-coupled proximal arterial and microvascular sections and the passive large vein section. Myogenic mechanisms are described by a slowly adapting force-receptor that determines the activation level of smooth muscle. The contractile machinery is represented by our recently developed mathematical model of smooth muscle mechanics. The metabolic control is described by the vasodilator theory whereby changes in the interstitial concentration of a dilator substance(s) alter the excitation-contraction coupling by shifting the [Ca2+]-force relationship. Experimental results indicate that the model correctly simulates vascular resistance responses to a variety of pressure stimuli, as well as autoregulation of blood flow and capillary pressure. Our results show that autoregulation of blood flow requires myogenic mechanisms which act synergistically with metabolic factors related to blood flow. It is also shown that the autoregulation of capillary pressure can be attributed to passive pressure-induced changes of postcapillary resistance, and that in autoregulation of blood flow the concentration of the mediating vasodilator metabolite(s) is a controlled variable being kept virtually constant in the range where blood flow is autoregulated.

Demodulation methods for an adaptive neural encoder model

An adaptive version of the integrate and fire-at-threshold model for the neural coding process is presented. The encoder transforms stimulus intensity information into sequences of identical membrane depolarization spikes, their times of occurrence defining a modulated point process. Several theoretical decoding schemes are then introduced and their performance analyzed. These implement simple, recursive parameter estimation algorithms and their output reproduces reliably; the encoded time-varying stimulus level.

A model for impulse frequency modulation used in neural encoding

The impulse rate at the output of a neural encoder can be interpreted as the sum of the mean impulse rate plus a noise component. From literature models are known which describe the transient phenomena of the encoder as far as the mean impulse rate is concerned. In this paper in addition the noise phenomenon is treated by a model which is in agreement with results derived from measurements. This model consists of two parts, a multiplicative and an additive estimator. The first one is similar to the automatic gain control system known from literature. This system estimates the amplification of the impulse rate due to the step input of the neural encoder. Multiplying the impulse rate with the inverse of this factor inhibits the change of the impulse rate. The second estimator calculates the step size of the impulse rate which is subtracted from the output of the encoder. Again the change of the impulse rate is inhibited. The comparison of the impulse rates simulated by the model and given by published measurements shows a good agreement for the properties of the mean impulse rate and the variance of the imposed noise.

Adaptive neural encoder model with selfinhibition and threshold control

A general model for an adaptive neural encoder relating the output firing frequency to input stimulus is presented. The model is based on an "integrate and fire at threshold" scheme and includes cumulative inhibitory feedback as well as output rate dependent threshold control.

Relevance of the single ommatidium performance in determining the oscillatory response of the Limulus retina

The response of a healthy lateral eye of Limulus to constant, uniform and sufficiently intense light stimulation, consists of a sustained oscillatory discharge, all ommatidia firing synchronously in bursts, at intervals of about 0.2s (Barlow and Fraioli, 1978). This response has been analysed by a computer simulation, where the performance of the single unit is described by encoder models of the integrate-and-fire type, already extensively investigated. The results obtained show that the occurrence and the time features of the oscillatory response depend on the neural models adopted.

Simulation of phase-dependent pattern changes to perturbations of regular firing in crayfish stretch receptor

A comparison was made of responses of a repetitively firing neuron to perturbations imposed in an ongoing steady firing pattern with those predicted by a model termed the 'active pacemaker model' and by a simpler 'integrate-and-fire' model. The active pacemaker model simulates the kinetics of processes such as active response generation and electrogenic sodium pumping which govern the membrane potential trajectory between a reset-point following an impulse and threshold for the next impulse. Responses of the crayfish stretch receptor neuron (MRO) and of both models were studied for both abrupt steps and square pulses of current, both hyperpolarizing and depolarizing, as a function of phase of the start of the stimulus in the normal interspike interval. Physiological results are consistent with a substantially weaker effect of a perturbation delivered earlier in the interspike interval as compared to the same one given later. The active pacemaker model successfully simulates several of the prominent results of the physiology (though by no means all), while the linear integrate-and-fire model is less successful.

Motor pattern production in reciprocally inhibitory neurons exhibiting postinhibitory rebound

Pairs of neurons which inhibit each other can produce regular alternating bursts of impulses if they also exhibit postinhibitory rebound (PIR). Computer studies show that stable patterns occur spontaneously in systems of pacemaker neurons with PIR, and can be triggered in systems of nonpacemakers without requiring tonic excitation. The repetition rates of these patterns are determined largely by the PIR parameters. The patterns resist perturbation by phasic synaptic inputs, but can be modulated or turned off by tonic inputs. One pair of PIR neurons can be entrained by another pair with a different repetition rate to produce more complex firing patterns.