Brain areas involved in medial temporal lobe seizures: a principal component analysis of ictal SPECT data

The study describes brain areas involved in medial temporal lobe (mTL) seizures of 12 patients. All patients showed so-called oro-alimentary behavior within the first 20 s of clinical seizure manifestation characteristic of mTL seizures. Single photon emission computed tomography (SPECT) images of regional cerebral blood flow (rCBF) were acquired from the patients in ictal and interictal phases and from normal volunteers. Image analysis employed categorical comparisons with statistical parametric mapping and principal component analysis (PCA) to assess functional connectivity. PCA supplemented the findings of the categorical analysis by decomposing the covariance matrix containing images of patients and healthy subjects into distinct component images of independent variance, including areas not identified by the categorical analysis. Two principal components (PCs) discriminated the subject groups: patients with right or left mTL seizures and normal volunteers, indicating distinct neuronal networks implicated by the seizure. Both PCs were correlated with seizure duration, one positively and the other negatively, confirming their physiological significance. The independence of the two PCs yielded a clear clustering of subject groups. The local pattern within the temporal lobe describes critical relay nodes which are the counterpart of oro-alimentary behavior: (1) right mesial temporal zone and ipsilateral anterior insula in right mTL seizures, and (2) temporal poles on both sides that are densely interconnected by the anterior commissure. Regions remote from the temporal lobe may be related to seizure propagation and include positively and negatively loaded areas. These patterns, the covarying areas of the temporal pole and occipito-basal visual association cortices, for example, are related to known anatomic paths.

Statistical shape analysis via principal factor analysis

Statistical shape analysis techniques commonly employed in the medical imaging community, such as active shape models or active appearance models, rely on principal component analysis (PCA) to decompose shape variability into a reduced set of interpretable components. In this paper we propose principal factor analysis (PFA) as an alternative and complementary tool to PCA providing a decomposition into modes of variation that can be more easily interpretable, while still being a linear efficient technique that performs dimensionality reduction (as opposed to independent component analysis, ICA). The key difference between PFA and PCA is that PFA models covariance between variables, rather than the total variance in the data. The added value of PFA is illustrated on 2D landmark data of corpora callosa outlines. Then, a study of the 3D shape variability of the human left femur is performed. Finally, we report results on vector-valued 3D deformation fields resulting from non-rigid registration of ventricles in MRI of the brain.

Comparison of partial least squares regression and principal component regression for pelvic shape prediction.

This paper studied two different regression techniques for pelvic shape prediction, i.e., the partial least square regression (PLSR) and the principal component regression (PCR). Three different predictors such as surface landmarks, morphological parameters, or surface models of neighboring structures were used in a cross-validation study to predict the pelvic shape. Results obtained from applying these two different regression techniques were compared to the population mean model. In almost all the prediction experiments, both regression techniques unanimously generated better results than the population mean model, while the difference on prediction accuracy between these two regression methods is not statistically significant (α=0.01).

Principal-Agent Theory and the World Trade Organization: Complex Agency and ‘Missing Delegation’

This paper analyses the World Trade Organization within a principal-agent framework. The concept of complex agency is introduced to focus on the variety of actors that comprise an international organization. Special attention is paid to the relationship between contracting parties’ representatives and the Secretariat. In the empirical part, the paper analyses the role of the Secretariat in assisting negotiations and presents evidence of declining influence. It is shown how principal-agent theory can contribute to addressing this ‘puzzle of missing delegation’. The paper concludes with a cautionary note as to the ‘location’ of international organizations’ emerging pathologies and calls for additional research to address the relationship between material and social sources to explain behaviour of the key actors within the complex agency.

Hohlraum Target for Overcoming Refractive Losses in Plasma X-ray Lasers

Refractive losses in laser-produced plasmas used as gain media are caused by electron density gradients, and limit the energy transport range. The pump pulse is thus deflected from the high-gain region and the short wavelength laser signal also steers away, causing loss of collimation. A Hohlraum used as a target makes the plasma homogeneous and can mitigate refractive losses by means of wave-guiding. A computational study combining a hydrodynamics code and an atomic physics code is presented, which includes a ray-tracing modeling based on the eikonal theory of the trajectory equation. This study presents gain calculations based on population inversion produced by free-electron collisions exciting bound electrons into metastable levels in the 3d94d1(J = 0) → 3d94p1(J = 1) transition of Ni-like Sn. Further, the Hohlraum suggests a dramatic enhancement of the conversion efficiency of collisionally excited x-ray lasing for Ni-like Sn.

Relative indexes of cutaneous blood perfusion measured by real-time laser Doppler imaging (LDI) in healthy volunteers.

We used real-time LDI to study regional variations in microcirculatory perfusion in healthy candidates to establish a new methodology for global perfusion body mapping that is based on intra-individual perfusion index ratios. Our study included 74 (37 female) healthy volunteers aged between 22 and 30 years (mean 24.49). Imaging was performed using a recent microcirculation-imaging camera (EasyLDI) for different body regions of each volunteer. The perfusion values were reported in Arbitrary Perfusion Units (APU). The relative perfusion indexes for each candidate's body region were then obtained by normalization with the perfusion value of the forehead. Basic parameters such as weight, height, and blood pressure were also measured and analyzed. The highest mean perfusion value was reported in the forehead area (259.21APU). Mean perfusion in the measured parts of the body correlated positively with mean forehead value, while there was no significant correlation between forehead blood perfusion values and room temperature, BMI, systolic blood pressure and diastolic blood pressure (p=0.420, 0.623, 0.488, 0.099, respectively). Analysis of the data showed that perfusion indexes were not significantly different between male and female volunteers except for the ventral upper arm area (p=.001). LDI is a non-invasive, fast technique that opens several avenues for clinical applications. The mean perfusion indexes are useful in clinical practice for monitoring patients before and after surgical interventions. Perfusion values can be predicted for different body parts for patients only by taking the forehead perfusion value and using the perfusion index ratios to obtain expected normative perfusion values.