Causal measures of structure and plasticity in simulated and living neural networks

A major goal of neuroscience is to understand the relationship between neural structures and their function. Recording of neural activity with arrays of electrodes is a primary tool employed toward this goal. However, the relationships among the neural activity recorded by these arrays are often highly complex making it problematic to accurately quantify a network's structural information and then relate that structure to its function. Current statistical methods including cross correlation and coherence have achieved only modest success in characterizing the structural connectivity. Over the last decade an alternative technique known as Granger causality is emerging within neuroscience. This technique, borrowed from the field of economics, provides a strong mathematical foundation based on linear auto-regression to detect and quantify “causal” relationships among different time series. This paper presents a combination of three Granger based analytical methods that can quickly provide a relatively complete representation of the causal structure within a neural network. These are a simple pairwise Granger causality metric, a conditional metric, and a little known computationally inexpensive subtractive conditional method. Each causal metric is first described and evaluated in a series of biologically plausible neural simulations. We then demonstrate how Granger causality can detect and quantify changes in the strength of those relationships during plasticity using 60 channel spike train data from an in vitro cortical network measured on a microelectrode array. We show that these metrics can not only detect the presence of causal relationships, they also provide crucial information about the strength and direction of that relationship, particularly when that relationship maybe changing during plasticity. Although we focus on the analysis of multichannel spike train data the metrics we describe are applicable to any stationary time series in which causal relationships among multiple measures is desired. These techniques can be especially useful when the interactions among those measures are highly complex, difficult to untangle, and maybe changing over time.

Differentiation of mouse nuclear transfer embryonic stem cells into functional pancreatic beta cells

AIMS/HYPOTHESIS

Therapeutic cloning has been reported to have potential in the treatment of several degenerative diseases. However, it has yet to be determined whether mouse nuclear transfer-embryonic stem cells (NT-ESCs) can be differentiated into pancreatic beta cells and used to reverse diabetes in an animal model.

METHODS

We first used the somatic nuclear transfer technique to generate mouse NT-ESCs and then developed a chemically defined stepwise protocol to direct the NT-ESCs into functional pancreatic beta cells. We examined the gene expression pattern of the differentiated NT-ESCs and transplanted the NT-ESC-derived insulin-producing cells into recipient diabetic mice.

RESULTS

Four mouse NT-ESC lines were first established using an improved nuclear transfer technique and insulin-producing cells were efficiently generated from NT-ESCs by mimicking pancreatic in vivo development. Most of the insulin-producing cells that we generated co-produced pancreatic and duodenal homeobox 1, but not glucagon at the final stage of this differentiation method, which differed from the insulin and glucagon co-production reported by other groups. The differentiated NT-ESCs were able to release insulin in response to glucose stimuli and normalise the blood glucose level of diabetic mice for at least 2 months.

CONCLUSIONS/INTERPRETATION

These results demonstrate the potential of therapeutic cloning for cell therapy of type 1 diabetes in a mouse model.

Response preparation and inhibition: the role of the cortical sensorimotor beta rhythm

Paradigms requiring either a GO or a NO-GO response are often used to study the neural mechanisms of response inhibition. Here this issue is examined from the perspective of event-related beta (14-30 Hz) oscillatory activity. Two macaque monkeys performed a task that began with a self-initiated lever depression and maintenance (sustained motor output) and required a visual pattern discrimination followed by either a lever release (GO) or continued lever-holding (NO-GO) response. Analyzing simultaneous local field potentials (LFPs) from primary somatosensory, frontal motor, and posterior parietal cortices, we report two results. First, beta oscillation desynchronized shortly after stimulus presentation, the onset of which was approximately the same for both the GO and NO-GO conditions ( approximately 110 ms). Since it is well known that beta desynchronization is a reliable indicator of movement preparation, this result suggests that early motor preparation took place in both conditions. Second, following the GO/NO-GO decision ( approximately 190 ms), beta activity rebounded significantly ( approximately 300 ms) only in the NO-GO condition. Coherence and Granger causality measures revealed that the dynamical organization of the rebounded beta network was similar to that existing during the sustained motor output prior to stimulus onset. This finding suggests that response inhibition led to the restoration of the sensorimotor network to its prestimulus state.

BSMART: a Matlab/C toolbox for analysis of multichannel neural time series

We have developed a Matlab/C toolbox, Brain-SMART (System for Multivariate AutoRegressive Time series, or BSMART), for spectral analysis of continuous neural time series data recorded simultaneously from multiple sensors. Available functions include time series data importing/exporting, preprocessing (normalization and trend removal), AutoRegressive (AR) modeling (multivariate/bivariate model estimation and validation), spectral quantity estimation (auto power, coherence and Granger causality spectra), network analysis (including coherence and causality networks) and visualization (including data, power, coherence and causality views). The tools for investigating causal network structures in respect of frequency bands are unique functions provided by this toolbox. All functionality has been integrated into a simple and user-friendly graphical user interface (GUI) environment designed for easy accessibility. Although we have tested the toolbox only on Windows and Linux operating systems, BSMART itself is system independent. This toolbox is freely available (http://www.brain-smart.org) under the GNU public license for open source development.

Uncovering interactions in the frequency domain

Oscillatory activity plays a critical role in regulating biological processes at levels ranging from subcellular, cellular, and network to the whole organism, and often involves a large number of interacting elements. We shed light on this issue by introducing a novel approach called partial Granger causality to reliably reveal interaction patterns in multivariate data with exogenous inputs and latent variables in the frequency domain. The method is extensively tested with toy models, and successfully applied to experimental datasets, including (1) gene microarray data of HeLa cell cycle; (2) in vivo multi-electrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of a sheep; and (3) in vivo LFPs recorded from distributed sites in the right hemisphere of a macaque monkey.

Gene expression in lung and basal forebrain during influenza infection in mice

Inbred mice develop strain-dependent changes in sleep during the first few days after inoculation with influenza virus. To identify genes with the potential to differentially modulate sleep under this condition, we performed complementary DNA microarray analysis of both lung and basal forebrain (BF) of infected (I) and uninfected BALB/cByJ (C) and C57BL/6J (B6) mice. This analysis showed significant variation in the expression pattern of 667 and 1217 of the surveyed genes in BF and lung, respectively (P < 0.01). Applying the additional criterion of an effect size >or=2, 495 genes differed in expression in lung compared with 204 in BF. In BF, more genes were differentially expressed as a function of mouse strain, whereas in lung, more genes were differentially expressed as a function of health status. Significant alterations in expression after infection were more numerous and robust in BALB/cByJ vs. C57BL/6J mice. Some genes showed significant variation in both tissues as a function of strain or condition, but the changes in general were not parallel. Genes that showed significant and robust variation as a function of strain, health status or tissue included those related to immune function, metabolism, signal transduction, cell cycle regulation, apoptosis and other miscellaneous categories. Different patterns of gene expression in BF of uninfected mice suggest the possibility of fundamental mechanistic differences in pathways that modulate vigilance in these strains, whereas differences in expression of lung of infected mice suggests different peripherally generated sleep-modulatory stimuli in the two strains.

Analyzing information flow in brain networks with nonparametric Granger causality

Multielectrode neurophysiological recording and high-resolution neuroimaging generate multivariate data that are the basis for understanding the patterns of neural interactions. How to extract directions of information flow in brain networks from these data remains a key challenge. Research over the last few years has identified Granger causality as a statistically principled technique to furnish this capability. The estimation of Granger causality currently requires autoregressive modeling of neural data. Here, we propose a nonparametric approach based on widely used Fourier and wavelet transforms to estimate both pairwise and conditional measures of Granger causality, eliminating the need of explicit autoregressive data modeling. We demonstrate the effectiveness of this approach by applying it to synthetic data generated by network models with known connectivity and to local field potentials recorded from monkeys performing a sensorimotor task.

Estimating Granger causality from fourier and wavelet transforms of time series data

Experiments in many fields of science and engineering yield data in the form of time series. The Fourier and wavelet transform-based nonparametric methods are used widely to study the spectral characteristics of these time series data. Here, we extend the framework of nonparametric spectral methods to include the estimation of Granger causality spectra for assessing directional influences. We illustrate the utility of the proposed methods using synthetic data from network models consisting of interacting dynamical systems.

Stilbene C-glucosides from Cissus repens

Four new stilbene C-glucosides, namely trans-3-O-methyl-resveratrol-2-C-beta-glucoside (1), cis-3-O-methyl-resveratrol-2-C-beta-glucoside (2), trans-3-O-methyl-resveratrol-2-(2-p-coumaric)-C-beta-glucoside (cissuside A) (3), and trans-3-O-methyl-resveratrol-2-(3-p-coumaric)-C-beta-glucoside (cissuside B) (4), were isolated from the aerial parts of Cissus repens, along with known trans-resveratrol (5), trans-resveratrol-2-C-beta-glucoside (6) and cis-resveratrol-2-C-beta-glucoside (7). Their structures were established by spectroscopic methods. Stilbene C-glucosides were found in the genus Cissus for the first time.

Mitigating the effects of measurement noise on Granger causality

Computing Granger causal relations among bivariate experimentally observed time series has received increasing attention over the past few years. Such causal relations, if correctly estimated, can yield significant insights into the dynamical organization of the system being investigated. Since experimental measurements are inevitably contaminated by noise, it is thus important to understand the effects of such noise on Granger causality estimation. The first goal of this paper is to provide an analytical and numerical analysis of this problem. Specifically, we show that, due to noise contamination, (1) spurious causality between two measured variables can arise and (2) true causality can be suppressed. The second goal of the paper is to provide a denoising strategy to mitigate this problem. Specifically, we propose a denoising algorithm based on the combined use of the Kalman filter theory and the expectation-maximization algorithm. Numerical examples are used to demonstrate the effectiveness of the denoising approach.

Capillary Number Correlations for Gas-Liquid Systems

Abstract

Conventional capillary number theory predicts that residual oil will not be mobilized until a critical capillary number (2E - 5) is exceeded. This theory was tested to determine residual oil saturation mobilization after forced water imbibition. In the literature, high residual oil saturation was established from waterflooding at a certain pressure. Then gradually increasing pressure was applied for water injection until residual oil production was observed. It was confirmed that this critical capillary number is applicable when the initial residual oil saturation was estimated from spontaneous water imbibition tests. The same types of experiments were repeated for gas-liquid systems by creating the initial residual gas saturation through spontaneous oil or water imbibition tests on the same samples. The procedures, which included spontaneous imbibition tests followed by forced imbibition tests, were monitored by an on-line NMR system. Analysis of the experimental results produced an estimate of the critical capillary number for mobilizing residual gas from water imbibition or oil imbibition tests. In this research, we broadened the term of "imbibition" for both water and oil terms since, compared to gas, both water and oil are in the wetting phase. It was found that the critical capillary number for a gas-liquid system is very different from that of an oil-water system in the same type of rock.

Berea sandstone plugs were used in all the experiments. The reason for using Berea sandstone plugs is due to their relatively homogeneous pore structure. Additional Western Canadian sandstone plugs were used for testing gas-water systems to confirm the results obtained from the Berea sandstone plugs. Understanding the different mechanisms to produce discontinuous residual oil or residual gas is important for enhanced oil and gas recovery operations. Hopefully, this research can provide new insights into recovering additional gas from gas reservoirs with active aquifers.

Introduction

Increasing the capillary number has long been investigated as a strategy for improving oil recovery. Many methodologies around increasing the capillary number have been either tested in the laboratory or applied in the field. Capillary number is defined as the ratio of viscous forces to capillary forces. Evaluation of the capillary number can be used to describe the relative importance of viscous forces to capillary forces during immiscible displacements. There are various forms of the capillary number. The most common versions of capillary number are those by Saffman and Taylor(1):

Equation (1) (Available in full paper)

and Melrose and Brandner(2):

Equation (2) (Available in full paper)

When non-wetting phase oil is trapped in porous media, the pressure gradient required to move it through a capillary tube is much higher than what would be predicted by the pipe flow equation, due to the pressure discontinuity at the wetting/non-wetting interface. Because of the contact angle hysteresis, this discontinuity is not of the same magnitude on both sides of the discontinuous non-wetting phase. For example, in a water-wet medium, an oil droplet represents the discontinuous non-wetting phase. As the oil droplet is pushed through a pore throat, its downstream end gets squeezed into a much narrower segment making its radius of curvature much smaller than the upstream part.

Cortical functional network organization from autoregressive modeling of local field potential oscillations

A framework is presented for quantifying functional network organization in the brain by spectral analysis based on autoregressive modeling. Local field potentials (LFPs), simultaneously recorded from distributed sites in the cerebral cortex of monkeys, are treated as signals generated by local neuronal assemblies. During the delay period of a visual pattern discrimination task, oscillatory assembly activity is manifested in the LFPs in the beta-frequency range (14-30 Hz). Coherence analysis has shown that these oscillations are phase synchronized in functional networks in the sensorimotor cortex in relation to maintenance of contralateral hand position, and in the visual cortex in relation to anticipation of the visual stimulus. Granger causality analysis has revealed information flow in the sensorimotor network that is consistent with a peripheral sensorimotor feedback loop, and in the visual network that is consistent with top-down anticipatory modulation of assemblies in the primary visual cortex.

Trial-by-trial estimation of amplitude and latency variability in neuronal spike trains

The rate function underlying single-trial spike trains can vary from trial to trial. We propose to estimate the amplitude and latency variability in single-trial neuronal spike trains on a trial-by-trial basis. The firing rate over a trial is modeled by a family of rate profiles with trial-invariant waveform and trial-dependent amplitude scaling factors and latency shifts. Using a Bayesian inference framework we derive an iterative fixed-point algorithm from which the single-trial amplitude scaling factors and latency shifts are estimated. We test the performance of the algorithm on simulated data and then apply it to actual neuronal recordings from the sensorimotor cortex of the monkey.

Optimisation and validation of a medium-throughput electrophysiology-based hERG assay using IonWorks™ HT

INTRODUCTION

Regulatory and competitive pressure to reduce the QT interval prolongation risk of potential new drugs has led to focus on methods to test for inhibition of the human ether-a-go-go-related gene (hERG)-encoded K+ channel, the primary molecular target underlying this safety issue. Here we describe the validation of a method that combines medium-throughput with direct assessment of channel function.

METHODS

The electrophysiological and pharmacological properties of hERG were compared using two methods: conventional, low-throughput electrophysiology and planar-array-based, medium-throughput electrophysiology (IonWorks HT). A pharmacological comparison was also made between IonWorks HT and an indirect assay (Rb+ efflux).

RESULTS

Basic electrophysiological properties of hERG were similar whether recorded conventionally (HEK cells) or using IonWorks HT (CHO cells): for example, tail current V1/2 -12.1+/-5.0 mV (32) for conventional and -9.5+/-6.0 mV (46) for IonWorks HT (mean+/-S.D. (n)). A key finding was that as the number of cells per well was increased in IonWorks HT, the potency reported for a given compound decreased. Using the lowest possible cell concentration (250,000 cells/ml) and 89 compounds spanning a broad potency range, the pIC50 values from IonWorks HT (CHO-hERG) were found to correlate well with those obtained using conventional methodology (HEK-hERG)(r=0.90; p<0.001). Further validation using CHO-hERG cells with both methods confirmed the correlation (r=0.94; p<0.001). In contrast, a comparison of IonWorks HT and Rb+ efflux data with 649 compounds using CHO-hERG cells showed that the indirect assay consistently reported compounds as being, on average, 6-fold less potent, though the differences varied depending on chemical series.

DISCUSSION

The main finding of this work is that providing a relatively low cell concentration is used in IonWorks HT, the potency information generated correlates well with that determined using conventional electrophysiology. The effect on potency of increasing cell concentration may relate to a reduced free concentration of test compound owing to partitioning into cell membranes. In summary, the IonWorks HT hERG assay can generate pIC50 values based on a direct assessment of channel function in a timeframe short enough to influence chemical design.

Stochastic modeling of neurobiological time series: power, coherence, Granger causality, and separation of evoked responses from ongoing activity

In this article we consider the stochastic modeling of neurobiological time series from cognitive experiments. Our starting point is the variable-signal-plus-ongoing-activity model. From this model a differentially variable component analysis strategy is developed from a Bayesian perspective to estimate event-related signals on a single trial basis. After subtracting out the event-related signal from recorded single trial time series, the residual ongoing activity is treated as a piecewise stationary stochastic process and analyzed by an adaptive multivariate autoregressive modeling strategy which yields power, coherence, and Granger causality spectra. Results from applying these methods to local field potential recordings from monkeys performing cognitive tasks are presented.

Differentially Variable Component Analysis: Identifying Multiple Evoked Components Using Trial-to-Trial Variability

Electric potentials and magnetic fields generated by ensembles of synchronously active neurons, either spontaneously or in response to external stimuli, provide information essential to understanding the processes underlying cognitive and sensorimotor activity. Interpreting recordings of these potentials and fields is difficult because detectors record signals simultaneously generated by various regions throughout the brain. We introduce a novel approach to this problem, the differentially variable component analysis (dVCA) algorithm, which relies on trial-to-trial variability in response amplitude and latency to identify multiple components. Using simulations we demonstrate the importance of response variability to component identification, the robustness of dVCA to noise, and its ability to characterize single-trial data. We then compare the source-separation capabilities of dVCA with those of principal component analysis and independent component analysis. Finally, we apply dVCA to neural ensemble activity recorded from an awake, behaving macaque—demonstrating that dVCA is an important tool for identifying and characterizing multiple components in the single trial.

Synchronization in networks with random interactions: theory and applications

Synchronization is an emergent property in networks of interacting dynamical elements. Here we review some recent results on synchronization in randomly coupled networks. Asymptotical behavior of random matrices is summarized and its impact on the synchronization of network dynamics is presented. Robert May's results on the stability of equilibrium points in linear dynamics are first extended to systems with time delayed coupling and then nonlinear systems where the synchronized dynamics can be periodic or chaotic. Finally, applications of our results to neuroscience, in particular, networks of Hodgkin-Huxley neurons, are included.

Age-related three-dimensional microarchitectural adaptations of subchondral bone tissues in guinea pig primary osteoarthrosis

We explored potential mechanisms of the microarchitectural adaptations of subchondral bone tissues in a guinea pig primary osteoarthrosis (OA) model. We harvested proximal tibiae of male Dunkin-Hartley (Charles River strain) guinea pigs at 3, 6, 9, 12, and 24 months of age (10 in each group). These proximal tibiae were scanned by micro-computed tomography to quantify the three-dimensional microarchitecture of the subchondral plate, cancellous bone, and cortical bone. Subsequently, the bones were compression-tested to determine their mechanical properties. Furthermore, bone collagen, bone mineral, and bone density were determined. Mankin's score corresponded to OA grading from absent or minimal cartilage degeneration in 3-month-old to severe degeneration in 24-month-old guinea pigs. In young guinea pigs, the volume fraction and thickness of the subchondral plate markedly increased from 3 to 6 months, whereas the volume fraction of the subchondral cancellous bone displayed an initial decline followed by an increase. With age, the trabeculae increased in thickness, changed from rod-like to plate-like, and became more axially oriented. An increasing ratio of bone collagen to mineral in subchondral bone indicated undermineralized bone tissues. In subchondral cancellous bone, Young's modulus was maximal at 6 months of age, whereas ultimate stress and failure energy showed a gradual increase with age. The findings show pronounced alterations of the microarchitecture and bone matrix composition of the subchondral bone. These alterations did not appear to follow the same pattern as in normal aging and may have different influences on the resulting mechanical properties.

Large-Scale Visuomotor Integration in the Cerebral Cortex

Efficient visuomotor behavior depends on integrated processing by the visual and motor systems of the cerebral cortex. Yet, many previous cortical neurophysiology studies have examined the visual and motor modalities in isolation, largely ignoring questions of large-scale cross-modal integration. To address this issue, we analyzed event-related local field potentials simultaneously recorded from multiple visual, motor, and executive cortical sites in monkeys performing a visuomotor pattern discrimination task. The timing and cortical location of four aspects of event-related activities were examined: stimulus-evoked activation onset, stimulus-specific processing, stimulus category-specific processing, and response-specific processing. Activations appeared earliest in striate cortex and rapidly thereafter in other visual areas. Stimulus-specific processing began early in most visual cortical areas, some at activation onset. Early onset latencies were also observed in motor, premotor, and prefrontal areas, some as early as in striate cortex, but these early-activating frontal sites did not show early stimulus-specific processing. Response-specific processing began around 150 ms poststimulus in widespread cortical areas, suggesting that perceptual decision formation and response selection arose through concurrent processes of visual, motor, and executive areas. The occurrence of stimulus-specific and stimulus category-specific differences after the onset of response-specific processing suggests that sensory and motor stages of visuomotor processing overlapped in time.

Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data

It is often useful in multivariate time series analysis to determine statistical causal relations between different time series. Granger causality is a fundamental measure for this purpose. Yet the traditional pairwise approach to Granger causality analysis may not clearly distinguish between direct causal influences from one time series to another and indirect ones acting through a third time series. In order to differentiate direct from indirect Granger causality, a conditional Granger causality measure in the frequency domain is derived based on a partition matrix technique. Simulations and an application to neural field potential time series are demonstrated to validate the method.

Recombinant human vascular endothelial growth factor enhances bone healing in an experimental nonunion model

The re-establishment of vascularity is an early event in fracture healing; upregulation of angiogenesis may therefore promote the formation of bone. We have investigated the capacity of vascular endothelial growth factor (VEGF) to stimulate the formation of bone in an experimental atrophic nonunion model.

Three groups of eight rabbits underwent a standard nonunion operation. This was followed by interfragmentary deposition of 100 μg VEGF, carrier alone or autograft.

After seven weeks, torsional failure tests and callus size confirmed that VEGF-treated osteotomies had united whereas the carrier-treated osteotomies failed to unite. The biomechanical properties of the groups treated with VEGF and autograft were identical. There was no difference in bone blood flow.

We considered that VEGF stimulated the formation of competent bone in an environment deprived of its normal vascularisation and osteoprogenitor cell supply. It could be used to enhance the healing of fractures predisposed to nonunion.

Stability of synchronous oscillations in a system of Hodgkin-Huxley neurons with delayed diffusive and pulsed coupling

We study the synchronization dynamics for a system of two Hodgkin-Huxley (HH) neurons coupled diffusively or through pulselike interactions. By calculating the maximum transverse Lyapunov exponent, we found that, with diffusive coupling, there are three regions in the parameter space, corresponding to qualitatively distinct behaviors of the coupled dynamics. In particular, the two neurons can synchronize in two regions and desynchronize in the third. When excitatory and inhibitory pulse coupling is considered, we found that synchronized dynamics becomes more difficult to achieve in the sense that the parameter regions where the synchronous state is stable are smaller. Numerical simulations of the coupled system are presented to validate these results. The stability of a network of coupled HH neurons is then analyzed and the stability regions in the parameter space are exactly obtained.

Dosimetric evaluation of MRI-based treatment planning for prostate cancer

The purpose of this study is to evaluate the dosimetric accuracy of MRI-based treatment planning for prostate cancer using a commercial radiotherapy treatment planning system. Three-dimensional conformal plans for 15 prostate patients were generated using the AcQPlan system. For each patient, dose distributions were calculated using patient CT data with and without heterogeneity correction, and using patient MRI data without heterogeneity correction. MR images were post-processed using the gradient distortion correction (GDC) software. The distortion corrected MR images were fused to the corresponding CT for each patient for target and structure delineation. The femoral heads were delineated based on CT. Other anatomic structures relevant to the treatment (i.e., prostate, seminal vesicles, lymph notes, rectum and bladder) were delineated based on MRI. The external contours were drawn separately on CT and MRI. The same internal contours were used in the dose calculation using CT- and MRI-based geometries by directly transferring them between MRI and CT as needed. Treatment plans were evaluated based on maximum dose, isodose distributions and dose-volume histograms. The results confirm previous investigations that there is no clinically significant dose difference between CT-based prostate plans with and without heterogeneity correction. The difference in the target dose between CT- and MRI-based plans using homogeneous geometry was within 2.5%. Our results suggest that MRI-based treatment planning is suitable for radiotherapy of prostate cancer.

Further development of Axisymmetric Drop Shape Analysis-Captive Bubble for pulmonary surfactant related studies

The methodology combining Axisymmetric Drop Shape Analysis (ADSA) with a captive bubble (ADSA-CB) facilitates pulmonary surfactant related studies. The accuracy of ADSA-CB is crucially dependent on the quality of the bubble profile extracted from the raw image. In a previous paper, an image analysis scheme featuring a Canny edge detector and a Axisymmetric Liquid Fluid Interfaces-Smoothing (ALFI-S) algorithm was developed to process captive bubble images under a variety of conditions, including images with extensive noise and/or lack of contrast. A new version of ADSA-CB based on that image analysis scheme is developed and applied to pulmonary surfactant and pulmonary surfactant-polymer systems. The new version is found to be highly noise-resistant and well self-adjusting.

Measurement of the exclusive 3He(e,e'p) reaction below the quasielastic peak

New, high-precision measurements of the 3He(e,e(')p) reaction using the A1 Collaboration spectrometers at the Mainz microtron MAMI are presented. These were performed in antiparallel kinematics at energy transfers below the quasielastic peak, and at a central momentum transfer of 685 MeV/c. Cross sections and distorted momentum distributions were extracted and compared to theoretical predictions and existing data. The longitudinal and transverse behavior of the cross section was also studied. Sizable differences in the cross-section behavior from theoretical predictions based on the plane wave impulse approximation were observed in both the two- and three-body breakup channels. Full Faddeev-type calculations account for some of the observed excess cross-section, but significant differences remain.

Will a large complex system with time delays be stable?

In 1972 May showed that for a large linear system with random coupling the system size and the average coupling strength must together satisfy a simple inequality to ensure the stability of the equilibrium point. Here we extend the analysis to delay coupled systems. Our calculations establish that the same inequality obtained by May constrains the stability for systems randomly coupled through discrete and distributed delays.

Beta oscillations in a large-scale sensorimotor cortical network: directional influences revealed by Granger causality

Previous studies have shown that synchronized beta frequency (14-30 Hz) oscillations in the primary motor cortex are involved in maintaining steady contractions of contralateral arm and hand muscles. However, little is known about the role of postcentral cortical areas in motor maintenance and their patterns of interaction with motor cortex. We investigated the functional relations of beta-synchronized neuronal assemblies in pre- and postcentral areas of two monkeys as they pressed a hand lever during the wait period of a visual discrimination task. By using power and coherence spectral analysis, we identified a beta-synchronized large-scale network linking pre- and postcentral areas. We then used Granger causality spectra to measure directional influences among recording sites. In both monkeys, strong Granger causal influences were observed from primary somatosensory cortex to both motor cortex and inferior posterior parietal cortex, with the latter area also exerting Granger causal influences on motor cortex. Granger causal influences from motor cortex to postcentral sites, however, were weak in one monkey and not observed in the other. These results are the first, to our knowledge, to demonstrate in awake monkeys that synchronized beta oscillations bind multiple sensorimotor areas into a large-scale network during motor maintenance behavior and carry Granger causal influences from primary somatosensory and inferior posterior parietal cortices to motor cortex.

Optimization of combined electron and photon beams for breast cancer

Recently, intensity-modulated radiation therapy and modulated electron radiotherapy have gathered a growing interest for the treatment of breast and head and neck tumours. In this work, we carried out a study to combine electron and photon beams to achieve differential dose distributions for multiple target volumes simultaneously. A Monte Carlo based treatment planning system was investigated, which consists of a set of software tools to perform accurate dose calculation, treatment optimization, leaf sequencing and plan analysis. We compared breast treatment plans generated using this home-grown optimization and dose calculation software for different treatment techniques. Five different planning techniques have been developed for this study based on a standard photon beam whole breast treatment and an electron beam tumour bed cone down. Technique 1 includes two 6 MV tangential wedged photon beams followed by an anterior boost electron field. Technique 2 includes two 6 MV tangential intensity-modulated photon beams and the same boost electron field. Technique 3 optimizes two intensity-modulated photon beams based on a boost electron field. Technique 4 optimizes two intensity-modulated photon beams and the weight of the boost electron field. Technique 5 combines two intensity-modulated photon beams with an intensity-modulated electron field. Our results show that technique 2 can reduce hot spots both in the breast and the tumour bed compared to technique 1 (dose inhomogeneity is reduced from 34% to 28% for the target). Techniques 3, 4 and 5 can deliver a more homogeneous dose distribution to the target (with dose inhomogeneities for the target of 22%, 20% and 9%, respectively). In many cases techniques 3, 4 and 5 can reduce the dose to the lung and heart. It is concluded that combined photon and electron beam therapy may be advantageous for treating breast cancer compared to conventional treatment techniques using tangential wedged photon beams followed by a boost electron field.

Is partial coherence a viable technique for identifying generators of neural oscillations?

Partial coherence measures the linear relationship between two signals after the influence of a third signal has been removed. Gersch proposed in 1970 that partial coherence could be used to identify sources of driving for multivariate time series. This idea, referred to in this paper as Gersch Causality, has received wide acceptance and has been applied extensively to a variety of fields in the signal processing community. Neurobiological data from a given sensor include both the signals of interest and other unrelated processes collectively referred to as measurement noise. We show that partial-coherence-based Gersch Causality is extremely sensitive to signal-to-noise ratio; that is, for a group of three or more simultaneously recorded time series, the time series with the highest signal-to-noise ratio (i.e., relatively noise free) is often identified as the "driver" of the group, irrespective of the true underlying patterns of connectivity. This hypothesis is tested both theoretically and on experimental time series acquired from limbic brain structures during the theta rhythm.

Bisphosphonate treatment affects trabecular bone apparent modulus through micro-architecture rather than matrix properties

Bisphosphonates are emerging as an important treatment for osteoporosis. But whether the reduced fracture risk associated with bisphosphonate treatment is due to increased bone mass, improved trabecular architecture and/or increased secondary mineralization of the calcified matrix remains unclear. We examined the effects of bisphosphonates on both the trabecular architecture and matrix properties of canine trabecular bone. Thirty-six beagles were divided into a control group and two treatment groups, one receiving risedronate and the other alendronate at 5-6 times the clinical dose for osteoporosis treatment. After one year, the dogs were killed, and samples from the first lumbar vertebrae were examined using a combination of micro-computed tomography, finite element modeling, and mechanical testing. By combining these methods, we examined the treatment effects on the calcified matrix and trabecular architecture independently. Conventional histomorphometry and microdamage data were obtained from the second and third lumbar vertebrae of the same dogs [Bone 28 (2001) 524]. Bisphosphonate treatment resulted in an increased apparent Young's modulus, decreased bone turnover, increased calcified matrix density, and increased microdamage. We could not detect any change in the effective Young's modulus of the calcified matrix in the bisphosphonate treated groups. The observed increase in apparent Young's modulus was due to increased bone mass and altered trabecular architecture rather than changes in the calcified matrix modulus. We hypothesize that the expected increase in the Young's modulus of the calcified matrix due to the increased calcified matrix density was counteracted by the accumulation of microdamage.

Neural dynamics and the fundamental mechanisms of event-related brain potentials

Event-related potentials (ERPs) provide a critical link between the hemodynamic response, as measured by functional magnetic resonance imaging, and the dynamics of the underlying neuronal activity. Single-trial ERP recordings capture the oscillatory activity that are hypothesized to underlie both communication between brain regions and amplified processing of behaviorally relevant stimuli. However, precise interpretations of ERPs are precluded by uncertainty about their neural mechanisms. One influential theory holds that averaged sensory ERPs are generated by partial phase resetting of ongoing electroencephalographic oscillations, while another states that ERPs result from stimulus-evoked neural responses. We formulated critical predictions of each theory and tested these using direct, intracortical analyses of neural activity in monkeys. Our findings support a predominant role for stimulus-evoked activity in sensory ERP generation, and they outline both logic and methodology necessary for differentiating evoked and phase resetting contributions to cognitive and motor ERPs in future studies.

Enhancement of neural synchrony by time delay

In a network of neuronal oscillators with time-delayed coupling, we uncover a phenomenon of enhancement of neural synchrony by time delay: a stable synchronized state exists at low coupling strengths for significant time delays. By formulating a master stability equation for time-delayed networks of Hindmarsh-Rose neurons, we show that there is always an extended region of stable synchronous activity corresponding to low coupling strengths. Such synchrony could be achieved in the undelayed system only by much higher coupling strengths. This phenomenon of enhanced neural synchrony by delay has important implications, in particular, in understanding synchronization of distant neurons and information processing in the brain.