Local Network Properties Research Articles

Age-dependent reduction of γ oscillations in the mouse hippocampus in vitro

Normal brain ageing is associated with a decline in hippocampal memory functions. Neuronal oscillations in the γ frequency band have been implicated in various cognitive tasks. In this study we test the effect of normal brain ageing on γ oscillations in the mouse hippocampus in vitro. γ Oscillations were evoked by either 10 μM carbachol or 100 nM kainate in ventral hippocampus slices from young (>5 month) and aged (>22 month) C57Bl/J6 mice. In slices from young mice carbachol-induced γ oscillations were more regular and more coherent than those induced by kainate. Compared with young, the power in the 20–80 Hz frequency range in area CA3 of slices from aged mice was reduced to 14% for kainate-induced oscillations and to 7% for carbachol-induced oscillations, whereas waveform, dominant frequency and coherence of the oscillation were unchanged. Local network properties were assessed by paired-pulse stimulation of Schaffer collateral/commissural fibers. The excitatory synaptic response in stratum radiatum of CA3 was reduced, in correlation with the antidromic population spike, but functional inhibition in CA3 and CA1 was unaffected. Changes in local network properties could not explain the reduced γ oscillation strength. Since oscillations driven by two different pathways are similarly affected with age, an age-dependent effect on tonic depolarizing drive of principal cells is unlikely to explain the current results. Other mechanisms, including a change with age in the use-dependent modulation of synaptic strength, should account for the impaired γ oscillations in the aged hippocampus that may contribute to age-dependent memory impairment.

Theory of Intrachain Relaxation Spectra for Polymer Networks Possessing a Short‐ or Long‐Scale Ordering. Effects of the Nematic Ordering on the Relaxation Spectrum of a Polymer Network with Included Rods

AbstractWe discuss the relaxation properties of polymer networks possessing either short‐scale ordering caused by rigidity of network strands or long‐scale liquid crystalline order. The main topics of the paper are the equilibrium and local dynamic properties of a polymer network ordered due to nematic‐like interactions of the network segments with included rod‐like particles. A simplified three chain network model is used. Lagrange multipliers in the equations of motion of hard rods are replaced by their averaged values. This approximation corresponds to modelling the rod‐like particles by elastic Gaussian springs, their mean‐square lengths independent of the ordering. Nematic‐like interactions between network segments and rods are taken into account in terms of the Maier‐Saupe mean‐field approximation. Nematic ordering of rods induces ordering of the network segments. Relaxation spectrum of the ordered network splits into two main branches for the parallel and perpendicular components of the chain segments with respect to the director. We calculate the relaxation times of a polymer network as functions of the wave number. The relaxation spectrum of an isotropic network and that of the ordered network with included rods are compared.

Theory of relaxation properties of two-dimensional polymer networks, 1. Normal modes and relaxation times

The local relaxation properties of polymer networks with a two-dimensional connectivity are considered. We use the mesh-like network model in which the average positions of junctions form the regular spatial structure consisting of square repeating units (network cells). The two-dimensional polymer network consisting of “bead and spring” Rouse chains and the simplified coarse-grained network model describing only the large-scale collective relaxation of a network are studied. For both dynamic network models the set of relaxation times and the transformation from Cartesian coordinates of network elements to normal modes are obtained. Using the normal mode transformation obtained, in Part 2 of this series the exact analytical expressions for various local dynamic characteristics of the polymer network having a two-dimensional connectivity will be calculated.

Theory of relaxation properties of two-dimensional polymer networks, 2. Local dynamic characteristics

Using normal mode transformation obtained in Part 1 of this series 1) , the exact analytical expressions for the mean-square displacements of junctions and non-junction beads. the autocorrelation functions of the end-to-end chain vectors between neighboring junctions. and those of subchain vectors of a two-dimensional regular network consisting of bead and spring Rouse chains are obtained. Contributions of intra- and interchain relaxation processes to the local dynamic characteristics considered are compared. The time behavior of dynamic quantities obtained is estimated for different scales of motions. The possibility of describing long-time relaxation of a two-dimensional network by a simplified coarse-grained network model is demonstrated. It is shown that the local relaxation properties of a two-dimensional polymer network (as well as a three-dimensional network) on scales smaller than the average distance between cross-links are very close to those of a single Rouse chain. The large-scale collective relaxation of the polymer networks having a two-dimensional connectivity differs considerably from that of the three-dimensional networks.

Theory of relaxation properties of two-dimensional polymer networks, 1. Normal modes and relaxation times

The local relaxation properties of polymer networks with a two-dimensional connectivity are considered. We use the mesh-like network model in which the average positions of junctions form the regular spatial structure consisting of square repeating units (network cells). The two-dimensional polymer network consisting of bead and spring Rouse chains and the simplified coarse-grained network model describing only the large-scale collective relaxation of a network are studied. For both dynamic network models the set of relaxation times and the transformation from Cartesian coordinates of network elements to normal modes are obtained. Using the normal mode transformation obtained, in Part 2 of this series the exact analytical expressions for various local dynamic characteristics of the polymer network having a two-dimensional connectivity will be calculated.

Compliance of actin filament networks measured by particle-tracking microrheology and diffusing wave spectroscopy

We monitor the time-dependent shear compliance of a solution of semi-flexible polymers, using diffusing wave spectroscopy (DWS) and video-enhanced single-particle-tracking (SPT) microrheology. These two techniques use the small thermally excited motion of probing microspheres to interrogate the local properties of polymer solutions. The solutions consist of networks of actin filaments which are long semi-flexible polymers. We establish a relationship between the mean square displacement (MSD) of microspheres imbedded in the solution and the time-dependent creep compliance of the solution, <Δr 2(t)>=(k B T/πa)J(t). Here, J(t) is the creep compliance, <Δr 2(t)> is the mean-square displacement, and a is the radius of the microsphere chosen to be larger than the mesh size of the polymer network. DWS allows us to measure mean square displacements with microsecond temporal resolution and Angstrom spatial resolution. At short times, the mean square displacement of a 0.96μm diameter sphere in a concentrated actin solution displays sub-diffusion. <Δr 2(t)>∝t , with a characteristic exponent =0.78±0.05, which reflects the finite rigidity of actin. At long times, the MSD reaches a plateau, with a magnitude that decreases with concentration. The creep compliance is shown to be a weak function of polymer concentration and scales as J p ∝c –1.2±0.3. This exponent is correctly described by a recent model describing the viscoelasticity of semi-flexible polymer solutions. The DWS and video-enhanced SPT measurements of the compliance plateau agree quantitatively with compliance measured independently using classical mechanical rheometry for a viscous oil and for a solution of flexible polymers. This paper extends the use of DWS and single-particle-tracking to probe the local mechanical properties of polymer networks, shows for the first time the proportionality between mean square displacement and local creep compliance, and therefore presents a new, direct way to extract the viscoelastic properties of polymer systems and complex fluids.

Semiflexible Polymer Network: A View From Inside

The dynamics of a polymer network are studied by direct view observation of the motion of a single point within a single polymer. Taking advantage of rather rigid biological microtubules as a case study, we expand the space and time scales of the system to those accessible by optical microscopy and standard video tools. Tracking is achieved by chemically attaching an optically resolved microsphere to a single point on the filament. We study the time dynamics of this point, without spatial averaging inherent in scattering methods. It is shown that the mean square displacement of the individual point is sensitive to local filament and network properties. [S0031-9007(97)05158-2] PACS numbers: 83.10.Nn An essential physical question in the study of polymer dynamics is how to relate the bulk rheological response of a network to the molecular-scale motions executed by an individual monomer. The latter are driven by random thermal collisions with the surrounding solvent molecules, and constrained at two levels: the embedding of the monomer within the polymer and the entanglement of the polymer within the network. In conventional chemical polymers the relevant length scales are on the order of 1 nm, far too small to be resolved by direct imaging techniques. Typical methods of study include light and neutron scattering, which are sensitive to local fluctuations in the density of the bulk sample. Light scattering can provide superb time resolution, while the few-angstrom wavelength of neutrons offers much improved spatial sensitivity. Nonetheless, these methods make a spatial averaging of the fluctuations taking place in a large volume of the sample. Attention is typically focused on the time domain, with use of fluctuation-dissipation arguments to relate modes of response to the thermally generated fluctuations. Recently, there have been a number of attempts to investigate local dynamics by direct imaging methods. The main trend has been to exploit biological polymers for their relative stiffness compared to simple synthetic ones, and also for their intrinsic biophysical interest. One approach has been to fluorescently label an entire polymer and watch its motion using video microscopy. The polymer is analyzed by measuring the wave vector [1] or the cosine correlation function [2]. In these methods the dynamics of a monomer is studied implicitly by measuring the dynamics of the entire polymer. Another method has been to implant a large bead in a network and investigate its restricted diffusion due to collisions with the surrounding filaments [3]. In this method, interpretation in terms of single filament dynamics must involve some a priori assumption. The approach described here is to prepare a system in which it is possible to image monomer motion directly, and to study the polymer network via the dynamics of a single monomer [4]. To this end, we expand the size and time scales of the system by exploiting biological polymers known as microtubules. These self-assembling filaments are stiff enough to maintain an average direction from end to end, yet sufficiently flexible to display thermally driven undulations. We “tag” a single monomer by attaching to it an optically resolvable bead (Fig. 1) and trace the bead’s position by video analysis. The motion of the bead displays the thermally driven motion of the microtubule itself. Using the clock provided by the video frame rate, we measure the mean square displacement (MSD) vs time interval of the bead. Classical random walk diffusion predicts that the MSD grows linearly in time, and our results lie in the deviations from this familiar situation. We interpret the data to probe the internal state of the network, e.g., to detect entanglement or quenched stress. Background for this experiment is set by considering a bead attached to a single microtubule whose dynamics are governed by thermally driven bending fluctuations. The important parameters governing the MSD at a point

Shear field mapping in actin networks by using magnetic tweezers.

An improved magnetic bead microrheometer based on phase contrast microscopy allowing high resolution measurements of local deformations within macromolecular network is applied to study local viscoelastic properties of cross-linked actin networks. By embedding nonmagnetic colloidal beads as probes into the networks, the spatial variation of the strain field within cross-linked actin networks can be mapped. Moreover, the Poisson ratio and shear modulus can be measured locally.

Continuous-time global computer vision with analog, specialized, and interacting neural networks

Traditional computer vision considers early vision as an “inverse optics” problem and tries to invert projective and radiometric equations. It postulates independent modules and uses constraint satisfaction techniques within each module to obtain the desired inverse. We outline the shortcomings of these approaches and discuss how neural networks can overcome them. We review relevant findings from neurophysiology and psychophysics and indicate how they have been incorporated into neural network models. In particular, we stress massive parallelism, nonalgorithmic analog behavior, attention, goal-directed behavior, habituation, sensitization, self-organization, and local and global processing properties of neural networks as key elements to analyze visual inputs in nonstationary environments.

Distributed virtual hosts and networks

Diverse network application requirements bring about local networks of various size, degree of complexity and architecture. The purpose of this paper is to present a network protocol layer which is used to provide a homogeneous operating environment and to ensure the availability of network resources. The network layer process probes the underlying local network to discover its properties and then adapts to changing network conditions. The principle contribution of this paper is to generalize properties of diverse local networks which can be measured. This is important when considering maintenance and service of various communication links. Three type of links are point-to-point links, multi-drop, loop or switched links and multi-access contention data buses. A prototype network is used to show a complexity improvement in the number of measurement probes required using a multi-access contention bus. Examples of measurement techniques and network adaption are presented.