Electro-cortical correlates of motor inhibition : a comparison between selective and non-selective stop tasks

In this study, we compared a selective stop task (transition from a bimanual in-phase to a unimanual index fingers' tapping), with a non-selective stop task (stopping a bimanual in-phase tapping at all), and with a switching task (transition from in-phase to anti-phase bimanual tapping). The aim was twofold: 1) to identify the electro-cortical correlates of selective and non-selective inhibition processes and 2) to investigate which type of inhibition - selective or not - is required when switching between two bimanual motor patterns. The results revealed that all tasks led to enhanced activation (alpha power) of the left sensorimotor and posterior regions which seems to reflect an overall effort to stop the preferred bimanual in-phase tendency. Each task implied specific functional connectivity reorganizations (beta coherence) between cerebral motor areas, probably reflecting engagement in a new unimanual or bimanual movement.

Central and Cortical Gray Mater Segmentation of Magnetic Resonance Images of the Fetal Brain

Motivation. The study of human brain development in itsearly stage is today possible thanks to in vivo fetalmagnetic resonance imaging (MRI) techniques. Aquantitative analysis of fetal cortical surfacerepresents a new approach which can be used as a markerof the cerebral maturation (as gyration) and also forstudying central nervous system pathologies [1]. However,this quantitative approach is a major challenge forseveral reasons. First, movement of the fetus inside theamniotic cavity requires very fast MRI sequences tominimize motion artifacts, resulting in a poor spatialresolution and/or lower SNR. Second, due to the ongoingmyelination and cortical maturation, the appearance ofthe developing brain differs very much from thehomogenous tissue types found in adults. Third, due tolow resolution, fetal MR images considerably suffer ofpartial volume (PV) effect, sometimes in large areas.Today extensive efforts are made to deal with thereconstruction of high resolution 3D fetal volumes[2,3,4] to cope with intra-volume motion and low SNR.However, few studies exist related to the automatedsegmentation of MR fetal imaging. [5] and [6] work on thesegmentation of specific areas of the fetal brain such asposterior fossa, brainstem or germinal matrix. Firstattempt for automated brain tissue segmentation has beenpresented in [7] and in our previous work [8]. Bothmethods apply the Expectation-Maximization Markov RandomField (EM-MRF) framework but contrary to [7] we do notneed from any anatomical atlas prior. Data set &Methods. Prenatal MR imaging was performed with a 1-Tsystem (GE Medical Systems, Milwaukee) using single shotfast spin echo (ssFSE) sequences (TR 7000 ms, TE 180 ms,FOV 40 x 40 cm, slice thickness 5.4mm, in plane spatialresolution 1.09mm). Each fetus has 6 axial volumes(around 15 slices per volume), each of them acquired inabout 1 min. Each volume is shifted by 1 mm with respectto the previous one. Gestational age (GA) ranges from 29to 32 weeks. Mother is under sedation. Each volume ismanually segmented to extract fetal brain fromsurrounding maternal tissues. Then, in-homogeneityintensity correction is performed using [9] and linearintensity normalization is performed to have intensityvalues that range from 0 to 255. Note that due tointra-tissue variability of developing brain someintensity variability still remains. For each fetus, ahigh spatial resolution image of isotropic voxel size of1.09 mm is created applying [2] and using B-splines forthe scattered data interpolation [10] (see Fig. 1). Then,basal ganglia (BS) segmentation is performed on thissuper reconstructed volume. Active contour framework witha Level Set (LS) implementation is used. Our LS follows aslightly different formulation from well-known Chan-Vese[11] formulation. In our case, the LS evolves forcing themean of the inside of the curve to be the mean intensityof basal ganglia. Moreover, we add local spatial priorthrough a probabilistic map created by fitting anellipsoid onto the basal ganglia region. Some userinteraction is needed to set the mean intensity of BG(green dots in Fig. 2) and the initial fitting points forthe probabilistic prior map (blue points in Fig. 2). Oncebasal ganglia are removed from the image, brain tissuesegmentation is performed as described in [8]. Results.The case study presented here has 29 weeks of GA. Thehigh resolution reconstructed volume is presented in Fig.1. The steps of BG segmentation are shown in Fig. 2.Overlap in comparison with manual segmentation isquantified by the Dice similarity index (DSI) equal to0.829 (values above 0.7 are considered a very goodagreement). Such BG segmentation has been applied on 3other subjects ranging for 29 to 32 GA and the DSI hasbeen of 0.856, 0.794 and 0.785. Our segmentation of theinner (red and blue contours) and outer cortical surface(green contour) is presented in Fig. 3. Finally, torefine the results we include our WM segmentation in theFreesurfer software [12] and some manual corrections toobtain Fig.4. Discussion. Precise cortical surfaceextraction of fetal brain is needed for quantitativestudies of early human brain development. Our workcombines the well known statistical classificationframework with the active contour segmentation forcentral gray mater extraction. A main advantage of thepresented procedure for fetal brain surface extraction isthat we do not include any spatial prior coming fromanatomical atlases. The results presented here arepreliminary but promising. Our efforts are now in testingsuch approach on a wider range of gestational ages thatwe will include in the final version of this work andstudying as well its generalization to different scannersand different type of MRI sequences. References. [1]Guibaud, Prenatal Diagnosis 29(4) (2009). [2] Rousseau,Acad. Rad. 13(9), 2006, [3] Jiang, IEEE TMI 2007. [4]Warfield IADB, MICCAI 2009. [5] Claude, IEEE Trans. Bio.Eng. 51(4) (2004). [6] Habas, MICCAI (Pt. 1) 2008. [7]Bertelsen, ISMRM 2009 [8] Bach Cuadra, IADB, MICCAI 2009.[9] Styner, IEEE TMI 19(39 (2000). [10] Lee, IEEE Trans.Visual. And Comp. Graph. 3(3), 1997, [11] Chan, IEEETrans. Img. Proc, 10(2), 2001 [12] Freesurfer,http://surfer.nmr.mgh.harvard.edu.

Semi-supervised segmentation of ultrasound images based on patch representation and continuous min cut.

Ultrasound segmentation is a challenging problem due to the inherent speckle and some artifacts like shadows, attenuation and signal dropout. Existing methods need to include strong priors like shape priors or analytical intensity models to succeed in the segmentation. However, such priors tend to limit these methods to a specific target or imaging settings, and they are not always applicable to pathological cases. This work introduces a semi-supervised segmentation framework for ultrasound imaging that alleviates the limitation of fully automatic segmentation, that is, it is applicable to any kind of target and imaging settings. Our methodology uses a graph of image patches to represent the ultrasound image and user-assisted initialization with labels, which acts as soft priors. The segmentation problem is formulated as a continuous minimum cut problem and solved with an efficient optimization algorithm. We validate our segmentation framework on clinical ultrasound imaging (prostate, fetus, and tumors of the liver and eye). We obtain high similarity agreement with the ground truth provided by medical expert delineations in all applications (94% DICE values in average) and the proposed algorithm performs favorably with the literature.

Neues aus Diagnostik und Therapie der spinalen Erkrankungen [Novel aspects of diagnostics and therapy of spinal cord diseases].

BACKGROUND: Both non-traumatic and traumatic spinal cord injuries have in common that a relatively minor structural lesion can cause profound sensorimotor and autonomous dysfunction. Besides treating the cause of the spinal cord injury the main goal is to restore lost function as far as possible. AIM: This article provides an overview of current innovative diagnostic (imaging) and therapeutic approaches (neurorehabilitation and neuroregeneration) aiming for recovery of function after non-traumatic and traumatic spinal cord injuries. MATERIAL AND METHODS: An analysis of the current scientific literature regarding imaging, rehabilitation and rehabilitation strategies in spinal cord disease was carried out. RESULTS: Novel magnetic resonance imaging (MRI) based techniques (e.g. diffusion-weighted MRI and functional MRI) allow visualization of structural reorganization and specific neural activity in the spinal cord. Robotics-driven rehabilitative measures provide training of sensorimotor function in a targeted fashion, which can even be continued in the homecare setting. From a preclinical point of view, defined stem cell transplantation approaches allow for the first time robust structural repair of the injured spinal cord. CONCLUSION: Besides well-established neurological and functional scores, MRI techniques offer the unique opportunity to provide robust and reliable "biomarkers" for restorative therapeutic interventions. Function-oriented robotics-based rehabilitative interventions alone or in combination with stem cell based therapies represent promising approaches to achieve substantial functional recovery, which go beyond current rehabilitative treatment efforts.

Comparing Multilevel Clustering Methods on Weighted Graphs : The Case of Worldwide Air Passenger Traffic 2000-2004

Specific properties emerge from the structure of large networks, such as that of worldwide air traffic, including a highly hierarchical node structure and multi-level small world sub-groups that strongly influence future dynamics. We have developed clustering methods to understand the form of these structures, to identify structural properties, and to evaluate the effects of these properties. Graph clustering methods are often constructed from different components: a metric, a clustering index, and a modularity measure to assess the quality of a clustering method. To understand the impact of each of these components on the clustering method, we explore and compare different combinations. These different combinations are used to compare multilevel clustering methods to delineate the effects of geographical distance, hubs, network densities, and bridges on worldwide air passenger traffic. The ultimate goal of this methodological research is to demonstrate evidence of combined effects in the development of an air traffic network. In fact, the network can be divided into different levels of âeurooecohesionâeuro, which can be qualified and measured by comparative studies (Newman, 2002; Guimera et al., 2005; Sales-Pardo et al., 2007).

Structural Analysis of Networks

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

D-JNKi, a peptide inhibitor of c-Jun N-terminal kinase, promotes functional recovery after transient focal cerebral ischemia in rats

The c-Jun-N-terminal kinase (JNK) pathway has been shown to play an important role in excitotoxic neuronal death and several studies have demonstrated a neuroprotective effect of D-JNKi, a peptide inhibitor of JNK, in various models of cerebral ischemia. We have now investigated the effect of D-JNKi in a model of transient focal cerebral ischemia (90 min) induced by middle cerebral artery occlusion (MCAo) in adult male rats. D-JNKi (0.1 mg/kg), significantly decreased the volume of infarct, 3 days after cerebral ischemia. Sensorimotor and cognitive deficits were then evaluated over a period of 6 or 10 days after ischemia and infarct volumes were measured after behavioral testing. In behavioral studies, D-JNKi improved the general state of the animals as demonstrated by the attenuation of body weight loss and improvement in neurological score, as compared with animals receiving the vehicle. Moreover, D-JNKi decreased sensorimotor deficits in the adhesive removal test and improved cognitive function in the object recognition test. In contrast, D-JNKi did not significantly affect the infarct volume at day 6 and at day 10. This study shows that D-JNKi can improve functional recovery after transient focal cerebral ischemia in the rat and therefore supports the use of this molecule as a potential therapy for stroke.

Cerebellar transcranial direct current stimulation modulates verbal working memory.

BACKGROUND: Neuroimaging studies show cerebellar activations in a wide range of cognitive tasks and patients with cerebellar lesions often present cognitive deficits suggesting a cerebellar role in higher-order cognition. OBJECTIVE: We used cathodal transcranial direct current stimulation (tDCS), known to inhibit neuronal excitability, over the cerebellum to investigate if cathodal tDCS impairs verbal working memory, an important higher-order cognitive faculty. METHOD: We tested verbal working memory as measured by forward and backward digit spans in 40 healthy young participants before and after applying cathodal tDCS (2 mA, stimulation duration 25 min) to the right cerebellum using a randomized, sham-controlled, double-blind, cross-over design. In addition, we tested the effect of cerebellar tDCS on word reading, finger tapping and a visually cued sensorimotor task. RESULTS: In line with lower digit spans in patients with cerebellar lesions, cerebellar tDCS reduced forward digit spans and blocked the practice dependent increase in backward digit spans. No effects of tDCS on word reading, finger tapping or the visually cued sensorimotor task were found. CONCLUSION: Our results support the view that the cerebellum contributes to verbal working memory as measured by forward and backward digit spans. Moreover, the induction of reversible "virtual cerebellar lesions" in healthy individuals by means of tDCS may improve our understanding of the mechanistic basis of verbal working memory deficits in patients with cerebellar lesions.

BOLD responses to trigeminal nerve stimulation.

The current study investigates a new model of barrel cortex activation using stimulation of the infraorbital branch of the trigeminal nerve. A robust and reproducible activation of the rat barrel cortex was obtained following trigeminal nerve stimulation. Blood oxygen level-dependent (BOLD) effects were obtained in the primary somatosensory barrel cortex (S1BF), the secondary somatosensory cortex (S2) and the motor cortex. These cortical areas were reached from afferent pathways from the trigeminal ganglion, the trigeminal nuclei and thalamic nuclei from which neurons project their axons upon whisker stimulation. The maximum BOLD responses were obtained for a stimulus frequency of 1 Hz, a stimulus pulse width of 100 μs and for current intensities between 1.5 and 3 mA. The BOLD response was nonlinear as a function of frequency and current intensity. Additionally, modeling BOLD responses in the rat barrel cortex from separate cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO(2)) measurements showed good agreement with the shape and amplitude of measured BOLD responses as a function of stimulus frequency and will potentially allow to identify the sources of BOLD nonlinearities. Activation of the rat barrel cortex using trigeminal nerve stimulation will contribute to the interpretation of the BOLD signals from functional magnetic resonance imaging studies.

Quantifying network properties in multi-electrode recordings: spatiotemporal characterization and inter-trial variation of evoked gamma oscillations in mouse somatosensory cortex in vitro.

Linking the structural connectivity of brain circuits to their cooperative dynamics and emergent functions is a central aim of neuroscience research. Graph theory has recently been applied to study the structure-function relationship of networks, where dynamical similarity of different nodes has been turned into a "static" functional connection. However, the capability of the brain to adapt, learn and process external stimuli requires a constant dynamical functional rewiring between circuitries and cell assemblies. Hence, we must capture the changes of network functional connectivity over time. Multi-electrode array data present a unique challenge within this framework. We study the dynamics of gamma oscillations in acute slices of the somatosensory cortex from juvenile mice recorded by planar multi-electrode arrays. Bursts of gamma oscillatory activity lasting a few hundred milliseconds could be initiated only by brief trains of electrical stimulations applied at the deepest cortical layers and simultaneously delivered at multiple locations. Local field potentials were used to study the spatio-temporal properties and the instantaneous synchronization profile of the gamma oscillatory activity, combined with current source density (CSD) analysis. Pair-wise differences in the oscillation phase were used to determine the presence of instantaneous synchronization between the different sites of the circuitry during the oscillatory period. Despite variation in the duration of the oscillatory response over successive trials, they showed a constant average power, suggesting that the rate of expenditure of energy during the gamma bursts is consistent across repeated stimulations. Within each gamma burst, the functional connectivity map reflected the columnar organization of the neocortex. Over successive trials, an apparently random rearrangement of the functional connectivity was observed, with a more stable columnar than horizontal organization. This work reveals new features of evoked gamma oscillations in developing cortex.

Real-time antifungal susceptibility testing of Mucor spp., Fusarium spp. and Scedosporium spp. by isothermal microcalorimetry

Objective: Aspergillus species are the main pathogens causing invasive fungal infections but the prevalence of other mould species is rising. Resistance to antifungals among these new emerging pathogens presents a challenge for managing of infections. Conventional susceptibility testing of non-Aspergillus species is laborious and often difficult to interpret. We evaluated a new method for real-time susceptibility testing of moulds based on their of growth-related heat production.Methods: Laboratory and clinical strains of Mucor spp. (n = 4), Scedoporium spp. (n = 4) and Fusarium spp. (n = 5) were used. Conventional MIC was determined by microbroth dilution. Isothermal microcalorimetry was performed at 37 C using Sabouraud dextrose broth (SDB) inoculated with 104 spores/ml (determined by microscopical enumeration). SDB without antifungals was used for evaluation of growth characteristics. Detection time was defined as heat flow exceeding 10 lW. For susceptibility testing serial dilutions of amphotericin B, voriconazole, posaconazole and caspofungin were used. The minimal heat inhibitory concentration (MHIC) was defined as the lowest antifungal concentration, inhbiting 50% of the heat produced by the growth control at 48 h or at 24 h for Mucor spp. Susceptibility tests were performed in duplicate.Results: Tested mould genera had distinctive heat flow profiles with a median detection time (range) of 3.4 h (1.9-4.1 h) for Mucor spp, 11.0 h (7.1-13.7 h) for Fusarium spp and 29.3 h (27.4-33.0 h) for Scedosporium spp. Graph shows heat flow (in duplicate) of one representative strain from each genus (dashed line marks detection limit). Species belonging to the same genus showed similar heat production profiles. Table shows MHIC and MIC ranges for tested moulds and antifungals.Conclusions: Microcalorimetry allowed rapid detection of growth of slow-growing species, such as Fusarium spp. and Scedosporium spp. Moreover, microcalorimetry offers a new approach for antifungal susceptibility testing of moulds, correlating with conventional MIC values. Interpretation of calorimetric susceptibility data is easy and real-time data on the effect of different antifungals on the growth of the moulds is additionally obtained. This method may be used for investigation of different mechanisms of action of antifungals, new substances and drug-drug combinations.

Llenguatges de consulta per documents RDF

Els objectius principals d'aquest projecte són analitzar i descartar algunes dels llenguatges de consulta, gestors relacionals i reposadors que s'estan utilitzant més habitualment en l'entorn de la Web Semàntica. Amb l'estudi de les principals tecnologies implicades en la Web Semàntica es tractarà de realitzar una aplicació que permeti el maneig de dades d'un graf RDF.

Anatomical correlates for category-specific naming of objects and actions: A brain stimulation mapping study.

The production of object and action words can be dissociated in aphasics, yet their anatomical correlates have been difficult to distinguish in functional imaging studies. To investigate the extent to which the cortical neural networks underlying object- and action-naming processing overlap, we performed electrostimulation mapping (ESM), which is a neurosurgical mapping technique routinely used to examine language function during brain-tumor resections. Forty-one right-handed patients who had surgery for a brain tumor were asked to perform overt naming of object and action pictures under stimulation. Overall, 73 out of the 633 stimulated cortical sites (11.5%) were associated with stimulation-induced language interferences. These interference sites were very much localized (<1 cm(2) ), and showed substantial variability across individuals in their exact localization. Stimulation interfered with both object and action naming over 44 sites, whereas it specifically interfered with object naming over 19 sites and with action naming over 10 sites. Specific object-naming sites were mainly identified in Broca's area (Brodmann area 44/45) and the temporal cortex, whereas action-naming specific sites were mainly identified in the posterior midfrontal gyrus (Brodmann area 6/9) and Broca's area (P = 0.003 by the Fisher's exact test). The anatomical loci we emphasized are in line with a cortical distinction between objects and actions based on conceptual/semantic features, so the prefrontal/premotor cortex would preferentially support sensorimotor contingencies associated with actions, whereas the temporal cortex would preferentially underpin (functional) properties of objects. Hum Brain Mapp 35:429-443, 2014. © 2012 Wiley Periodicals, Inc.

Hardy-Weinberg Equilibrium and the Ternary Plot

The Hardy-Weinberg law, formulated about 100 years ago, states that under certainassumptions, the three genotypes AA, AB and BB at a bi-allelic locus are expected to occur inthe proportions p2, 2pq, and q2 respectively, where p is the allele frequency of A, and q = 1-p.There are many statistical tests being used to check whether empirical marker data obeys theHardy-Weinberg principle. Among these are the classical xi-square test (with or withoutcontinuity correction), the likelihood ratio test, Fisher's Exact test, and exact tests in combinationwith Monte Carlo and Markov Chain algorithms. Tests for Hardy-Weinberg equilibrium (HWE)are numerical in nature, requiring the computation of a test statistic and a p-value.There is however, ample space for the use of graphics in HWE tests, in particular for the ternaryplot. Nowadays, many genetical studies are using genetical markers known as SingleNucleotide Polymorphisms (SNPs). SNP data comes in the form of counts, but from the countsone typically computes genotype frequencies and allele frequencies. These frequencies satisfythe unit-sum constraint, and their analysis therefore falls within the realm of compositional dataanalysis (Aitchison, 1986). SNPs are usually bi-allelic, which implies that the genotypefrequencies can be adequately represented in a ternary plot. Compositions that are in exactHWE describe a parabola in the ternary plot. Compositions for which HWE cannot be rejected ina statistical test are typically “close" to the parabola, whereas compositions that differsignificantly from HWE are “far". By rewriting the statistics used to test for HWE in terms ofheterozygote frequencies, acceptance regions for HWE can be obtained that can be depicted inthe ternary plot. This way, compositions can be tested for HWE purely on the basis of theirposition in the ternary plot (Graffelman & Morales, 2008). This leads to nice graphicalrepresentations where large numbers of SNPs can be tested for HWE in a single graph. Severalexamples of graphical tests for HWE (implemented in R software), will be shown, using SNPdata from different human populations

Continuous monitoring of cerebrovascular pressure reactivity in patients with head injury.

OBJECT: Cerebrovascular pressure reactivity is the ability of cerebral vessels to respond to changes in transmural pressure. A cerebrovascular pressure reactivity index (PRx) can be determined as the moving correlation coefficient between mean intracranial pressure (ICP) and mean arterial blood pressure. METHODS: The authors analyzed a database consisting of 398 patients with head injuries who underwent continuous monitoring of cerebrovascular pressure reactivity. In 298 patients, the PRx was compared with a transcranial Doppler ultrasonography assessment of cerebrovascular autoregulation (the mean index [Mx]), in 17 patients with the PET-assessed static rate of autoregulation, and in 22 patients with the cerebral metabolic rate for O(2). Patient outcome was assessed 6 months after injury. RESULTS: There was a positive and significant association between the PRx and Mx (R(2) = 0.36, p < 0.001) and with the static rate of autoregulation (R(2) = 0.31, p = 0.02). A PRx > 0.35 was associated with a high mortality rate (> 50%). The PRx showed significant deterioration in refractory intracranial hypertension, was correlated with outcome, and was able to differentiate patients with good outcome, moderate disability, severe disability, and death. The graph of PRx compared with cerebral perfusion pressure (CPP) indicated a U-shaped curve, suggesting that too low and too high CPP was associated with a disturbance in pressure reactivity. Such an optimal CPP was confirmed in individual cases and a greater difference between current and optimal CPP was associated with worse outcome (for patients who, on average, were treated below optimal CPP [R(2) = 0.53, p < 0.001] and for patients whose mean CPP was above optimal CPP [R(2) = -0.40, p < 0.05]). Following decompressive craniectomy, pressure reactivity initially worsened (median -0.03 [interquartile range -0.13 to 0.06] to 0.14 [interquartile range 0.12-0.22]; p < 0.01) and improved in the later postoperative course. After therapeutic hypothermia, in 17 (70.8%) of 24 patients in whom rewarming exceeded the brain temperature threshold of 37 degrees C, ICP remained stable, but the average PRx increased to 0.32 (p < 0.0001), indicating significant derangement in cerebrovascular reactivity. CONCLUSIONS: The PRx is a secondary index derived from changes in ICP and arterial blood pressure and can be used as a surrogate marker of cerebrovascular impairment. In view of an autoregulation-guided CPP therapy, a continuous determination of a PRx is feasible, but its value has to be evaluated in a prospective controlled trial.