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R E Poppele

Publications and source records attributed to R E Poppele.

At least 55 records · Page 3Linked to original sources
PubMed1982

On the application of systems analysis to neurophysiological problems.

In this essay we have presented some personal viewpoints on the application of Systems. Analysis to suitable neurophysiological problems and provided reasoned reviews on selected topics (receptor and nerve cell physiology, motor control, vestibular and visual systems) in which new data and ideas were brought about in the past several years by the use of Systems Analysis. Since the nature of the paper precludes the possibility of writing a summary, we simply thank those readers who have endured up to this point. As for those prudent persons who are beginning from this summary, before deciding as to the advisability of taking-up the task, we have a simple advice which runs contrary to the rule stated by the King to Alice in Wonderland (and accepted by one of us; see p. 60): begin from the topic that you like most and eventually go on, using the same criteria, till you are tired: then stop.

Animals↗
PubMed1981

Stretch-induced contraction of intrafusal muscle in cat muscle spindle.

Measurements of tension, stiffness, and sarcomere length of intrafusal muscle during ramp stretch of isolated muscle spindles have revealed a stretch-induced contraction of the bag1 fiber. This behavior can account for the very high sensitivity of primary endings to stretch as well as the enhanced sensitivity evoked by dynamic fusimotor stimulation.

Afferent Pathways↗
PubMed1980

Excitation properties of the squid axon membrane and model systems with current stimulation. Statistical evaluation and comparison.

The space-clamped squid axon membrane and two versions of the Hodgkin-Huxley model (the original, and a strongly adapting version) are subjected to a first order dynamic analysis. Stable, repetitive firing is induced by phase-locking nerve impulses to sinusoidal currents. The entrained impulses are then pulse position modulated by additional, small amplitude perturbation sinusoidal currents with respect to which the frequencies response of impulse density functions are measured. (Impulse density is defined as the number of impulses per unit time of an ensemble of membranes with each membrane subject to the same stimulus). Two categories of dynamic response are observed: one shows clear indications of a corner frequency, the other has the corner frequency obscured by dynamics associated with first order conductance perturbations in the interspike interval. The axon membrane responds with first order perturbations whereas the unmodified Hodgkin-Huxley model does not. Quantitative dynamic signatures suggest that the relaxation times of axonal recovery excitation variables are twice as long as those of the corresponding model variables. A number of other quantitative differences between axon and models, including the values of threshold stimuli are also observed.

Animals↗
PubMed1978

Small-signal analysis of response of mammalian muscle spindles with fusimotor stimulation and a comparison with large-signal responses.

1. Response dynamics of primary and secondary muscle spindle endings to small-amplitude sinusoidal stretches were found to be unaltered by tonic repetitive stimulation of fusistatic or fusidynamic fibers. 2. Overall sensitivity of these receptors is decreased by fusistatic stimulation and either unchanged, increased, or decreased by fusidynamic stimulation at rates of 75/s or greater. 3. In the case of primary endings, the results obtained with small-amplitude sinusoidal stretches are not compatible with the response of these receptors to large-amplitude ramp stretches. The difference is explained by dependence of receptor dynamics on stretch amplitude. Fusistatic stimulation tends to prevent those changes in dynamics, whereas fusidynamic stimulation tends to enhance them. 4. In the case of secondary endings, the results obtained with small- and large-amplitude stretches appear to be compatible with a linear model for this receptor (i.e., one with dynamics independent of input parameters). 5. By modulating the frequency of stimulation applied to fusimotor fibers and comparing the resulting afferent response to the receptor response to stretch dynamic characteristics of intrafusal muscle contraction can be deduced. The results suggest that the dynamics of fusiastatic and fusidynamic contraction are the same and, furthermore, that they are the same as those of extrafusal muscle. We note that the result is incompatible with measurements of the time course of twitch and tetanus development and suggest, therefore, that muscle dynamics are a function of contractile state.

Adaptation, Physiological↗
PubMed1978

[Differences of behavior of DSCT neurons in decerebrate and barbiturate anesthetized cats (author's transl)].

Responses of dorsal spinocerebellar tract (DSCT) neurons to random electrical stimulation of peripheral nerves of the hindleg in decerebrate cats were studied using cross-correlation analysis of the output spike train. The spontaneous background discharge in barbiturate's cats had longer mean interspike interval than that in decerebrate cats, but there was no difference of the coefficient of variation in the two groups. This suggests that barbiturate has no effect on raising of the electrical threshold of the axon, but prolonging effect on interspike interval. Comparison of the conduction velocity showed to be slower in barbiturate's cats, so barbiturate reduces the conduction rate of the axon. The DSCT responses to the electrical stimulation of peripheral nerve in decerebrate cats were recorded in 60%, while 85% in barbiturate's cats. The reasons for this difference are that the DSCT cells in decerebrate cats are tonically inhibited from the pontine and bulbar reticular formation and the function of brain-stem reticular formation is suppressed by the barbiturate. Type 2 response in decerebrate cats, which represents reduced excitability of the DSCT cells, had inhibition with shorter initial peak latency and duration as compared to that in barbiturate's cats. This confirms the result of Eccles et al. that barbiturate in moderate dosage increases and prolongs the presynaptic inhibition.

Action Potentials↗
PubMed1978

[Bulbar reticular control on DSCT activity in decerebrate cats (author's transl)].

Effects of bulbar reticular tetanic stimulation on the responses of dorsal spinocerebellar tract (DSCT) units were studied in the decerebrate cat. The conditioning stimulation of lateral or paramedian reticular nucleus was found to reduce polysynaptic activation of DSCT cells (type 3 response) selectively without affecting either the spontaneous background discharge or the monosynaptic activation (type 1 response) or inhibition (type 2 response) by afferent inputs from the peripheral nerves of hindleg. These results show that the descending inhibition to the polysynaptic activation of DSCT cells occurs presynaptically by reticulospinal pathways from brain-stem reticular formation.

Animals↗
PubMed1977

Repetitive firing: a quantitative study of feedback in model encoders.

Recognition of nonlinearities in the neuronal encoding of repetitive spike trains has generated a number of models to explain this behavior. Here we develop the mathematics and a set of tests for two such models: the leaky integrator and the variable-gamma model. Both of these are nearly sufficient to explain the dynamic behavior of a number of repetitively firing, sensory neurons. Model parameters can be related to possible underlying basic mechanisms. Summed and nonsummed, spike-locked negative feedback are examined in conjunction with the models. Transfer functions are formulated to predict responses to steady state, steps, and sinusoidally varying stimuli in which output data are the times of spike-train events only. An electrical analog model for the leaky integrator is tested to verify predicted responses. Curve fitting and parameter variation techniques are explored for the purpose of extracting basic model parameters from spike train data. Sinusoidal analysis of spike trains appear to be a very accurate method for determining spike-locked feedback parameters, and it is to a large extent a model independent method that may also be applied to neuronal responses.

Action Potentials↗
PubMed1977

Repetitive firing: quantitative analysis of encoder behavior of slowly adapting stretch receptor of crayfish and eccentric cell of Limulus.

Techniques developed for determining summed encoder feedback in conjunction with the leaky integrator and variable-gamma models for repetitive firing are applied to spike train data obtained from the slowly adapting crustacean stretch receptor and the eccentric cell of Limulus. Input stimuli were intracellularly applied currents. Analysis of data from cells stringently selected by reproducibility criteria gave a consistent picture for the dynamics of repetitive firing. The variable-gamma model with appropriate summed feedback was most accurate for describing encoding behavior of both cell types. The leaky integrator model, while useful for determining summed feedback parameters, was inadequate to account for underlying mechanisms of encoder activity. For the stretch receptor, two summed feedback processes were detected: one had a short time constant; the other, a long one. Appropriate tests indicated that the short time constant effect was from an electrogenic sodium pump, and the same is presumed for the long time constant summed feedback. Both feedbacks show seasonal and/or species variations. Short hyperpolarizing pulses inhibited the feedback from the long time constant process. The eccentric cell also showed two summed feedback processes: one is due to self inhibition, the other is postulated to be a short time constant electrogenic sodium pump similar to that described in the stretch receptor.

Action Potentials↗
PubMed1977

Correlation analysis of stimulus-evoked changes in excitability of spontaneously firing neurons.

1. Theoretical expressions for the cross-correlation function are described which relate the output spike train of a neuron to an input spike train. The cross-correlation function is related to a convolution integral of two functions: 1) a waiting-time density, which describes the probability of observing the next succeeding output spike given an arbitrary input; and 2) a conditional output autocorrelation function, which contains information related to the statistical properties of the output spike train itself, and to the carry-over of the effects of an input to subsequent intervals. 2. The primary synaptic effect appears in the cross-correlation function as a distorted version of the derivative of the PSP. Depending on the duration of the evoked excitability change, as compared to the mean output interspike interval, periodicities due to the spontaneous activity of the cell appear to a greater or lesser extent in the cross-correlation. 3. To estimate underlying excitability changes using correlation techniques, one must estimate both the cross- and the conditional output autocorrelation functions. In cases when the excitability changes are short and do not carry forward to subsequent intervals, the more readily estimated unconditional output autocorrelation can be used in place of the conditional correlation.

Animals↗
PubMed1977

A determination of excitability changes in dorsal spinocerebellar tract neurons from spike-train analysis.

1. Responses of DSCT neurons to random electrical stimulation of peripheral nerves of the hindleg at group I intensity were studied using cross-correlation analysis of the output spike train with the stimulus. Three types of response were found: type 1 was due to monosynaptic activation of DSCT cells, type 2 resulted from inhibition of those cells, and type 3 was due to a long-latency excitation that was probably polysynaptic. 2. Most of the units studied responded to stimulation of both proximal and distal flexor and extensor nerves. The extensive convergence of afferent input on DSCT cells is much greater than has been observed previously, with type 2 and type 3 responses totaling 80% of the observed responses. We attribute this to the sensitivity of the analysis in detecting small changes in postsynaptic excitability. 3. The results of the study, particularly the derivation of postsynaptic excitability changes, generally confirm those of earlier work employing intracellular recording. 4. By varying stimulus rate and stimulus intensity in the group 1 range and simulating the resulting correlations, we conclude that excitability changes in DSCT cells are the net result of complex interactions involving excitation and inhibition. A summary of these findings is presented as a model for the minimum circuitry necessary to account for the observed behavior.

Afferent Pathways↗
PubMed1977

[A study of excitability changes in DSCT neurons of the cat (author's transl)].

Excitability changes in the dorsal spinocerebellar tract (DSCT) neurons of the cat were extracellularly studied with correlation analysis. Most of the interval histograms were classifed as normal distribution, and occasionally bimodal distributions were observed, which resulted from an occasional "double spiking" in the spontaneous background discharge (BD). The conduction velocity was measured in 72 DSCT fibers. The histogram showed a peak at 40-50 M/S. The majority of the units had BD with coefficient of variation less than 0.2, which suggest BD with regular firing. Based on cross-correlelograms, DSCT responses to electrical stimulation of the muscle nerves of the hind leg were classified into at least three types. Type 1 response, constituted approximately one-fifth of the total, is monosynaptic activation. Type 2 response, observed most frequently (47%), is inhibition of DSCT cells with a short latency. Type 3 responses, observed nearly as often as type 2 (34%), is a long latency excitation, undoubtedly polysynaptic. Changes in stimulation intensity showed complex changes in the pattern of response. Type 1 and 2 responses were unaffected by increasing stimulus rate. Peak correlations in type 3 response were reduced by increase in stimulus rate. There were no data demonstrating feedback circuitry associated with collaterals of DSCT axons. This suggest that axon collaterals have no direct effect on the activity of Dsct cells.

Afferent Pathways↗