Source modeling of ElectroCorticoGraphy (ECoG) data: Stability analysis and spatial filtering.

BACKGROUND: Electrocorticography (ECoG) measures the distribution of the electrical potentials on the cortex produced by the neural currents. A full interpretation of ECoG data requires solving the ill-posed inverse problem of reconstructing the spatio-temporal distribution of the neural currents. This study addresses the ECoG source modeling developing a beamformer method. NEW METHOD: We computed the lead-field matrix by using a novel routine provided by the OpenMEEG software. We performed an analysis of the numerical stability of the ECoG inverse problem by computing the condition number of the lead-field matrix for different configurations of the electrodes grid. We applied a Linear Constraint Minimum Variance (LCMV) beamformer to both synthetic data and a set of real measurements recorded during a rapid visual categorization task. RESULTS: For all considered grids the condition number indicates that the ECoG inverse problem is mildly ill-conditioned. For realistic SNR we found a good performance of the LCMV algorithm for both localization and waveforms reconstruction. COMPARISON WITH EXISTING METHOD: The flow of information reconstructed by analyzing real data seems consistent with both invasive monkey electrophysiology studies and non-invasive (MEG and fMRI) human studies. CONCLUSIONS: Despite a growing interest from the neuroscientific community, solving the ECoG inverse problem has not quite yet reached the level of systematicity found for EEG and MEG. Starting from an analysis of the numerical stability of the problem we considered the most widely utilized method for modeling neurophysiological data based on the beamformer method in the hope to establish benchmarks for future studies.

[Biometric and biomechanic analysis of lumbar posterior facets based on a CT-scan database]. / Analyse biométrique et biomécanique des articulaires lombaires postérieures au sein d'une base de données scanographique.

AIM OF THE STUDY: Our knowledge on anatomy of lumbar spine is based on few cadaver's study with old and few subjects. CT-scan is very precise for lumbar facet's morphology. We have analysed 400 subjects. The aim of this study is to measure different distances, angles and circles to better understand the mechanical function of the lumbar facets. PATIENTS AND METHODS: We have analysed 720 CT-scan. We had 217 men and 183 women with 59 years of mean age. We used native slices of 1.25 mm thick from L1 to S1. We created transversal plan and we put different mark point. We took their coordinates and we have calculated different distances, angles and mechanical circles. We have compared different axis of rotation of the facets. RESULTS: From L1 to S1, the facets goes near to the posterior wall and far from themselves. Moreover, the posterior angle between both facets increase down to the sacrum. The radius of the left side circle and the right one are very closed in 50% of the cases but the three radius are close only in 10% of cases. CONCLUSION: This study based on 400 subjects shows that there is not a unique axis of rotation for both lumbar posterior facets. We have had only 50% of symmetry between both sides whatever the level studied.

Liver injuries in frontal crash situations a coupled numerical - experimental approach.

From clinical knowledge, it has been established that hepatic traumas frequently lead to lethal injuries. In frontal or lateral crash situations, these injuries can be induced by pure deceleration effects or blunt trauma due to belt or steering wheel impact. Concerning the liver under frontal decelerations, how could one investigate organ behaviour leading to the injury mechanisms? This work couples experimental organ decelerations measurements (with 19 tests on cadaver trunks) and finite element simulation, provides a first analysis of the liver behaviour within the abdomen. It shows the influence of the liver attachment system that leads to liver trauma and also torsion effects between the two lobes of the liver. Injury mechanisms were evaluated through the four phases of the liver kinematics under frontal impact: (1) postero-anterior translation, (2) compression and sagittal rotation, (3) rotation in the transverse plane and (4) relaxation.

A human model for road safety: from geometrical acquisition to model validation with radioss.

In order to investigate injury mechanisms, and to provide directions for road safety system improvements, the HUMOS project has lead to the development of a 3D finite element model of the human body in driving position. The model geometry was obtained from a 50th percentile adult male. It includes the description of all compact and trabecular bones, ligaments, tendons, skin, muscles and internal organs. Material properties were based on literature data and specific experiments performed for the project. The validation of the HUMOS model was first achieved on isolated segments and then on the whole model in both frontal and lateral impact situations. HUMOS responses were in good agreement with the experimental data used in the model validation and offers now a wide range of applications from crash simulation, optimization of safety systems, to biomedical and ergonomics.

The seated man: geometry acquisition and three-dimensional reconstruction.

A three-dimensional (3D) virtual human body in seated position can be used in a wide range of applications such as basic or clinical research. A male cadaver placed in the driving position in a car cockpit was frozen. Strictly parallel 5 mm thickness serial sections were then performed. Both sides of the slices were photographed, scanned and analyzed by anatomists with software tools, in order to produce accurate contours of the identified anatomical structures. A 3D reconstruction of organs, based on the marching cubes method, was achieved except for thin structures. This allowed an anatomical validation of these reconstructed elements. The result of this work is a complete geometrical database of a seated human body in the driving position including skin, all bones, internal organs and main muscle groups.