Epoch-specific functional networks involved in working memory

Working memory (WM) is not a unitary construct. There are distinct processes involved in encoding information, maintaining it on-line, and using it to guide responses. The anatomical configurations of these processes are more accurately analyzed as functionally connected networks than collections of individual regions. In the current study we analyzed event-related functional magnetic resonance imaging (fMRI) data from a Sternberg Item Recognition Paradigm WM task using a multivariate analysis method that allowed the linking of functional networks to temporally-separated WM epochs. The length of the delay epochs was varied to optimize isolation of the hemodynamic response (HDR) for each task epoch. All extracted functional networks displayed statistically significant sensitivity to delay length. Novel information extracted from these networks that was not apparent in the univariate analysis of these data included involvement of the hippocampus in encoding/probe, and decreases in BOLD signal in the superior temporal gyrus (STG), along with default-mode regions, during encoding/delay. The bilateral hippocampal activity during encoding/delay fits with theoretical models of WM in which memoranda held across the short term are activated long-term memory representations. The BOLD signal decreases in the STG were unexpected, and may reflect repetition suppression effects invoked by internal repetition of letter stimuli. Thus, analysis methods focusing on how network dynamics relate to experimental conditions allowed extraction of novel information not apparent in univariate analyses, and are particularly recommended for WM experiments for which task epochs cannot be randomized.

Cortical thickness changes in the non-lesioned hemisphere associated with non-paretic arm immobilization in modified CI therapy

Recent evidence suggests that immobilization of the upper limb for 2–3 weeks induces changes in cortical thickness as well as motor performance. In constraint induced (CI) therapy, one of the most effective interventions for hemiplegia, the non-paretic arm is constrained to enforce the use of the paretic arm in the home setting. With the present study we aimed to explore whether non-paretic arm immobilization in CI therapy induces structural changes in the non-lesioned hemisphere, and how these changes are related to treatment benefit. 31 patients with chronic hemiparesis participated in CI therapy with (N = 14) and without (N = 17) constraint. Motor ability scores were acquired before and after treatment. Diffusion tensor imaging (DTI) data was obtained prior to treatment. Cortical thickness was measured with the Freesurfer software. In both groups cortical thickness in the contralesional primary somatosensory cortex increased and motor function improved with the intervention. However the cortical thickness change was not associated with the magnitude of motor function improvement. Moreover, the treatment effect and the cortical thickness change were not significantly different between the constraint and the non-constraint groups. There was no correlation between fractional anisotropy changes in the non-lesioned hemisphere and treatment outcome. CI therapy induced cortical thickness changes in contralesional sensorimotor regions, but this effect does not appear to be driven by the immobilization of the non-paretic arm, as indicated by the absence of differences between the constraint and the non-constraint groups. Our data does not suggest that the arm immobilization used in CI therapy is associated with noticeable cortical thinning.

Intercontinental transport of nitrogen oxide pollution plumes

We describe the first satellite observation of intercontinental transport of nitrogen oxides emitted by power plants, verified by simulations with a particle tracer model. The analysis of such episodes shows that anthropogenic NOx plumes may influence the atmospheric chemistry thousands of kilometers away from its origin, as well as the ocean they traverse due to nitrogen fertilization. This kind of monitoring became possible by applying an improved algorithm to extract the tropospheric fraction of NO2 from the spectral data coming from the GOME instrument.As an example we show the observation of NO2 in the time period 4-14 May, 1998, from the South African Plateau to Australia which was possible due to favourable weather conditions during that time period which availed the satellite measurement. This episode was also simulated with the Lagrangian particle dispersion model FLEXPART which uses NOx emissions taken from an inventory for industrial emissions in South Africa and is driven with analyses from the European Centre for Medium-RangeWeather Forecasts. Additionally lightning emissions were taken into account by utilizing Lightning Imaging Sensor data. Lightning was found to contribute probably not more than 25% of the resulting concentrations. Both, the measured and simulated emission plume show matching patterns while traversing the Indian Ocean to Australia and show great resemblance to the aerosol and CO2 transport observed by Piketh et al. (2000).

Magnetic images of pharmaceutical dosage forms in the human gastrointestinal tract

Oral administration with solid dosage forms is a common route in the drug therapy widely used. The drug release by the disintegration process occurs in several gastrointestinal tract (GIT) regions. AC Biosusceptometry (ACB) was originally proposal to characterize the disintegration process of tablets in vitro and in the human stomach, through changes in magnetic signals. The aim of this work was to employ a multisensor ACB system to monitoring magnetic tablets and capsules in the human GIT and to obtain the magnetic images of the disintegration process. The ACB showed accuracy to quantify the gastric residence time, the intestinal transit time and the magnetic images allowed to visualize the disintegration of magnetic formulations in the GIT. The ACB is a non-invasive, radiation free technique, completely safe and harmless to the volunteers and had demonstrated potential to evaluate pharmaceutical dosage forms in the human gastrointestinal tract. © 2005 IEEE.

A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas

Evapotranspiration (ET) plays an important role in global climate dynamics and in primary production of terrestrial ecosystems; it represents the mass and energy transfer from the land to atmosphere. Limitations to measuring ET at large scales using ground-based methods have motivated the development of satellite remote sensing techniques. The purpose of this work is to evaluate the accuracy of the SEBAL algorithm for estimating surface turbulent heat fluxes at regional scale, using 28 images from MODIS. SEBAL estimates are compared with eddy-covariance (EC) measurements and results from the hydrological model MGB-IPH. SEBAL instantaneous estimates of latent heat flux (LE) yielded r(2) = 0.64 and r(2) = 0.62 over sugarcane croplands and savannas when compared against in situ EC estimates. At the same sites, daily aggregated estimates of LE were r(2) = 0.76 and r(2) = 0.66, respectively. Energy balance closure showed that turbulent fluxes over sugarcane croplands were underestimated by 7% and 9% over savannas. Average daily ET from SEBAL is in close agreement with estimates from the hydrological model for an overlay of 38,100 km(2) (r(2) = 0.88). Inputs to which the algorithm is most sensitive are vegetation index (NDVI), gradient of temperature (dT) to compute sensible heat flux (H) and net radiation (Re). It was verified that SEBAL has a tendency to overestimate results both at local and regional scales probably because of low sensitivity to soil moisture and water stress. Nevertheless the results confirm the potential of the SEBAL algorithm, when used with MODIS images for estimating instantaneous LE and daily ET from large areas.

Uniform approach to linear and nonlinear interrelation patterns in multivariate time series

Currently, a variety of linear and nonlinear measures is in use to investigate spatiotemporal interrelation patterns of multivariate time series. Whereas the former are by definition insensitive to nonlinear effects, the latter detect both nonlinear and linear interrelation. In the present contribution we employ a uniform surrogate-based approach, which is capable of disentangling interrelations that significantly exceed random effects and interrelations that significantly exceed linear correlation. The bivariate version of the proposed framework is explored using a simple model allowing for separate tuning of coupling and nonlinearity of interrelation. To demonstrate applicability of the approach to multivariate real-world time series we investigate resting state functional magnetic resonance imaging (rsfMRI) data of two healthy subjects as well as intracranial electroencephalograms (iEEG) of two epilepsy patients with focal onset seizures. The main findings are that for our rsfMRI data interrelations can be described by linear cross-correlation. Rejection of the null hypothesis of linear iEEG interrelation occurs predominantly for epileptogenic tissue as well as during epileptic seizures.

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.

Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

The spatial distribution of water in the inner coma of Comet 9P/Tempel 1: Comparison between models and observations

The near nucleus coma of Comet 9P/Tempel 1 has been simulated with the 3D Direct Simulation Monte Carlo (DSMC) code PDSC++ (Su, C.-C. [2013]. Parallel Direct Simulation Monte Carlo (DSMC) Methods for Modeling Rarefied Gas Dynamics. PhD Thesis, National Chiao Tung University, Taiwan) and the derived column densities have been compared to observations of the water vapour distribution found by using infrared imaging spectrometer on the Deep Impact spacecraft (Feaga, L.M., A’Hearn, M.F., Sunshine, J.M., Groussin, O., Farnham, T.L. [2007]. Icarus 191(2), 134–145. http://dx.doi.org/10.1016/j.icarus.2007.04.038). Modelled total production rates are also compared to various observations made at the time of the Deep Impact encounter. Three different models were tested. For all models, the shape model constructed from the Deep Impact observations by Thomas et al. (Thomas, P.C., Veverka, J., Belton, M.J.S., Hidy, A., A’Hearn, M.F., Farnham, T.L., et al. [2007]. Icarus, 187(1), 4–15. http://dx.doi.org/10.1016/j.icarus.2006.12.013) was used. Outgassing depending only on the cosine of the solar insolation angle on each shape model facet is shown to provide an unsatisfactory model. Models constructed on the basis of active areas suggested by Kossacki and Szutowicz (Kossacki, K., Szutowicz, S. [2008]. Icarus, 195(2), 705–724. http://dx.doi.org/10.1016/j.icarus.2007.12.014) are shown to be superior. The Kossacki and Szutowicz model, however, also shows deficits which we have sought to improve upon. For the best model we investigate the properties of the outflow.

The 2dF-SDSS LRG and QSO (2SLAQ) survey: the z < 2.1 quasar luminosity function from 5645 quasars to g=21.85

We have used the Two-Degree Field (2dF) instrument on the Anglo-Australian Telescope (AAT) to obtain redshifts of a sample of z < 3 and 18.0 < g < 21.85 quasars selected from Sloan Digital Sky Survey (SDSS) imaging. These data are part of a larger joint programme between the SDSS and 2dF communities to obtain spectra of faint quasars and luminous red galaxies, namely the 2dF-SDSS LRG and QSO (2SLAQ) Survey. We describe the quasar selection algorithm and present the resulting number counts and luminosity function of 5645 quasars in 105.7 deg(2). The bright-end number counts and luminosity functions agree well with determinations from the 2dF QSO Redshift Survey (2QZ) data to g similar to 20.2. However, at the faint end, the 2SLAQ number counts and luminosity functions are steeper (i.e. require more faint quasars) than the final 2QZ results from Croom et al., but are consistent with the preliminary 2QZ results from Boyle et al. Using the functional form adopted for the 2QZ analysis ( a double power law with pure luminosity evolution characterized by a second-order polynomial in redshift), we find a faint-end slope of beta =-1.78 +/- 0.03 if we allow all of the parameters to vary, and beta =-1.45 +/- 0.03 if we allow only the faint-end slope and normalization to vary (holding all other parameters equal to the final 2QZ values). Over the magnitude range covered by the 2SLAQ survey, our maximum-likelihood fit to the data yields 32 per cent more quasars than the final 2QZ parametrization, but is not inconsistent with other g > 21 deep surveys for quasars. The 2SLAQ data exhibit no well-defined 'break' in the number counts or luminosity function, but do clearly flatten with increasing magnitude. Finally, we find that the shape of the quasar luminosity function derived from 2SLAQ is in good agreement with that derived from Type I quasars found in hard X-ray surveys.

Pattern recognition analyses of brain activation elicited by happy and neutral faces in unipolar and bipolar depression

Objectives: Recently, pattern recognition approaches have been used to classify patterns of brain activity elicited by sensory or cognitive processes. In the clinical context, these approaches have been mainly applied to classify groups of individuals based on structural magnetic resonance imaging (MRI) data. Only a few studies have applied similar methods to functional MRI (fMRI) data. Methods: We used a novel analytic framework to examine the extent to which unipolar and bipolar depressed individuals differed on discrimination between patterns of neural activity for happy and neutral faces. We used data from 18 currently depressed individuals with bipolar I disorder (BD) and 18 currently depressed individuals with recurrent unipolar depression (UD), matched on depression severity, age, and illness duration, and 18 age- and gender ratio-matched healthy comparison subjects (HC). fMRI data were analyzed using a general linear model and Gaussian process classifiers. Results: The accuracy for discriminating between patterns of neural activity for happy versus neutral faces overall was lower in both patient groups relative to HC. The predictive probabilities for intense and mild happy faces were higher in HC than in BD, and for mild happy faces were higher in HC than UD (all p < 0.001). Interestingly, the predictive probability for intense happy faces was significantly higher in UD than BD (p = 0.03). Conclusions: These results indicate that patterns of whole-brain neural activity to intense happy faces were significantly less distinct from those for neutral faces in BD than in either HC or UD. These findings indicate that pattern recognition approaches can be used to identify abnormal brain activity patterns in patient populations and have promising clinical utility as techniques that can help to discriminate between patients with different psychiatric illnesses.

Examination of the predictive value of structural magnetic resonance scans in bipolar disorder:a pattern classification approach

Background - Bipolar disorder (BD) is one of the leading causes of disability worldwide. Patients are further disadvantaged by delays in accurate diagnosis ranging between 5 and 10 years. We applied Gaussian process classifiers (GPCs) to structural magnetic resonance imaging (sMRI) data to evaluate the feasibility of using pattern recognition techniques for the diagnostic classification of patients with BD. Method - GPCs were applied to gray (GM) and white matter (WM) sMRI data derived from two independent samples of patients with BD (cohort 1: n = 26; cohort 2: n = 14). Within each cohort patients were matched on age, sex and IQ to an equal number of healthy controls. Results - The diagnostic accuracy of the GPC for GM was 73% in cohort 1 and 72% in cohort 2; the sensitivity and specificity of the GM classification were respectively 69% and 77% in cohort 1 and 64% and 99% in cohort 2. The diagnostic accuracy of the GPC for WM was 69% in cohort 1 and 78% in cohort 2; the sensitivity and specificity of the WM classification were both 69% in cohort 1 and 71% and 86% respectively in cohort 2. In both samples, GM and WM clusters discriminating between patients and controls were localized within cortical and subcortical structures implicated in BD. Conclusions - Our results demonstrate the predictive value of neuroanatomical data in discriminating patients with BD from healthy individuals. The overlap between discriminative networks and regions implicated in the pathophysiology of BD supports the biological plausibility of the classifiers.

Departure of high temperature iron lines from the equilibrium state in flaring solar plasmas

The aim of this study is to clarify if the assumption of ionization equilibrium and a Maxwellian electron energy distribution is valid in flaring solar plasmas. We analyze the 2014 December 20 X1.8 flare, in which the \ion{Fe}{xxi} 187~\AA, \ion{Fe}{xxii} 253~\AA, \ion{Fe}{xxiii} 263~\AA\ and \ion{Fe}{xxiv} 255~\AA\ emission lines were simultaneously observed by the EUV Imaging Spectrometer onboard the Hinode satellite. Intensity ratios among these high temperature Fe lines are compared and departures from isothermal conditions and ionization equilibrium examined. Temperatures derived from intensity ratios involving these four lines show significant discrepancies at the flare footpoints in the impulsive phase, and at the looptop in the gradual phase. Among these, the temperature derived from the \ion{Fe}{xxii}/\ion{Fe}{xxiv} intensity ratio is the lowest, which cannot be explained if we assume a Maxwellian electron distribution and ionization equilibrium, even in the case of a multi-thermal structure. This result suggests that the assumption of ionization equilibrium and/or a Maxwellian electron energy distribution can be violated in evaporating solar plasma around 10MK.

Multi-body simulation of a canine hind limb: model development, experimental validation and calculation of ground reaction forces

Background: Among other causes the long-term result of hip prostheses in dogs is determined by aseptic loosening. A prevention of prosthesis complications can be achieved by an optimization of the tribological system which finally results in improved implant duration. In this context a computerized model for the calculation of hip joint loadings during different motions would be of benefit. In a first step in the development of such an inverse dynamic multi-body simulation (MBS-) model we here present the setup of a canine hind limb model applicable for the calculation of ground reaction forces. Methods: The anatomical geometries of the MBS-model have been established using computer tomography- (CT-) and magnetic resonance imaging- (MRI-) data. The CT-data were collected from the pelvis, femora, tibiae and pads of a mixed-breed adult dog. Geometric information about 22 muscles of the pelvic extremity of 4 mixed-breed adult dogs was determined using MRI. Kinematic and kinetic data obtained by motion analysis of a clinically healthy dog during a gait cycle (1 m/s) on an instrumented treadmill were used to drive the model in the multi-body simulation. Results and Discussion: As a result the vertical ground reaction forces (z-direction) calculated by the MBS-system show a maximum deviation of 1.75%BW for the left and 4.65%BW for the right hind limb from the treadmill measurements. The calculated peak ground reaction forces in z- and y-direction were found to be comparable to the treadmill measurements, whereas the curve characteristics of the forces in y-direction were not in complete alignment. Conclusion: In conclusion, it could be demonstrated that the developed MBS-model is suitable for simulating ground reaction forces of dogs during walking. In forthcoming investigations the model will be developed further for the calculation of forces and moments acting on the hip joint during different movements, which can be of help in context with the in silico development and testing of hip prostheses.

Large national series of patients with Xq28 duplication involving MECP2: Delineation of brain MRI abnormalities in 30 affected patients.

Xq28 duplications encompassing MECP2 have been described in male patients with a severe neurodevelopmental disorder associated with hypotonia and spasticity, severe learning disability, stereotyped movements, and recurrent pulmonary infections. We report on standardized brain magnetic resonance imaging (MRI) data of 30 affected patients carrying an Xq28 duplication involving MECP2 of various sizes (228 kb to 11.7 Mb). The aim of this study was to seek recurrent malformations and attempt to determine whether variations in imaging features could be explained by differences in the size of the duplications. We showed that 93% of patients had brain MRI abnormalities such as corpus callosum abnormalities (n = 20), reduced volume of the white matter (WM) (n = 12), ventricular dilatation (n = 9), abnormal increased hyperintensities on T2-weighted images involving posterior periventricular WM (n = 6), and vermis hypoplasia (n = 5). The occipitofrontal circumference varied considerably between >+2SD in five patients and <-2SD in four patients. Among the nine patients with dilatation of the lateral ventricles, six had a duplication involving L1CAM. The only patient harboring bilateral posterior subependymal nodular heterotopia also carried an FLNA gene duplication. We could not demonstrate a correlation between periventricular WM hyperintensities/delayed myelination and duplication of the IKBKG gene. We thus conclude that patients with an Xq28 duplication involving MECP2 share some similar but non-specific brain abnormalities. These imaging features, therefore, could not constitute a diagnostic clue. The genotype-phenotype correlation failed to demonstrate a relationship between the presence of nodular heterotopia, ventricular dilatation, WM abnormalities, and the presence of FLNA, L1CAM, or IKBKG, respectively, in the duplicated segment.