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Biomedical subjects

T Geisel

Publications and source records attributed to T Geisel.

At least 19 recordsLinked to original sources

The scaling laws of human travel.

The dynamic spatial redistribution of individuals is a key driving force of various spatiotemporal phenomena on geographical scales. It can synchronize populations of interacting species, stabilize them, and diversify gene pools. Human travel, for example, is responsible for the geographical spread of human infectious disease. In the light of increasing international trade, intensified human mobility and the imminent threat of an influenza A epidemic, the knowledge of dynamical and statistical properties of human travel is of fundamental importance. Despite its crucial role, a quantitative assessment of these properties on geographical scales remains elusive, and the assumption that humans disperse diffusively still prevails in models. Here we report on a solid and quantitative assessment of human travelling statistics by analysing the circulation of bank notes in the United States. Using a comprehensive data set of over a million individual displacements, we find that dispersal is anomalous in two ways. First, the distribution of travelling distances decays as a power law, indicating that trajectories of bank notes are reminiscent of scale-free random walks known as Lévy flights. Second, the probability of remaining in a small, spatially confined region for a time T is dominated by algebraically long tails that attenuate the superdiffusive spread. We show that human travelling behaviour can be described mathematically on many spatiotemporal scales by a two-parameter continuous-time random walk model to a surprising accuracy, and conclude that human travel on geographical scales is an ambivalent and effectively superdiffusive process.

Diffusion↗

Action potential onset dynamics and the response speed of neuronal populations.

The result of computational operations performed at the single cell level are coded into sequences of action potentials (APs). In the cerebral cortex, due to its columnar organization, large number of neurons are involved in any individual processing task. It is therefore important to understand how the properties of coding at the level of neuronal populations are determined by the dynamics of single neuron AP generation. Here, we analyze how the AP generating mechanism determines the speed with which an ensemble of neurons can represent transient stochastic input signals. We analyze a generalization of the theta-neuron, the normal form of the dynamics of Type-I excitable membranes. Using a novel sparse matrix representation of the Fokker-Planck equation, which describes the ensemble dynamics, we calculate the transmission functions for small modulations of the mean current and noise noise amplitude. In the high-frequency limit the transmission function decays as omega(-gamma), where gamma surprisingly depends on the phase theta(s) at which APs are emitted. If at theta(s) the dynamics is insensitive to external inputs, the transmission function decays as (i) omega(-3) for the case of a modulation of a white noise input and as (ii) omega(-2) for a modulation of the mean input current in the presence of a correlated and uncorrelated noise as well as (iii) in the case of a modulated amplitude of a correlated noise input. If the insensitivity condition is lifted, the transmission function always decays as omega(-1), as in conductance based neuron models. In a physiologically plausible regime up to 1 kHz the typical response speed is, however, independent of the high-frequency limit and is set by the rapidness of the AP onset, as revealed by the full transmission function. In this regime modulations of the noise amplitude can be transmitted faithfully up to much higher frequencies than modulations in the mean input current. We finally show that the linear response approach used is valid for a large regime of stimulus amplitudes.

Action Potentials↗

Forecast and control of epidemics in a globalized world.

The rapid worldwide spread of severe acute respiratory syndrome demonstrated the potential threat an infectious disease poses in a closely interconnected and interdependent world. Here we introduce a probabilistic model that describes the worldwide spread of infectious diseases and demonstrate that a forecast of the geographical spread of epidemics is indeed possible. This model combines a stochastic local infection dynamics among individuals with stochastic transport in a worldwide network, taking into account national and international civil aviation traffic. Our simulations of the severe acute respiratory syndrome outbreak are in surprisingly good agreement with published case reports. We show that the high degree of predictability is caused by the strong heterogeneity of the network. Our model can be used to predict the worldwide spread of future infectious diseases and to identify endangered regions in advance. The performance of different control strategies is analyzed, and our simulations show that a quick and focused reaction is essential to inhibiting the global spread of epidemics.

Aerospace Medicine↗

Particle dispersion on rapidly folding random heteropolymers.

We investigate the dynamics of a particle moving randomly along a disordered heteropolymer subjected to rapid conformational changes which induce superdiffusive motion in chemical coordinates. We study the antagonistic interplay between the enhanced diffusion and the quenched disorder. The dispersion speed exhibits universal behavior independent of the folding statistics. On the other hand it is strongly affected by the structure of the disordered potential. The results may serve as a reference point for a number of translocation phenomena observed in biological cells, such as protein dynamics on DNA strands.

Biopolymers↗

Lévy flights in inhomogeneous media.

We investigate the impact of external periodic potentials on superdiffusive random walks known as Lévy flights and show that even strongly superdiffusive transport is substantially affected by the external field. Unlike ordinary random walks, Lévy flights are surprisingly sensitive to the shape of the potential while their asymptotic behavior ceases to depend on the Lévy index mu. Our analysis is based on a novel generalization of the Fokker-Planck equation suitable for systems in thermal equilibrium. Thus, the results presented are applicable to the large class of situations in which superdiffusion is caused by topological complexity, such as diffusion on folded polymers and scale-free networks.

Journal Article↗

Signatures of prelocalized states in classically chaotic systems.

We investigate the statistics of eigenfunction intensities P(/psi/(2)) in dynamical systems with classical chaotic diffusion. Our results contradict some recent theoretical considerations that challenge the applicability of field theoretical predictions, derived in a different framework for diffusive disordered samples. For two-dimensional systems, the tails of P(/psi/(2)) contradict the results of the optimal fluctuation method, but agree very well with the predictions of the nonlinear sigma model.

Journal Article↗

Superballistic spreading of wave packets.

We demonstrate for various systems that the variance of a wave packet M(t) proportional to t(nu), can show a superballistic increase with 2 < nu < or = 3, for parametrically large time intervals. A model is constructed that explains this phenomenon and its predictions are verified numerically for various disordered and quasiperiodic systems.

Journal Article↗

Taming chaos by impurities in two-dimensional oscillator arrays.

The effect of impurities in a two-dimensional lattice of coupled nonlinear chaotic oscillators and their ability to control the dynamical behavior of the system are studied. We show that a single impurity can produce synchronized spatiotemporal patterns, even though all oscillators and the impurity are chaotic when uncoupled. When a small number of impurities is arranged in a way, that the lattice is divided into two disjoint parts, synchronization is enforced even for small coupling. The synchronization is not affected as the size of the lattice increases, although the impurity concentration tends to zero.

Journal Article↗

Stochastic resonance in neuron models: endogenous stimulation revisited.

The paradigm of stochastic resonance (SR)-the idea that signal detection and transmission may benefit from noise-has met with great interest in both physics and the neurosciences. We investigate here the consequences of reducing the dynamics of a periodically driven neuron to a renewal process (stimulation with reset or endogenous stimulation). This greatly simplifies the mathematical analysis, but we show that stochastic resonance as reported earlier occurs in this model only as a consequence of the reduced dynamics.

Action Potentials↗

Statistics of resonances and of delay times in quasiperiodic Schrodinger equations

We study the distributions of the resonance widths P(gamma) and of delay times P(tau) in one-dimensional quasiperiodic tight-binding systems at critical conditions with one open channel. Both quantities are found to decay algebraically as gamma(-alpha) and tau(-gamma) on small and large scales, respectively. The exponents alpha and gamma are related to the fractal dimension D(E)(0) of the spectrum of the closed system as alpha = 1+D(E)(0) and gamma = 2-D(E)(0). Our results are verified for the Harper model at the metal-insulator transition and for Fibonacci lattices.

Journal Article↗

Bloch electrons in a magnetic field: why does chaos send electrons the hard Way?

We find that a 2D periodic potential, with different modulation amplitudes in the x and y directions, and a perpendicular magnetic field may lead to a transition to electron transport along the direction of stronger modulation and to localization in the direction of weaker modulation. In the experimentally accessible regime we relate this new quantum transport phenomenon to avoided band crossings due to classical chaos.

Journal Article↗

Theory of ocular dominance pattern formation.

We investigate a general and analytically tractable model for the activity-dependent formation of neuronal connectivity patterns. Previous models are contained as limiting cases. As an important example we analyze the formation of ocular dominance patterns in the visual cortex. A linear stability analysis reveals that the model undergoes a Turing-type instability as a function of interaction range and receptive field size. The phase transitions is of second order. After the linear instability the patterns may reorganize which we analyze in terms of a potential for the dynamics. Our analysis demonstrates that the experimentally observed dependency of ocular dominance patterns on interocular correlations of visual experience during development can emerge according to two generic scenarios: either the system is driven through the phase transition during development thereby selecting and stabilizing the first unstable mode or a primary pattern reorganizes towards larger wavelength according their lower energy. Experimentally observing the time course of ocular dominance pattern formation will decide which scenario is realized in the brain.

Algorithms↗

Markov analysis of stochastic resonance in a periodically driven integrate-and-fire neuron.

We model the dynamics of the leaky integrate-and-fire neuron under periodic stimulation as a Markov process with respect to the stimulus phase. This avoids the unrealistic assumption of a stimulus reset after each spike made in earlier papers and thus solves the long-standing reset problem. The neuron exhibits stochastic resonance, both with respect to input noise intensity and stimulus frequency. The latter resonance arises by matching the stimulus frequency to the refractory time of the neuron. The Markov approach can be generalized to other periodically driven stochastic processes containing a reset mechanism.

Animals↗

Spontaneous pinwheel annihilation during visual development.

Neurons in the visual cortex respond preferentially to edge-like stimuli of a particular orientation. It is a long-standing hypothesis that orientation selectivity arises during development through the activity-dependent refinement of cortical circuitry. Unambiguous evidence for such a process has, however, remained elusive. Here we argue that, if orientation preferences arise through activity-dependent refinement of initially unselective patterns of synaptic connections, this process should leave distinct signatures in the emerging spatial pattern of preferred orientations. Preferred orientations typically change smoothly and progressively across the cortex. This smooth progression is disrupted at the centres of so-called pinwheels, where neurons exhibiting the whole range of orientation preferences are located in close vicinity. Assuming that orientation selectivity develops through a set of rules that we do not specify, we demonstrate mathematically that the spatial density of pinwheels is rigidly constrained by basic symmetry principles. In particular, the spatial density of pinwheels, which emerge when orientation selectivity is first established, is larger than a model-independent minimal value. As a consequence, lower densities, if observed in adult animals, are predicted to develop through the motion and annihilation of pinwheel pairs.

Models, Biological↗

Breaking Rotational Symmetry in a Self&hyphenOrganizing Map Model for Orientation Map Development

We analyze the pattern formation behavior of a high&hyphendimensional self&hyphenorganizing map (SOM) model for the competitive projection of ON&hyphencenter&hyphentype and OFF&hyphencenter&hyphentype inputs to a common map layer. We mathematically show, and numerically confirm, that even isotropic stimuli can drive the development of oriented receptive fields and an orientation map in this model. This result provides an important missing link in the spectrum of pattern formation behaviors observed in SOM models. Extending the model by including further layers for binocular inputs, we also investigate the combined development of orientation and ocular dominance maps. A parameter region for combined patterns exists; corresponding maps show a preference for perpendicular intersection angles between iso&hyphenorientation lines and ocularity domain boundaries, consistent with experimental observations.

Journal Article↗