Biomedical subjects

P Lánský

Publications and source records attributed to P Lánský.

At least 19 recordsLinked to original sources

PubMed2004

From spreading depression to spatial cognition.

The Laboratory of Neurophysiology of Memory started its existence in 1954 by systematic research into spreading depression of EEG activity of laboratory rodents and by the use of this remarkable phenomenon as a functional ablation method in behavioral research. Its main contributions were in the study of memory formation and consolidation, interhemispheric transfer, motor learning, conditioned taste aversion and spatial orientation and navigation. In the last five years it concentrated on navigation of rats in multiple reference frames, on electrophysiological evidence for the role of hippocampal place cells support of behavior in such dissociated frames, on the analysis of idiothetic and allothetic forms of navigation and on the mathematical methods allowing assessment of the contribution of goal directed locomotion to place cell activity. The methods used in spatial memory research in rats were used for examination of human subjects in a laboratory equipped with a tracking system for humans in the hospital Homolka. Animal models of Alzheimer disease were studied in transgenic mice with the human gene for the beta amyloid precursor protein.

Animals↗

PubMed2004

Different types of noise in leaky integrate-and-fire model of neuronal dynamics with discrete periodical input.

Different variants of stochastic leaky integrate-and-fire model for the membrane depolarisation of neurons are investigated. The model is driven by a constant input and equidistant pulses of fixed amplitude. These two types of signal are considered under the influence of three types of noise: white noise, jitter on interpulse distance, and noise in the amplitude of pulses. The results of computational experiments demonstrate the enhancement of the signal by noise in subthreshold regime and deterioration of the signal if it is sufficiently strong to carry the information in absence of noise. Our study holds mainly to central neurons that process discrete pulses although an application in sensory system is also available.

Action Potentials↗

PubMed2003

Quantifying location-specific information in the discharge of rat hippocampal place cells.

The informational content in the location-specific discharge of rat hippocampal cells is usually quantified by an average for the entire behaviorally accessible space. In contrast to such "global" information measures, we consider here information that can be obtained from "local" spike counts at each position. The properties of these local information measures are first illustrated using simulated data with predetermined distributions of location-specific spike counts. Next, place cell recordings from rats foraging in a cylindrical arena with two cue cards on its walls are analyzed; time windows as short as 100 ms were used to accumulate spike counts in locations. We show that information at the centers of firing fields is higher for fields nearer to the cues. Neither firing rates or "global" information measures detected differences between fields near and far from the cues. Thus, analyses of the location-specific information provides a new valuable tool for studying the location-specific activity of rat hippocampal cells. Generalizations of location-specific information can be used to investigate place cell responses to other factors such as running speed or the state of the hippocampal EEG in addition to current position.

Action Potentials↗

PubMed2002

Properties of the extra-positional signal in hippocampal place cell discharge derived from the overdispersion in location-specific firing.

There is a good deal of evidence that in the rodent, an internal model of the external world is encoded by hippocampal pyramidal cells, called 'place cells'. During free exploration, the activity of place cells is higher within a small part of the space, called the firing field, and virtually silent elsewhere. We have previously shown that the spiking activity during passes through the firing field is characterized not only by the high firing rate, but also by its very high variability ('overdispersion'). This overdispersion indicates that place cells carry information in addition to position. Here we demonstrate by simulations of an integrate-and-fire neuronal model that while a rat is foraging in an open space this additional information may arise from a process that alternatingly modulates the inputs to place cells by about 10% with a mean period of about 1 s. We propose that the overdispersion reflects switches of the rats attention between different spatial reference frames of the environment. This predicts that the overdispersion will not be observed in rats that use only room-based cues for navigation. We show that while place cell firing is overdispersed in rats during foraging in an open arena, the firing is less overdispersed during the same behavior in the same environment, when the rats have been trained to use only room-based and not arena-based cues to navigate.

Action Potentials↗

PubMed2001

Receptor heterogeneity and its effect on sensitivity and coding range in olfactory sensory neurons.

Signal processing in the olfactory system is initiated by binding of odorant molecules to receptor molecules embedded in the membranes of sensory neurons. Most analyses of odorant-receptor interaction focus on one or more types of odorants binding with one type of receptors. Here, two basic models of this first step are investigated under the assumption that the population of receptors is not homogenous and is characterized by different activation/deactivation rates. Both, discrete and continuous variation of the rates are considered. The steady-state characteristics of the models are derived. In addition, time to crossing a threshold, defined as a response time, is also investigated. The achieved results are compared with those valid for models with the homogenous population of receptors and interpreted in terms of information coding. The obvious implications of the modeling study--that the heterogeneity of receptors enlarges the coding range and increases the sensitivity of the system--are quantified.

Animals↗

PubMed2001

Ligand-receptor interaction under periodic stimulation: a modeling study of concentration chemoreceptors.

The first step of chemosensory transduction consists in the association of ligand molecules with receptor proteins borne by the cell membrane. In this article, the time evolution of ligand-receptor complexes is studied in the presence of a periodically changing ligand concentration. This type of stimulation is a close approximation to some natural situations, for example in olfaction. The transient and steady-state periodic levels of the complexes, resulting from a single-step (binding) or double-step (binding and activation) reaction, are determined. When possible, analytical solutions are given, if not for the complete model, at least for its simplified version at low ligand concentration. Otherwise, solutions are found numerically and both the complete and simplified versions of the model are compared. The results obtained are discussed with respect to actual experimental data based on the moth sex-pheromone receptor. Periodic steady states are achieved very quickly and their amplitude decreases when the stimulation frequency increases. We show that the simplified description is adequate if only a fraction of activated receptors is sufficient to produce the maximum response, as is actually the case in the example treated. The role of the frequency of stimulation is investigated and it is shown to possess an optimal range between 2 and 5 Hz.

Animals↗

PubMed2001

Modeling heterogeneity of properties and random effects in drug dissolution.

PURPOSE: To investigate new models characterizing dissolution data obtained for heterogenous materials (model I) and under randomly time-varying conditions (model II). METHODS: In model I, the heterogeneity of the dissolving substance introduces variation of the fractional dissolution rate. In model II, the fractional dissolution rate evolves randomly, and thus the dissolution has the characteristics of a stochastic process. This situation is studied for the constant and time-dependent means of the dissolution rate. RESULTS: The time dynamics of the dissolved fraction is presented for model I. The standard characteristics of dissolution are derived under general conditions and for several examples. One of them is in accordance with a function found empirically (1). A duality between the time-dependency of the fractional dissolution rate and the heterogeneity of the substance is investigated. The mean and variance of the dissolved fraction are calculated for model II. A method for estimating the mean dissolution rate is proposed and illustrated using Monte-Carlo experiments. CONCLUSIONS: It follows from model I that the heterogeneity, with the same mean properties, slows down the dissolution with respect to the homogeneous case. The second approach permits predictions about the role of the stochastic fluctuations of the dissolution rate and to establish the boundaries for the dissolution profiles.

Models, Biological↗

PubMed2000

Perireceptor and receptor events in olfaction. Comparison of concentration and flux detectors: a modeling study.

Transduction in chemosensory cells begins with the association of ligand molecules to receptor proteins borne by the cell membrane. The receptor-ligand complexes formed act as signaling compounds that trigger a G-protein cascade. This receptor-ligand interaction, described here by a single-step or double-step reaction, depends on factors controlling the access of the ligand molecules to the cell membrane. Two basic mechanisms can be distinguished: concentration detectors (CD), in which the ligand can freely diffuse to the membrane, and flux detectors (FD), in which it accumulates irreversibly in a distinct perireceptor space where it is chemically deactivated. These two systems, plus their generalization, are investigated and compared. The transient and steady-state numbers of complexes are studied as a function of the external ligand concentration. The biological significance of the results is shown in a well-studied example of FD, the insect sex-pheromone olfactory receptor neuron. How the number of complexes can code for the intensity of stimulation is analyzed using the size, dynamic range and sensitivity of the steady-state responses, and the time needed to reach a predefined level of the transient responses. It is shown that the FD design affords a large increase in sensitivity (a shift of the threshold response towards low concentration) with respect to the CD design, which is paid for by a lesser ability to follow fast changes in stimulus intensity.

Kinetics↗

PubMed2000

Effect of spatial extension on noise-enhanced phase locking in a leaky integrate-and-fire model of a neuron.

Signal transmission enhanced by noise has been recently investigated in detail on the single compartment, also referred to as single point, leaky integrate-and-fire model neuron under a subthreshold stimulation. In this paper we study how this phenomenon is influenced by taking into account the spatial characteristics of the neuron. A stochastic two-point leaky integrate-and-fire model, comprising a dendritic compartment and trigger zone, under periodic stimulation is studied. A method of how to measure synchronization between the signal and the output in both, experiments and models, is proposed. This method is based on a distance between the exact periodic spiking, as expected for sufficiently strong and noiseless stimulation, and neuronal activity evoked by a subthreshold signal corrupted by noise. It is shown that qualitatively the same phenomenon, phase-locking enhanced by the noise, as found in the spatially unstructured neuron is produced by the spatially complex neuron. However, quantitatively there are significant differences. Namely, the two-point model neuron is more robust against the noise and therefore its amplitude has to be higher to enhance the signal. Further, it is found that the range of the critical levels of noise is larger for the two-point model than for the single-point one. Finally, the enhancing effect at the optimal noise is more efficient in the single-point model and thus the firing patterns at their optimal noise levels are different in both models.

Acoustic Stimulation↗

PubMed2000

Multidimensional counting processes and evoked neuronal activity.

It is shown that the joint behaviour of n counting processes can be used for description of neuronal spike generation in a system of n neurons with various synaptic links. This multidimensional process is suggested as a model of neuronal activity evoked by either a homogeneous or an inhomogeneous stimulus during a short time period. Several situations are considered, mainly the joint activity of pairs of neurons. The probability generating functions of the process are obtained for different kinds of intensity functions. The first and second moments of the process are provided as a tool for potential comparison of the model with experimental data.

Evoked Potentials↗

PubMed1999

The spatial properties of a model neuron increase its coding range.

The coding properties of one-compartment and two-compartment model neurons are compared. The membrane depolarization in both models is described as a deterministic leaky integrator. Interspike intervals are identified with the periods between reset of the depolarization after firing and consecutive crossing of a fixed firing threshold. The two-point model has an input in the dendritic compartment and an output in the trigger-zone compartment. it is shown that the sensitivity threshold for the two-point model is shifted to the larger values of the input intensity with respect to the sensitivity threshold of its single-point counterpart. Further, its coding range is substantially larger than the coding range of the single-point model.

Models, Neurological↗

PubMed1999

Does the dose-solubility ratio affect the mean dissolution time of drugs?

PURPOSE: To present a new model for describing drug dissolution. On the basis of the new model to characterize the dissolution profile by the distribution function of the random dissolution time of a drug molecule, which generalizes the classical first order model. METHODS: Instead of assuming a constant fractional dissolution rate, as in the classical model, it is considered that the fractional dissolution rate is a decreasing function of the dissolved amount controlled by the dose-solubility ratio. The differential equation derived from this assumption is solved and the distribution measures (half-dissolution time, mean dissolution time, relative dispersion of the dissolution time, dissolution time density, and fractional dissolution rate) are calculated. Finally, instead of monotonically decreasing the fractional dissolution rate, a generalization resulting in zero dissolution rate at time origin is introduced. RESULTS: The behavior of the model is divided into two regions defined by q, the ratio of the dose to the solubility level: q < 1 (complete dissolution of the dose, dissolution time) and q > 1 (saturation of the solution, saturation time). The singular case q = 1 is also treated and in this situation the mean as well as the relative dispersion of the dissolution time increase to infinity. The model was successfully fitted to data (1). CONCLUSIONS: This empirical model is descriptive without detailed physical reasoning behind its derivation. According to the model, the mean dissolution time is affected by the dose-solubility ratio. Although this prediction appears to be in accordance with preliminary application, further validation based on more suitable experimental data is required.

Capsules↗

PubMed1999

The stochastic diffusion models of nerve membrane depolarization and interspike interval generation.

The first step to make the theory of stochastic diffusion processes that arise in connection with single neuron description more understandable is reviewing the deterministic leaky-integrator model. After this step the general principles of simple stochastic models are summarized which clearly reveal that two different sources of noise, intrinsic and external, can be identified. Many possible strategies of neuronal coding exist and one of these, the rate coding, for which the stochastic modeling is relevant, is pursued further. The rate coding is reflected, in experimental as well as theoretical studies, by an input-output curve and its properties are reviewed for the most common stochastic diffusion models. The results for the simplest stochastic diffusion model, the Wiener process, are presented and from them strong limitations of this model can be understood. The most common diffusion model is the Ornstein-Uhlenbeck process, which is one substantial step closer to reality since the spontaneous changes of the membrane potential are included in the model. Both these models are characterized by an additive noise. Taking into account the state dependency of the changes caused by neuronal inputs, we derive models where the noise has a multiplicative effect on the membrane depolarization. Two of these models are compared with the Wiener and Ornstein-Uhlenbeck models. How to identify the parameters of the models, which is an unavoidable task for the models verification, is investigated. The time-variable input is taken into account in the last part of the paper. An intuitive approach is stressed throughout the review.

Action Potentials↗

PubMed1998

The Müller-Lyer illusion in interpolated figures.

The Müller-Lyer patterns formed by separate dots have been used as stimuli in an experiment on visual perception to assess the influence of the number of dots composing the figures on the magnitude of the illusion. As predicted by our model, based on the Image Function theory, an increase was noted in the magnitude of illusion when the number of dots composing the arrowheads was increased. It follows from the model that filtering of the input image plays a central role in the formation of the illusion.

Adult↗

PubMed1997

An indirect method for absorption rate estimation: flurothyl-induced seizures.

This paper develops a method to estimate a minimal amount of flurothyl necessary to induce the seizures (the seizure threshold). A simple mathematical model is proposed which permits one to determine the drug absorption rate from the amount which has been administered and from the measured latency to onset of seizure. Experimental animal (rats) were exposed to a continuous intake of flurothyl in two different situations: either being alone in the airtight chamber or sharing it in a pair. In the latter case, we assume that the two rats uniformly share the infused drug. Our calculations estimate that approximately 20 microliters of flurothyl is necessary to induce twitches, whereas 25 microliters of flurothyl is the dose required for the induction of clonic seizures. The model can be used to estimate the threshold amounts of any drug producing obvious behavioral changes irrespective of the route of administration.

Absorption↗

PubMed1997

Cycle-time and residence-time density approximations in a stochastic model for circulatory transport.

The concentration of a drug in the circulatory system is studied under two different elimination strategies. The first strategy--geometric elimination--is the classical one which assumes a constant elimination rate per cycle. The second strategy--Poisson elimination--assumes that the elimination rate changes during the process of elimination. The problem studied here is to find a relationship between the residence-time distribution and the cycle-time distribution for a given rule of elimination. While the presented model gives this relationship in terms of Laplace-Stieltjes transform., the aim here is to determine the shapes of the corresponding probability density functions. From experimental data, we expect positively skewed, gamma-like distributions for the residence time of the drug in the body. Also, as some elimination parameter in the model approaches a limit, the exponential distribution often arises. Therefore, we use Laguerre series expansions, which yield a parsimonious approximation of positively skewed probability densities that are close to a gamma distribution. The coefficients in the expansion are determined by the central moments, which can be obtained from experimental data or as a consequence of theoretical assumptions. The examples presented show that gamma-like densities arise for a diverse set of cycle-time distribution and under both elimination rules.

Humans↗

PubMed1997

Coding of odour intensity in a sensory neuron.

A deterministic biophysical model of an olfactory sensory neuron under constant stimulation is presented with the aim of describing the successive conversion steps, including receptor activation, conductance change, receptor potential and firing frequency, that are involved in the coding of odorant concentration. This model is divided in two parts. The odorant-sensitive part (OSP), consisting of one cylindrical dendrite, is connected to the odorant-insensitive part (OIP), corresponding to passive dendrite, soma and axon. Each part exerts a specific effect on the coding properties of the conversion steps, i.e. their magnitude, sensitivity and dynamic range. The maximum conductance of the OSP affects positively all coding properties whereas the input resistance of the OIP, which depends on its size and shape, affects positively the sensitivity and negatively the dynamic range. These findings are helpful for understanding the input-output properties of many types of neurons.

Action Potentials↗

PubMed1997

On the simulation of biological diffusion processes.

Many phenomena of interest in biology can be modeled using diffusion processes satisfying a stochastic differential equation. We consider first the stochastic differential equation dX = mu Xdt + sigma X, dW, where W is a standard Wiener process and representing a population growth process. This is simulated using both a strong Euler scheme involving normal pseudorandom numbers and a weak Euler scheme using Bernoulli pseudorandom numbers. Results are given for the mean of X(1) and its 95% confidence intervals for various numbers of simulations. It is found that there are no significant differences between the results obtained by these two schemes at a particular value of the time step, but the weak scheme takes less computer time than the strong scheme. We also consider the process satisfying dX = (-gamma 1X + gamma 2 (1-X))dt + square root of X(1-X)dW, representing a gene frequency under the influence of random mating and mutation. It is similarly found that the results of simulation by the two schemes are not significantly different. It is concluded that in simulations of many biological diffusion processes it is often advantageous to employ a scheme involving Bernoulli rather than Gaussian random variates not only because it involves fewer machine arithmetic operations but also because problems with large jumps that sometimes occur with extreme values of normal variates are less likely, thus enabling one to employ a larger time step with a concomitant saving in machine time.

Computer Simulation↗