Corticobulbar Tract Injury, Oromotor Impairment and Language Plasticity in Adolescents Born Preterm

Children born preterm are at risk of impairments in oromotor control, with implications for early feeding and speech development. In this study, we aimed to identify (a) neuroanatomical markers of persistent oromotor deficits using diffusion-weighted imaging (DWI) tractography and (b) evidence of compensatory neuroplasticity using functional MRI (fMRI) during a language production task. In a cross-sectional study of 36 adolescents born very preterm (<33 weeks’ gestation) we identified persistent difficulties in oromotor control in 31% of cases, but no clinical diagnoses of speech-sound disorder (e.g., dysarthria, dyspraxia). We used DWI-tractography to examine the microstructure (fractional anisotropy, FA) of the corticospinal and corticobulbar tracts. Compared to the unimpaired group, the oromotor-impaired group showed (i) reduced FA within the dorsal portion of the left corticobulbar tract (containing fibres associated with movements of the lips, tongue, and larynx) and (ii) greater recruitment of right hemisphere language regions on fMRI. We conclude that, despite the development of apparently normal everyday speech, early injury to the corticobulbar tract leads to persistent subclinical problems with voluntary control of the face, lips, jaw, and tongue. Furthermore, we speculate that early speech problems may be ameliorated by cerebral plasticity – in particular, recruitment of right hemisphere language areas

Study of the rheological behavior of chocolate

info:eu-repo/semantics/publishe

Single-phase flow model development for macro mixing evaluation in an aerated tank, by computational fluid dynamics

info:eu-repo/semantics/inPres

An open-source toolbox for Multi-patient Intracranial EEG Analysis (MIA)

Intracranial EEG (iEEG) performed during the pre-surgical evaluation of refractory epilepsy provides a great opportunity to investigate the neurophysiology of human cognitive functions with exceptional spatial and temporal precisions. A difficulty of the iEEG approach for cognitive neuroscience, however, is the potential variability across patients in the anatomical location of implantations and in the functional responses that are recorded. In this context, we designed, implemented, and tested a user-friendly and efficient open-source toolbox for Multi-Patient Intracranial data Analysis (MIA), which can be used as standalone program or as a Brainstorm plugin. MIA helps analyzing iEEG signals while following good scientific practice recommendations, such as building reproducible analysis pipelines and applying robust statistics. The signals can be analyzed in the temporal and time-frequency domains, and the similarity of time courses across patients or contacts can be assessed within anatomical regions. MIA allows visualizing all these results in a variety of formats at every step of the analysis. Here we present the toolbox architecture and illustrate the different steps and features of the analysis pipeline using a group dataset collected during a language task

Study of the rheological behavior of chocolate and margarine

In the food industry, the production process is often established in an empirical way, according to rules of good practice. These methods present gaps, in particular at the level of the production regularity. To model and optimize the processes, it is highly useful to determine the physico-chemical properties of the product. In this work, chocolate and margarine are studied, both aiming direct industrial application but also aiming a general enhancement of rheological mechanism understanding. Indeed, the chocolate is a suspension of solid particles in cocoa butter and the margarine is a water-in-oil emulsion. Rheological behavior of those fluids is therefore relying on different key phenomena. In this work the flow behavior of both products is characterized and a mathematical model describing the rheological behavior of chocolate is developed. For chocolate, the goal is to model the tempering process. To establish the rheological behavior of chocolate, viscosity measurements were realized in a SEARLE VT550 viscometer using a bob and cup geometry. To build the mathematical law, general tests following the International Office of Cocoa, Chocolate and Sugar Confectionery (IOCCC) recommended method (Servais et al. 2004) were performed. The obtained rheogram shows that the chocolate has a slightly thixotropic behavior. More focus is set on a smaller range of shear rate important for the industrial application (Debaste et al. 2008). Measures for various temperatures and various quantities of cocoa butter were realized. The results show a classical shear-thinning behavior. Further, a statistical analysis of the results was made to determine the parameters of a power-law describing this behavior. It appears that temperature and cocoa butter fraction have no influence on the exponent but well on the consistency parameter. For margarine, the goal is to model the flow in resting tubes, the last step in the industrial production (Herman et al. 2008). To determine the rheological behavior of the margarine two kinds of devices were used. First the SEARLE VT550 viscometer with a four blades impeller was used. And the results were not satisfying because the measured viscosity was often nulls. We suppose that the sample was broken into two blocks, one between the blades of the impeller and a second outside of the impeller. A HAAK MARS rheometer with a plate-plate geometry was also used. In both experiments we evaluate how a change of 1°C can affect the viscosity of margarine. The obtained flow curves show that the margarine has a plastic and thixotropic behavior and that a variation of 1°C affects margarine's rheology. With the chocolate rheological law, the perspective is to get a general model for concentrated suspensions. And for margarine, more measures with an adapted viscometer should be done to build a model.info:eu-repo/semantics/publishe

An open-source toolbox for Multi-patient Intracranial EEG Analysis (MIA)

International audienceIntracranial EEG (iEEG) performed during the pre-surgical evaluation of refractory epilepsy provides a great opportunity to investigate the neurophysiology of human cognitive functions with exceptional spatial and temporal precisions. A difficulty of the iEEG approach for cognitive neuroscience, however, is the potential variability across patients in the anatomical location of implantations and in the functional responses therein recorded. In this context, we designed, implemented, and tested a userfriendly and efficient open-source toolbox for Multi-Patient Intracranial data Analysis (MIA), which can be used as standalone program or as a Brainstorm plugin. MIA helps analyzing event related iEEG signals while following good scientific practice recommendations, such as building reproducible analysis pipelines and applying robust statistics. The signals can be analyzed in the temporal and timefrequency domains, and the similarity of time courses across patients or contacts can be assessed within anatomical regions. MIA allows visualizing all these results in a variety of formats at every step of the analysis. Here, we present the toolbox architecture and illustrate the different steps and features of the analysis pipeline using a group dataset collected during a language task