Statistical shape modeling of pathological scoliotic vertebrae: A comparative analysis

Statistical shape models (SSMs) have been used widely as a basis for segmenting and interpreting complex anatomical structures. The robustness of these models are sensitive to the registration procedures, i.e., establishment of a dense correspondence across a training data set. In this work, two SSMs based on the same training data set of scoliotic vertebrae, and registration procedures were compared. The first model was constructed based on the original binary masks without applying any image pre- and post-processing, and the second was obtained by means of a feature preserving smoothing method applied to the original training data set, followed by a standard rasterization algorithm. The accuracies of the correspondences were assessed quantitatively by means of the maximum of the mean minimum distance (MMMD) and Hausdorf distance (H(D)). Anatomical validity of the models were quantified by means of three different criteria, i.e., compactness, specificity, and model generalization ability. The objective of this study was to compare quasi-identical models based on standard metrics. Preliminary results suggest that the MMMD distance and eigenvalues are not sensitive metrics for evaluating the performance and robustness of SSMs.

Effect of pulsatility on the mathematical modeling of rotary blood pumps

In this study, the effect of time derivatives of flow rate and rotational speed was investigated on the mathematical modeling of a rotary blood pump (RBP). The basic model estimates the pressure head of the pump as a dependent variable using measured flow and speed as predictive variables. Performance of the model was evaluated by adding time derivative terms for flow and speed. First, to create a realistic working condition, the Levitronix CentriMag RBP was implanted in a sheep. All parameters from the model were physically measured and digitally acquired over a wide range of conditions, including pulsatile speed. Second, a statistical analysis of the different variables (flow, speed, and their time derivatives) based on multiple regression analysis was performed to determine the significant variables for pressure head estimation. Finally, different mathematical models were used to show the effect of time derivative terms on the performance of the models. In order to evaluate how well the estimated pressure head using different models fits the measured pressure head, root mean square error and correlation coefficient were used. The results indicate that inclusion of time derivatives of flow and speed can improve model accuracy, but only minimally.

Social cognition as a mediator variable between neurocognition and functional outcome in schizophrenia: empirical review and new results by structural equation modeling

Cognitive impairments are currently regarded as important determinants of functional domains and are promising treatment goals in schizophrenia. Nevertheless, the exact nature of the interdependent relationship between neurocognition and social cognition as well as the relative contribution of each of these factors to adequate functioning remains unclear. The purpose of this article is to systematically review the findings and methodology of studies that have investigated social cognition as a mediator variable between neurocognitive performance and functional outcome in schizophrenia. Moreover, we carried out a study to evaluate this mediation hypothesis by the means of structural equation modeling in a large sample of 148 schizophrenia patients. The review comprised 15 studies. All but one study provided evidence for the mediating role of social cognition both in cross-sectional and in longitudinal designs. Other variables like motivation and social competence additionally mediated the relationship between social cognition and functional outcome. The mean effect size of the indirect effect was 0.20. However, social cognitive domains were differentially effective mediators. On average, 25% of the variance in functional outcome could be explained in the mediation model. The results of our own statistical analysis are in line with these conclusions: Social cognition mediated a significant indirect relationship between neurocognition and functional outcome. These results suggest that research should focus on differential mediation pathways. Future studies should also consider the interaction with other prognostic factors, additional mediators, and moderators in order to increase the predictive power and to target those factors relevant for optimizing therapy effects.

On the modeling of drug induced respiratory depression in the non-steady-state

The ability of anesthetic agents to provide adequate analgesia and sedation is limited by the ventilatory depression associated with overdosing in spontaneously breathing patients. Therefore, quantitation of drug induced ventilatory depression is a pharmacokinetic-pharmacodynamic problem relevant to the practice of anesthesia. Although several studies describe the effect of respiratory depressant drugs on isolated endpoints, an integrated description of drug induced respiratory depression with parameters identifiable from clinically available data is not available. This study proposes a physiological model of CO2 disposition, ventilatory regulation, and the effects of anesthetic agents on the control of breathing. The predictive performance of the model is evaluated through simulations aimed at reproducing experimental observations of drug induced hypercarbia and hypoventilation associated with intravenous administration of a fast-onset, highly potent anesthetic mu agonist (including previously unpublished experimental data determined after administration of 1 mg alfentanil bolus). The proposed model structure has substantial descriptive capability and can provide clinically relevant predictions of respiratory inhibition in the non-steady-state to enhance safety of drug delivery in the anesthetic practice.

The Assessment of Multiple Processes Underlying the Attentional Blink: A Fixed - links Modeling Approach based on Behavioral and Electrophysiological Data

When observers are presented with two visual targets appearing in the same position in close temporal proximity, a marked reduction in detection performance of the second target has often been reported, the so-called attentional blink phenomenon. Several studies found a similar decrement of P300 amplitudes during the attentional blink period as observed with detection performances of the second target. However, whether the parallel courses of second target performances and corresponding P300 amplitudes resulted from the same underlying mechanisms remained unclear. The aim of our study was therefore to investigate whether the mechanisms underlying the AB can be assessed by fixed-links modeling and whether this kind of assessment would reveal the same or at least related processes in the behavioral and electrophysiological data. On both levels of observation three highly similar processes could be identified: an increasing, a decreasing and a u-shaped trend. Corresponding processes from the behavioral and electrophysiological data were substantially correlated, with the two u-shaped trends showing the strongest association with each other. Our results provide evidence for the assumption that the same mechanisms underlie attentional blink task performance at the electrophysiological and behavioral levels as assessed by fixed-links models.

The Genesis Solar Wind Concentrator: Flight and Post-Flight Conditions and Modeling of Instrumental Fractionation

The Genesis mission Solar Wind Concentrator was built to enhance fluences of solar wind by an average of 20x over the 2.3 years that the mission exposed substrates to the solar wind. The Concentrator targets survived the hard landing upon return to Earth and were used to determine the isotopic composition of solar-wind—and hence solar—oxygen and nitrogen. Here we report on the flight operation of the instrument and on simulations of its performance. Concentration and fractionation patterns obtained from simulations are given for He, Li, N, O, Ne, Mg, Si, S, and Ar in SiC targets, and are compared with measured concentrations and isotope ratios for the noble gases. Carbon is also modeled for a Si target. Predicted differences in instrumental fractionation between elements are discussed. Additionally, as the Concentrator was designed only for ions ≤22 AMU, implications of analyzing elements as heavy as argon are discussed. Post-flight simulations of instrumental fractionation as a function of radial position on the targets incorporate solar-wind velocity and angular distributions measured in flight, and predict fractionation patterns for various elements and isotopes of interest. A tighter angular distribution, mostly due to better spacecraft spin stability than assumed in pre-flight modeling, results in a steeper isotopic fractionation gradient between the center and the perimeter of the targets. Using the distribution of solar-wind velocities encountered during flight, which are higher than those used in pre-flight modeling, results in elemental abundance patterns slightly less peaked at the center. Mean fractionations trend with atomic mass, with differences relative to the measured isotopes of neon of +4.1±0.9 ‰/amu for Li, between -0.4 and +2.8 ‰/amu for C, +1.9±0.7‰/amu for N, +1.3±0.4 ‰/amu for O, -7.5±0.4 ‰/amu for Mg, -8.9±0.6 ‰/amu for Si, and -22.0±0.7 ‰/amu for S (uncertainties reflect Monte Carlo statistics). The slopes of the fractionation trends depend to first order only on the relative differential mass ratio, Δ m/ m. This article and a companion paper (Reisenfeld et al. 2012, this issue) provide post-flight information necessary for the analysis of the Genesis solar wind samples, and thus serve to complement the Space Science Review volume, The Genesis Mission (v. 105, 2003).

Performance on auditory and visual temporal informationprocessing is related to psychometric intelligence

The present study investigated the relationship between psychometric intelligence and temporal resolution power (TRP) as simultaneously assessed by auditory and visual psychophysical timing tasks. In addition, three different theoretical models of the functional relationship between TRP and psychometric intelligence as assessed by means of the Adaptive Matrices Test (AMT) were developed. To test the validity of these models, structural equation modeling was applied. Empirical data supported a hierarchical model that assumed auditory and visual modality-specific temporal processing at a first level and amodal temporal processing at a second level. This second-order latent variable was substantially correlated with psychometric intelligence. Therefore, the relationship between psychometric intelligence and psychophysical timing performance can be explained best by a hierarchical model of temporal information processing.

Individual group efficacy beliefs and performance motivation: A mediational approach

Introduction: According to the theoretical model of Cranach, Ochsenbein, and Valach (1986) understanding group actions needs consideration of aspects at both the group level and the level of individual members. For example individual action units constituting group actions are motivated at the individual level while potentially being affected by characteristics of the group. Theoretically, group efficacy beliefs could be a part of this motivational process as they are an individual’s cognitive contents about group-level abilities to perform well in a specific task. Positive relations between group level efficacy-beliefs and group performance have been reported and Bandura and Locke (2003) argue that this relationship is being mediated by motivational processes and goal setting. The aims of this study were a) to examine the effects of group characteristics on individual performance motivation and b) to test if those are mediated by individual group efficacy beliefs. Methods: Forty-seven students (M=22.83 years, SD=2.83, 34% women) of the university of Berne participated in this scenario based experiment. Data were collected on two collection points. Subjects were provided information about fictive team members with whom they had to perform a group triathlon. Three values (low, medium, high) of the other team members’ abilities to perform in their parts of the triathlon (swimming and biking respectively) were combined in a 3x3 full factorial design (Anderson, 1982) yielding nine groups. Subjects were asked how confident they were that the teams would perform well in the task (individual group efficacy beliefs), and to provide information about their motivation to perform at their best in the respective group contexts (performance motivation). Multilevel modeling (Mplus) was used to estimate the effects of the factors swim and bike, and the context-varying covariate individual group efficacy beliefs on performance motivation. Further analyses were undertaken to test if the effects of group contexts on performance motivation are mediated by individual group efficacy beliefs. Results: Significant effects were reported for both the group characteristics (βswim = 7.86; βbike = 8.57; both p < .001) and the individual group efficacy beliefs (βigeb; .40, p < .001) on performance motivation. The subsequent mediation model indicated that the effects of group characteristics on performance motivation were partly mediated by the individual group efficacy beliefs of the subjects with significant mediation effects for both factors swim and bike. Discussion/Conclusion: The results of the study provide further support for the motivational character of efficacy beliefs and point out a mechanism by which team characteristics influence performance relevant factors at the level of individual team members. The study indicates that high team abilities lead to augmented performance motivation, adding a psychological advantage to teams already high on task relevant abilities. Future investigations will be aiming at possibilities to keep individual performance motivation high in groups with low task relevant abilities. One possibility could be the formulation of individual task goals. References: Anderson, N. H. (1982). Methods of information integration theory. New York: Academic Press. Bandura, A. & Locke, E. A. (2003). Negative self-efficacy and goal effects revisited. Journal of Applied Psychology, 88, 87-99. Cranach, M. von, Ochsenbein, G. & Valach, L. (1986). The group as a self-active system: Outline of a theory of group action. European Journal of Social Psychology, 16, 193-229.

The relation between cognitive and motor performance and their relevance for children’s transition to school: A latent variable approach

Both theoretically and empirically there is a continuous interest in understanding the specific relation between cognitive and motor development in childhood. In the present longitudinal study including three measurement points, this relation was targeted. At the beginning of the study, the participating children were 5-6-year-olds. By assessing participants' fine motor skills, their executive functioning, and their non-verbal intelligence, their cross-sectional and cross-lagged interrelations were examined. Additionally, performance in these three areas was used to predict early school achievement (in terms of mathematics, reading, and spelling) at the end of participants' first grade. Correlational analyses and structural equation modeling revealed that fine motor skills, non-verbal intelligence and executive functioning were significantly interrelated. Both fine motor skills and intelligence had significant links to later school achievement. However, when executive functioning was additionally included into the prediction of early academic achievement, fine motor skills and non-verbal intelligence were no longer significantly associated with later school performance suggesting that executive functioning plays an important role for the motor-cognitive performance link.

Automatic multi-resolution shape modeling of multi-organ structures.

Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.

A fixed-links modeling approach to assess individual differences in the attentional blink: Analysis of behavioral and psychophysiological data

The attentional blink (AB) is a fundamental limitation of the ability to select relevant information from irrelevant information. It can be observed with the detection rate in an AB task as well as with the corresponding P300 amplitude of the event-related potential. In previous research, however, correlations between these two levels of observation were weak and rather inconsistent. A possible explanation of this finding might be that multiple processes underlie the AB and, thus, obscure a possible relationship between AB-related detection rate and the corresponding P300 amplitude. The present study investigated this assumption by applying a fixed-links modeling approach to represent behavioral individual differences in the AB as a latent variable. Concurrently, this approach enabled us to control for additional sources of variance in AB performance by deriving two additional latent variables. The correlation between the latent variable reflecting behavioral individual differences in AB magnitude and a corresponding latent variable derived from the P300 amplitude was high (r=.70). Furthermore, this correlation was considerably stronger than the correlations of other behavioral measures of the AB magnitude with their psychophysiological counterparts (all rs<.40). Our findings clearly indicate that the systematic disentangling of various sources of variance by utilizing the fixed-links modeling approach is a promising tool to investigate behavioral individual differences in the AB and possible psychophysiological correlates of these individual differences.