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Eye-target synchronization is critical for effective smooth pursuit of a moving visual target. We apply the nonlinear dynamical technique of stochastic-phase synchronization to human visual pursuit of a moving target, in both normal and mild traumatic brain-injured (mTBI) patients. We observe significant fatigue effects in all subject populations, in which subjects synchronize better with the target during the first half of the trial than in the second half. The fatigue effect differed, however, between the normal and the mTBI populations and between old and young subpopulations of each group. In some cases, the younger (or=40 years old) normal subjects performed better than mTBI subjects and also better than older (40 years old) normal subjects. Our results, however, suggest that further studies will be necessary before a standard of "normal" smooth pursuit synchronization can be developed.

Increasing the spatial resolution in functional Magnetic Resonance Imaging (fMRI) inherently lowers the signal-to-noise ratio (SNR). In order to still detect functionally significant activations in high-resolution images, spatial smoothing of the data is required. However, conventional non-adaptive smoothing comes with a reduced effective resolution, foiling the benefit of the higher acquisition resolution. We show how our recently proposed structural adaptive smoothing procedure for functional MRI data can improve signal detection of high-resolution fMRI experiments regardless of the lower SNR. The procedure is evaluated on human visual and sensory-motor mapping experiments. In these applications, the higher resolution could be fully utilized and high-resolution experiments were outperforming normal resolution experiments by means of both statistical significance and information content.

Electrophysiological and activity-dependent gene expression studies of birdsong have contributed to the understanding of the neural representation of natural sounds. However, we have limited knowledge about the overall spatial topography of song representation in the avian brain. Here, we adapt the noninvasive functional MRI method in mildly sedated zebra finches ( Taeniopygia guttata ) to localize and characterize song driven brain activation. Based on the blood oxygenation level-dependent signal, we observed a differential topographic responsiveness to playback of bird's own song, tutor song, conspecific song, and a pure tone as a nonsong stimulus. The bird's own song caused a stronger response than the tutor song or tone in higher auditory areas. This effect was more pronounced in the medial parts of the forebrain. We found left–right hemispheric asymmetry in sensory responses to songs, with significant discrimination between stimuli observed only in the right hemisphere. This finding suggests that perceptual responses might be lateralized in zebra finches. In addition to establishing the feasibility of functional MRI in sedated songbirds, our results demonstrate spatial coding of song in the zebra finch forebrain, based on developmental familiarity and experience.

Background European citizens are increasingly being offered Internet health services. This study investigated patterns of health-related Internet use, its consequences, and citizens' expectations about their doctors' provision of e-health services. Methods Representative samples were obtained from the general populations in Norway, Denmark, Germany, Greece, Poland, Portugal and Latvia. The total sample consisted of 7934 respondents. Interviews were conducted by telephone. Results 44 % of the total sample, 71 % of the Internet users, had used the Internet for health purposes. Factors that positively affected the use of Internet for health purposes were youth, higher education, white-collar or no paid job, visits to the GP during the past year, long-term illness or disabilities, and a subjective assessment of one's own health as good. Women were the most active health users among those who were online. One in four of the respondents used the Internet to prepare for or follow up doctors' appointments. Feeling reassured after using the Internet for health purposes was twice as common as experiencing anxieties. When choosing a new doctor, more than a third of the sample rated the provision of e-health services as important. Conclusion The users of Internet health services differ from the general population when it comes to health and demographic variables. The most common way to use the Internet in health matters is to read information, second comes using the net to decide whether to see a doctor and to prepare for and follow up on doctors' appointments. Hence, health-related use of the Internet does affect patients' use of other health services, but it would appear to supplement rather than to replace other health services.

This study examined whether ventral frontostriatal regions differentially code expected and unexpected reward outcomes. We parametrically manipulated the probability of reward and examined the neural response to reward and nonreward for each probability condition in the ventral striatum and the orbitofrontal cortex (OFC). By late trials of the experiment, subjects showed slower behavioral responses for the condition with the lowest probability of reward, relative to the condition with the highest probability of reward. At the neural level, both the nucleus accumbens (NAcc) and OFC showed greater activation to rewarded relative to nonrewarded trials, but the accumbens appeared to be most sensitive to violations in expected reward outcomes. These data suggest distinct roles for frontostriatal circuitry in reward prediction and in responding to violations in expectations.

The coevolutionary relationships between brood parasites and their hosts are often studied by examining the egg rejection behaviour of host species using artificial eggs. However, the traditional methods for producing artificial eggs out of plasticine, plastic, wood, or plaster-of-Paris are laborious, imprecise, and prone to human error. As an alternative, 3D printing may reduce human error, enable more precise manipulation of egg size and shape, and provide a more accurate and replicable protocol for generating artificial stimuli than traditional methods. However, the usefulness of 3D printing technology for egg rejection research remains to be tested. Here, we applied 3D printing technology to the extensively studied egg rejection behaviour of American robins, Turdus migratorius. Eggs of the robin’s brood parasites, brownheaded cowbirds, Molothrus ater, vary greatly in size and shape, but it is unknown whether host egg rejection decisions diff er across this gradient of natural variation. We printed artificial eggs that encompass the natural range of shapes and sizes of cowbird eggs, painted them to resemble either robin or cowbird egg colour, and used them to artificially parasitize nests of breeding wild robins. In line with previous studies, we show that robins accept mimetically coloured and reject non-mimetically coloured artificial eggs. Although we found no evidence that subtle di ff erences in parasitic egg size or shape aff ect robins’ rejection decisions, 3D printing will provide an opportunity for more extensive experimentation on the potential biological or evolutionary significance of size and shape variation of foreign eggs in rejection decisions. We provide a detailed protocol for generating 3D printed eggs using either personal 3D printers or commercial printing services, and highlight additional potential future applications for this technology in the study of egg rejection.

CO RR EC TE D P RO OF these abnormalities through motor tests. Homozyous mice performed poorly and showed no improvement on the inverted grip and rotarod tests. Together, these data suggest that the mice are impaired in their motor ability and strength, which may be due to gross accumulative manifestations in the brain. Additionally, they demonstrated increased stereotypic behavior in the open field test by entering the center zone less frequently and in categorized observation by spending more time chewing, but decreased stereotypic behavior in the marble burying test by burying fewer marbles. This study implicates particular sphingolipids in highly specific functions within the brain and a complex, but specific, system to regulate their expression. The detailed ceramide composition of the mouse brain illustrated in this study can serve as a reference point upon which brains from other neurological and storage disorders can be compared.

A novel two-dimensional ladder network resonator design is introduced for signal transmission and detection in magnetic resonance imaging. It is shown that planar structures consisting solely of inductively coupled elements have a high-pass eigenmode spectrum and exhibit eigenfunctions which can be used for magnetic resonance imaging, including quadrature operation. Two 5 times 5 element prototypes, a planar surface coil and a volume head coil, are presented to demonstrate the suitability of the design for imaging at 3.0 Tesla

We used diffusion tensor imaging (DTI) to study 2 patients with traumatic brain injury. The first patient recovered reliable expressive language after 19 years in a minimally conscious state (MCS); the second had remained in MCS for 6 years. Comparison of white matter integrity in the patients and 20 normal subjects using histograms of apparent diffusion constants and diffusion anisotropy identified widespread altered diffusivity and decreased anisotropy in the damaged white matter. These findings remained unchanged over an 18-month interval between 2 studies in the first patient. In addition, in this patient, we identified large, bilateral regions of posterior white matter with significantly increased anisotropy that reduced over 18 months. In contrast, notable increases in anisotropy within the midline cerebellar white matter in the second study correlated with marked clinical improvements in motor functions. This finding was further correlated with an increase in resting metabolism measured by PET in this subregion. Aberrant white matter structures were evident in the second patient's DTI images but were not clinically correlated. We propose that axonal regrowth may underlie these findings and provide a biological mechanism for late recovery. Our results are discussed in the context of recent experimental studies that support this inference.

This article reviews and discusses recent findings in functional MRI at 1.5 and 3.0 T magnetic field strengths, in research and clinical applications. Particular attention is paid to comparative studies and to an explanation of the physical and biological dependencies leading to potential gains and tradeoffs of functional scanning at magnets with a high field strength.

Data from functional magnetic resonance imaging (fMRI) consist of time series of brain images that are characterized by a low signal-to-noise ratio. In order to reduce noise and to improve signal detection, the fMRI data are spatially smoothed. However, the common application of a Gaussian filter does this at the cost of loss of information on spatial extent and shape of the activation area. We suggest to use the propagation-separation procedures introduced by Polzehl, J., Spokoiny, V. (2006). Propagation-separation approach for local likelihood estimation. Probab. Theory Relat. Fields, in print. instead. We show that this significantly improves the information on the spatial extent and shape of the activation region with similar results for the noise reduction. To complete the statistical analysis, signal detection is based on thresholds defined by random field theory. Effects of adaptive and non-adaptive smoothing are illustrated by artificial examples and an analysis of experimental data.

We propose a quantitative model for human smooth pursuit tracking of a continuously moving visual target which is based on synchronization of an internal expectancy model of the target position coupled to the retinal target signal. The model predictions are tested in a smooth circular pursuit eye tracking experiment with transient target blanking of variable duration. In subjects with a high tracking accuracy, the model accounts for smooth pursuit and repeatedly reproduces quantitatively characteristic patterns of the eye dynamics during target blanking. In its simplest form, the model has only one free parameter, a coupling constant. An extended model with a second parameter, a time delay or memory term, accounts for predictive smooth pursuit eye movements which advance the target. The model constitutes an example of synchronization of a complex biological system with perceived sensory signals.

We present methods for detecting phase synchronization of two unidirectionally coupled, self-sustained noisy oscillators from a signal of the driven oscillator alone. One method detects soft, another hard phase locking. Both are applied to the problem of detecting phase synchronization in von Karman vortex flow meters., 4 pages, 4 figures

We introduce a grammar-based hybrid approach to reverse engineering nonlinear ordinary differential equation models from observed time series. This hybrid approach combines a genetic algorithm to search the space of model architectures with a Kalman filter to estimate the model parameters. Domain-specific knowledge is used in a context-free grammar to restrict the search space for the functional form of the target model. We find that the hybrid approach outperforms a pure evolutionary algorithm method, and we observe features in the evolution of the dynamical models that correspond with the emergence of favorable model components. We apply the hybrid method to both artificially generated time series and experimentally observed protein levels from subjects who received the smallpox vaccine. From the observed data, we infer a cytokine protein interaction network for an individual's response to the smallpox vaccine.

Late infantile neuronal ceroid lipofuscinosis (LINCL) is a fatal childhood neurodegenerative lysosomal storage disease with no known therapy. There are estimated to be 200 to 300 children in the United States at any one time with the disease. LINCL is a genetic disease resulting from a deficiency of tripeptidyl peptidase I (TPP-I), a proteolytic enzyme encoded by CLN2, the gene that is mutated in individuals with LINCL. The subjects are chronically ill, with a progressive CNS disorder that invariably results in death, typically by age 8 to 12 years. The strategy of this clinical study is based on the concept that persistent expression in the CNS of the normal CLN2 cDNA with production of sufficient amounts of TPP-I should prevent further loss of neurons, and hence limit disease progression. To assess this concept, an adeno-associated virus vector (AAV2CUh-CLN2) will be used to transfer to and express the human CLN2 cDNA in the brain of children with LINCL. The vector consists of the AAV2 capsid enclosing the 4278-base single-stranded genome consisting of the two inverted terminal repeats of AAV serotype 2 and an expression cassette composed of the human cytomegalovirus (CMV) enhancer, the chicken beta-actin promoter/splice donor and 5' end of the intron, the 3' end of the rabbit P-globin intron and splice acceptor, the human CLN2 cDNA with an optimized Kozak translation initiation signal, and the polyadenylation/transcription stop codon from rabbit 3-globin. The proposed study will include 10 individuals and will be divided into two parts. Group A, to be studied first, will include four individuals with the severe form of the disease. Group B of the trial will include six individuals with a moderate form of the disease. After direct intracranial administration of the vector, there will be neurological assessment based on the LINCL clinical rating scale and magnetic resonance imaging/magnetic resonance spectroscopy assessment of the brain in regions of vector administration. The data generated will help evaluate two hypotheses: (1) that it is safe to carry out direct intracranial administration of the AAV2cuhCLN2 vector to the CNS of individuals with LINCL, and (2) that administration of the AAV2cuhCLN2 vector will slow down or halt the progression of the disease in the central nervous system.

Epilepsy is characterized by the sudden occurrence of seizures disturbing the perception or behavior of epileptic patients. Several prediction methods have claimed to be able to predict seizures based on EEG-recordings minutes in advance, which opens up new approaches to treat the disease. However, the term seizure prediction is not unequivocally defined and different assessment criteria for prediction methods exist which impedes the comparison between methods. Moreover, only little attention is paid to the dependency between sensitivity and false prediction rate. We address these shortcomings and introduce a terminology and assessment criterion for seizure prediction methods based on statistical and clinical considerations: the seizure prediction characteristic.

Several methods have been suggested to predict the onset of epileptic seizures from EEG data. We evaluated the performance of three predictions methods: the "dynamical similarity index", the "effective correlation dimension" and an extended, prospective version of the "accumulated energy". These prediction methods were applied on a large pool of intracranial EEG data from 21 patients. Altogether, 582 hours EEG data and 88 seizures were investigated.The "seizure prediction characteristic" was used as assessment criterion. It considers the strong dependency between sensitivity and the false prediction rate. For a rate of 1 to 3.6 false predictions per day, the similarity index yields a sensitivity between 21% and 42%, which was the best result of the three examined prediction methods. The extended version of the accumulated energy achieves a sensitivity between 18% and 31%, the effective correlation dimension between 13% and 30%.

We review the problem of estimating parameters and unobserved trajectory components from noisy time series measurements of continuous nonlinear dynamical systems. It is first shown that in parameter estimation techniques that do not take the measurement errors explicitly into account, like regression approaches, noisy measurements can produce inaccurate parameter estimates. Another problem is that for chaotic systems the cost functions that have to be minimized to estimate states and parameters are so complex that common optimization routines may fail. We show that the inclusion of information about the time-continuous nature of the underlying trajectories can improve parameter estimation considerably. Two approaches, which take into account both the errors-in-variables problem and the problem of complex cost functions, are described in detail: shooting approaches and recursive estimation techniques. Both are demonstrated on numerical examples.

Signal data from DNA-microarray ("chip") technology can be noisy; i.e., the signal variation of one gene on a series of repetitive chips can be substantial. It is becoming more and more recognized that a sufficient number of chip replicates has to be made in order to separate correct from incorrect signals. To reduce the systematic fraction of the noise deriving from pipetting errors, from different treatment of chips during hybridization, and from chip-to-chip manufacturing variability, normalization schemes are employed. We present here an iterative nonparametric nonlinear normalization scheme called simultaneous alternating conditional expectation (sACE), which is designed to maximize correlation between chip repeats in all-chip-against-all space. We tested sACE on 28 experiments with 158 Affymetrix one-color chips. The procedure should be equally applicable to other DNA-microarray technologies, e.g., two-color chips. We show that the reduction of noise compared to a simple normalization scheme like the widely used linear global normalization leads to fewer false-positive calls, i.e., to fewer genes which have to be laboriously confirmed by independent methods such as TaqMan or quantitative PCR.

We report a preliminary measurement of the first and second moments of the hadronic mass distributions in B {yields} X{sub c}{ell}{nu} decays. The measurements are based on {Upsilon}(4S) {yields} B{bar B} events where the hadronic decay of one of the B mesons is fully reconstructed and a charged lepton from the decay of the other B meson is identified. The moments are presented for threshold lepton momenta ranging from 0.9 to 1.6 GeV. From the moments we determine the non-perturbative Heavy Quark Expansion (HQE) parameters, {bar {Lambda}} and {lambda}{sub 1}. We combine the measured moments with earlier BABAR measurements of the semileptonic branching ratios and B lifetimes and perform a simultaneous fit to the HQE for the moments obtained for different threshold lepton momenta and the semileptonic decay width. This fit results in an improved value for the CKM matrix element |V{sub cb}|.

The problem of identifying continuous spatiotemporal nonlinear systems from noisy and indirect observations is determined by its computational complexity. We propose a solution by means of nonlinear state space filtering along with a state partition technique. The method is demonstrated to be computationally feasible for spatiotemporal data with properties that occur typically in experimental recordings. It is applied to one component of the simulated chaotic data of a two-component reaction diffusion system, yielding estimates of both the unobserved state component and the diffusion constant.

A preliminary determination of the first moment of the hadronic mass distribution in semileptonic B decays has been obtained as a function of the minimum lepton momentum, ranging from 0.9 to 1.6 GeV/c. The measurement is based on a new technique involving B{bar B} events in which one fully reconstructed B meson decays hadronically and the recoiling B decays semileptonically. The mass of the hadrons in the semileptonic decay is determined from a kinematic fit to the whole event. For different minimum lepton momenta, the mass distribution is decomposed into contributions from various charm resonant states and a non-resonant contribution, allowing for the determination of the first moment. From these moments the Heavy Quark Effective Theory (HQET) parameters {lambda}{sub 1} and {bar {Lambda}} can be derived. For lepton momenta in the B rest frame above 1.5 GeV/c, we find a first moment that is compatible with existing measurements. However, if we extend the measurement to lower values of lepton momenta, the data can only be described by Operator Product Expansion calculations if we use significantly different values for {bar {Lambda}} and {lambda}{sub 1} than obtained from earlier measurements based on lepton momentummore » spectra and the photon spectrum in b {yields} s{gamma} transitions.« less

We study the problem of simultaneous estimation of parameters and unobserved states from noisy data of nonlinear time-continuous systems, including the case of additive stochastic forcing. We propose a solution by adapting the recently developed statistical method of unscented Kalman filtering to this problem. Due to its recursive and derivative-free structure, this method minimizes the cost function in a computationally efficient and robust way. It is found that parameters as well as unobserved components can be estimated with high accuracy, including confidence bands, from heavily noise-corrupted data.

Systems with a time-delayed feedback occur in various areas, for example in physics, climatology, physiology, and economy. In case of a nonlinear feedback, the systems can show complex behavior, like bifurcations, several types of oscillations, and chaotic solutions.