Chronic metal contamination shapes the size structure of Gammarus fossarum populations in French headwater rivers.

Assessing the effects of multigenerational exposure of aquatic animal populations to chemical contamination is essential for ecological risk assessment. However, beyond rare examples reporting the sporadic emergence of a toxicological tolerance within populations that persist in contaminated environments, conclusive results are even more limited from field studies when it comes to the alteration of life-history traits. Here, we investigated whether long-term exposure to cadmium (Cd) influences size-related life-history traits (i.e., size at puberty, median adult size, maximum size) in Gammarus fossarum, a keystone species of European stream ecosystems. We studied 13 field populations of G. fossarum (cryptic lineage B) living in headwater rivers located in natural areas scattered at a large geographical scale and exposed to contrasted bioavailable Cd contamination levels due to different local geochemical backgrounds. We achieved a detailed description of the physical and physicochemical conditions of the river reaches investigated. Land-use parameters, hydrological characteristics (flow, slope, river width, flow structure, mosaic of substrates), and physicochemical conditions (temperature, conductivity, dissolved oxygen) were measured. Metallic bioavailable contamination was assessed using a standardized active biomonitoring procedure (Gammarus caging). Based on the field demographic census of the 13 populations, our results demonstrated that chronic Cd contamination significantly influences life-history in the G. fossarum species, with a significant reduction in all size traits of populations (size at puberty, median adult size, maximum size). In addition, we confirmed Cd-tolerance in contaminated populations during exposure tests in the laboratory. Various hypotheses can be then put forward to explain the modification of size-related life-history traits: a direct toxic effect of Cd, a cost of Cd-tolerance, or an adaptive evolution of life-history exposed to toxic pressure.

Avoidance behaviour of aquatic macroinvertebrates for real-time detection of micropollutant surge in wastewater effluents.

Micropollutants are regularly detected at the outlets of wastewater treatment plants (WWTPs). Across urban and industrial WWTPs, monitoring directives only require assessment for a handful of chemicals via sampling methods that fail to capture the temporal variability in micropollutant discharge. In this study, we develop a biotest for real-time on-line monitoring of micropollutant discharge dynamics in WWTPs effluents. The selected biomonitoring device ToxMate uses videotracking of invertebrate movement, which was used to deduce avoidance behaviour of the amphipod Gammarus fossarum. Organism conditioning was set up to induce a state of minimal locomotor activity in basal conditions to maximise avoidance signal sensitivity to micropollutant spikes. We showed that with a standardised protocol, it was possible to minimise both overall movement and sensitivity to physio-chemical variations typical to WWTP effluents, as well as capture the spikes of two micropollutants upon exposure (copper and methomyl). Spikes in avoidance behaviour were consistently seen for the two chemicals, as well as a strong correlation between avoidance intensity and spiked concentration. A two-year effluent monitoring case study also illustrates how this biomonitoring method is suitable for real-time on-site monitoring, and shows a promising non-targeted approach for characterising complex micropollutant discharge variability at WWTP effluents, which today remains poorly understood.

Automatic segmentation of the hippocampus and the amygdala driven by hybrid constraints: method and validation.

The segmentation from MRI of macroscopically ill-defined and highly variable structures, such as the hippocampus (Hc) and the amygdala (Am), requires the use of specific constraints. Here, we describe and evaluate a fast fully automatic hybrid segmentation that uses knowledge derived from probabilistic atlases and anatomical landmarks, adapted from a semi-automatic method. The algorithm was designed at the outset for application on images from healthy subjects and patients with hippocampal sclerosis. Probabilistic atlases were built from 16 healthy subjects, registered using SPM5. Local mismatch in the atlas registration step was automatically detected and corrected. Quantitative evaluation with respect to manual segmentations was performed on the 16 young subjects, with a leave-one-out strategy, a mixed cohort of 8 controls and 15 patients with epilepsy with variable degrees of hippocampal sclerosis, and 8 healthy subjects acquired on a 3 T scanner. Seven performance indices were computed, among which error on volumes RV and Dice overlap K. The method proved to be fast, robust and accurate. For Hc, results with the new method were: 16 young subjects {RV=5%, K=87%}; mixed cohort {RV=8%, K=84%}; 3 T cohort {RV=9%, K=85%}. Results were better than with atlas-based (thresholded probability map) or semi-automatic segmentations. Atlas mismatch detection and correction proved efficient for the most sclerotic Hc. For Am, results were: 16 young controls {RV=7%, K=85%}; mixed cohort {RV=19%, K=78%}; 3 T cohort {RV=10%, K=77%}. Results were better than with the semi-automatic segmentation, and were also better than atlas-based segmentations for the 16 young subjects.

Multivariate source prelocalization (MSP): use of functionally informed basis functions for better conditioning the MEG inverse problem.

Spatially characterizing and quantifying the brain electromagnetic response using MEG/EEG data still remains a critical issue since it requires solving an ill-posed inverse problem that does not admit a unique solution. To overcome this lack of uniqueness, inverse methods have to introduce prior information about the solution. Most existing approaches are directly based upon extrinsic anatomical and functional priors and usually attempt at simultaneously localizing and quantifying brain activity. By contrast, this paper deals with a preprocessing tool which aims at better conditioning the source reconstruction process, by relying only upon intrinsic knowledge (a forward model and the MEG/EEG data itself) and focusing on the key issue of localization. Based on a discrete and realistic anatomical description of the cortex, we first define functionally Informed Basis Functions (fIBF) that are subject specific. We then propose a multivariate method which exploits these fIBF to calculate a probability-like coefficient of activation associated with each dipolar source of the model. This estimated distribution of activation coefficients may then be used as an intrinsic functional prior, either by taking these quantities into account in a subsequent inverse method, or by thresholding the set of probabilities in order to reduce the dimension of the solution space. These two ways of constraining the source reconstruction process may naturally be coupled. We successively describe the proposed Multivariate Source Prelocalization (MSP) approach and illustrate its performance on both simulated and real MEG data. Finally, the better conditioning induced by the MSP process in a classical regularization scheme is extensively and quantitatively evaluated.

Disorganized somatotopy in the putamen of patients with focal hand dystonia.

OBJECTIVE: To explore the selectivity of neuronal somatotopic representation in the striatum of patients with unilateral task-specific dystonia of the right arm. MATERIALS AND METHODS: The authors used fMRI in 14 right-handed dystonic subjects to examine putaminal organization. Subjects performed flexion/extension of the right and left fingers and toes, and contraction of the lips. RESULTS: Compared to healthy volunteer subjects, dystonic subjects had altered somatotopic organization in the left putamen, contralateral to the affected hand. Disease severity correlated with underactivation and decreased distance between right hand and lip representations. In the right putamen, ipsilateral to the affected hand, the somatotopic organization was not altered but disease severity also correlated with reduced distances between limbs. CONCLUSION: In dystonia there may be a dedifferentiation of the normally segregated cortico-subcortical sensorimotor maps in the putamen, which may contribute to the loss of functional selectivity of muscle activity observed in these dystonic subjects.

Investigations of dipole localization accuracy in MEG using the bootstrap.

We describe the use of the nonparametric bootstrap to investigate the accuracy of current dipole localization from magnetoencephalography (MEG) studies of event-related neural activity. The bootstrap is well suited to the analysis of event-related MEG data since the experiments are repeated tens or even hundreds of times and averaged to achieve acceptable signal-to-noise ratios (SNRs). The set of repetitions or epochs can be viewed as a set of independent realizations of the brain's response to the experiment. Bootstrap resamples can be generated by sampling with replacement from these epochs and averaging. In this study, we applied the bootstrap resampling technique to MEG data from somatotopic experimental and simulated data. Four fingers of the right and left hand of a healthy subject were electrically stimulated, and about 400 trials per stimulation were recorded and averaged in order to measure the somatotopic mapping of the fingers in the S1 area of the brain. Based on single-trial recordings for each finger we performed 5000 bootstrap resamples. We reconstructed dipoles from these resampled averages using the Recursively Applied and Projected (RAP)-MUSIC source localization algorithm. We also performed a simulation for two dipolar sources with overlapping time courses embedded in realistic background brain activity generated using the prestimulus segments of the somatotopic data. To find correspondences between multiple sources in each bootstrap, sample dipoles with similar time series and forward fields were assumed to represent the same source. These dipoles were then clustered by a Gaussian Mixture Model (GMM) clustering algorithm using their combined normalized time series and topographies as feature vectors. The mean and standard deviation of the dipole position and the dipole time series in each cluster were computed to provide estimates of the accuracy of the reconstructed source locations and time series.

Dynamics of parietofrontal networks underlying visuospatial short-term memory encoding.

Brain imaging studies in TEP, functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) have shown that visuospatial short-term memory tasks depend on dorsal parietofrontal networks. Knowing the spatiotemporal dynamics of this network would provide further understanding of the neural bases of the encoding process. We combined magnetoencephalography (MEG) with EEG and fMRI techniques to study this network in a task, in which participants had to judge the symmetry in position of two dots, presented either simultaneously ("immediate comparison") or successively ("memorization" of a first dot and "delayed comparison", after 3 s, with a second dot). With EEG, larger amplitude was observed in the parietocentral P3b component (350-500 ms) in the immediate and "delayed comparisons" than in "memorization" condition, where topography at this time was more anterior and right lateralized. MEG provided a more accurate localization and temporal variations of sources, revealing a strong M4 component at 450 ms in the "memorization" condition, with two sources localized in parietal and right premotor regions. These localizations are consistent with both fMRI foci and EEG cortical current source densities (CSD), but only MEG revealed the strong increase in premotor region at 450 ms related to "memorization". These combined results suggest that EEG P3B and MEG M4 components reflect two different dynamics in parietofrontal networks: the parietocentral P3b indexes a decision mechanism during the immediate and "delayed comparisons", whereas the MEG M4 component, with a larger right premotor source, reflects the encoding process in visuospatial short-term memory.

Localization of realistic cortical activity in MEG using current multipoles.

We present a novel approach to MEG source estimation based on a regularized first-order multipole solution. The Gaussian regularizing prior is obtained by calculation of the sample mean and covariance matrix for the equivalent moments of realistic simulated cortical activity. We compare the regularized multipole localization framework to the classical dipole and general multipole source estimation methods by evaluating the ability of all three solutions to localize the centroids of physiologically plausible patches of activity simulated on the surface of a human cerebral cortex. The results, obtained with a realistic sensor configuration, a spherical head model, and given in terms of field and localization error, depict the performance of the dipolar and multipolar models as a function of variable source surface area (50-500 mm(2)), noise conditions (20, 10, and 5 dB SNR), source orientation (0-90 degrees ), and source depth (3-11 cm). We show that as the sources increase in size, they become less accurately modeled as current dipoles. The regularized multipole systematically outperforms the single dipole model, increasingly so as the spatial extent of the sources increases. In addition, our simulations demonstrate that as the orientation of the sources becomes more radial, dipole localization accuracy decreases substantially, while the performance of the regularized multipole model is far less sensitive to orientation and even succeeds in localizing quasi-radial source configurations. Furthermore, our results show that the multipole model is able to localize superficial sources with higher accuracy than the current dipole. These results indicate that the regularized multipole solution may be an attractive alternative to current-dipole-based source estimation methods in MEG.

[Dystonia: contributions of functional imaging and magnetoencephalography]. / Les dystonies: apports de l'imagerie fonctionnelle et de la magnéto-encéphalographie.

Functional neuroimaging using positron emission tomography (PET), and more recently functional MRI (fMRI) and magnetoencephalography (MEG), is a valuable tool to study functional anomalies in dystonia. Activation studies have contributed to a better understanding of cerebral dysfunction in dystonia showing two main types of abnormalities: changes in activation levels during performance of sensory or motor tasks and disorganization of the selectivity of neuronal representations. In primary dystonia, most PET and fMRI studies have shown overactivity in premotor and prefrontal areas and underactivation of primary sensorimotor areas. In secondary dystonia, premotor and prefrontal areas are similarly overactive as well as primary sensorimotor areas. Altered selectivity of neuronal representations has been described more recently along cortico-subcortical circuits. The loss of neuronal selectivity may contribute to the loss of selectivity of muscular contractions observed in dystonia. Spectroscopic MRI may also be used to measure GABA levels, which are decreased in the cortex and basal ganglia in these patients.

A multiresolution framework to MEG/EEG source imaging.

A new method based on a multiresolution approach for solving the ill-posed problem of brain electrical activity reconstruction from electroencephaloram (EEG)/magnetoencephalogram (MEG) signals is proposed in a distributed source model. At each step of the algorithm, a regularized solution to the inverse problem is used to constrain the source space on the cortical surface to be scanned at higher spatial resolution. We present the iterative procedure together with an extension of the ST-maximum a posteriori method [1] that integrates spatial and temporal a priori information in an estimator of the brain electrical activity. Results from EEG in a phantom head experiment with a real human skull and from real MEG data on a healthy human subject are presented. The performances of the multiresolution method combined with a nonquadratic estimator are compared with commonly used dipolar methods, and to minimum-norm method with and without multiresolution. In all cases, the proposed approach proved to be more efficient both in terms of computational load and result quality, for the identification of sparse focal patterns of cortical current density, than the fixed scale imaging approach.

Human brain mapping in dystonia reveals both endophenotypic traits and adaptive reorganization.

Dystonia has a wide clinical spectrum from early-onset generalized to late-onset sporadic, task-specific forms. The genetic origin of the former has been clearly established. A critical role of repetitive skilled motor tasks has been put forward for the latter, while underlying vulnerability traits are still being searched for. Using magnetoencephalography, we looked for structural abnormalities reflecting a preexisting dysfunction. We studied finger representations of both hands in the primary sensory cortex, as compared in 23 patients with unilateral task-specific dystonia and 20 control subjects. A dramatic disorganization of the nondystonic hand representation was found in all patients, and its amount paralleled the severity of the dystonic limb motor impairment. Abnormalities were also observed in the cortex coding the dystonic limb representation, but they were important only in the most severely affected patients. The abnormal cortical finger representations from the nondystonic limb appear to be endophenotypic traits of dystonia. That finger representations from the dystonic limb were almost normal for the less severely affected patients may be due to intrinsic beneficial remapping in reaction against the primary disorder.

Evaluation of inverse methods and head models for EEG source localization using a human skull phantom.

We used a real-skull phantom head to investigate the performances of representative methods for EEG source localization when considering various head models. We describe several experiments using a montage with current sources located at multiple positions and orientations inside a human skull filled with a conductive medium. The robustness of selected methods based on distributed source models is evaluated as various solutions to the forward problem (from the sphere to the finite element method) are considered. Experimental results indicate that inverse methods using appropriate cortex-based source models are almost always able to locate the active source with excellent precision, with little or no spurious activity in close or distant regions, even when two sources are simultaneously active. Superior regularization schemes for solving the inverse problem can dramatically help the estimation of sparse and focal active zones, despite significant approximation of the head geometry and the conductivity properties of the head tissues. Realistic head models are necessary, though, to fit the data with a reasonable level of residual variance.

ERPs and PET analysis of time perception: spatial and temporal brain mapping during visual discrimination tasks.

ERPs were recorded from 12 subjects performing duration and intensity visual discrimination tasks which have been previously used in a PET study. PET data showed that the same network was activated in both tasks [P. Maquet et al., NeuroImage 3:119-126, 1996]. Different ERP waveforms were observed for the late latency components depending on the dimension of the stimulus to be processed: frontal negativity (CNV) for the duration task and parieto-occipital positivity (P300) for the intensity task. Using BESA software, the sources were first modelled with a "PET dipolar model" (right prefrontal, right parietal, anterior cingulate, left and right fusiforms). To obtain a better fit for ERPs recorded in each task, two sources (cuneus, left prefrontal area) had to be added. Consistently with PET findings, dipole modelling indicates that duration and intensity dimensions of a visual stimulus are processed in the same areas. However, ERPs also reveal prominent differences between the time course of the dipole activations for each task, particularly for sources contributing to the late latency ERP components. In the intensity task, dipoles located in the cuneus, the anterior cingulate, and the left prefrontal area yield largest activity within the P300 interval, then activity diminishes rapidly as the stimulus ends, whereas in the duration task, the cuneus and anterior cingulate are still active several hundred milliseconds following stimulus offset. Moreover, in the duration task, the activity of the right frontal dipole parallels the CNV waveform, whereas in the intensity task, this dipole is largely inactive. We assume that the right frontal area plays a specific role in the formation of temporal judgments.

TMpcp: a Tuber magnatum gene which encodes a putative mitochondrial phosphate carrier.

Little is known about the genome of Tuber, Ascomycetes which comprise a number of ectomycorrhizal species. Screening of a genomic library of Tuber magnatum led to identification of a chitin synthase gene (chs). On sequencing upstream of it in the same phage, we found a 2000 bp long fragment that proved to contain a hypothetical gene with high homology with mitochondrial phosphate carriers from human and bovine heart, and from Saccharomyces cerevisiae. The sequence contains two putative introns and its open reading frame encodes for a protein 305 amino acids long. A primary sequence analysis revealed 6 hydrophobic segments and a signature pattern, similar to that of other mitochondrial carriers.

Segmentation of the skull in MRI volumes using deformable model and taking the partial volume effect into account.

Segmentation of the skull in medical imagery is an important stage in applications that require the construction of realistic models of the head. Such models are used, for example, to simulate the behavior of electro-magnetic fields in the head and to model the electrical activity of the cortex in EEG and MEG data. In this paper, we present a new approach for segmenting regions of bone in MRI volumes using deformable models. Our method takes into account the partial volume effects that occur with MRI data, thus permitting a precise segmentation of these bone regions. At each iteration of the propagation of the model, partial volume is estimated in a narrow band around the deformable model. Our segmentation method begins with a pre-segmentation stage, in which a preliminary segmentation of the skull is constructed using a region-growing method. The surface that bounds the pre-segmented skull region offers an automatic 3D initialization of the deformable model. This surface is then propagated (in 3D) in the direction of its normal. This propagation is achieved using level set method, thus permitting changes to occur in the topology of the surface as it evolves, an essential capability for our problem. The speed at which the surface evolves is a function of the estimated partial volume. This provides a sub-voxel accuracy in the resulting segmentation.

Differential expression of chitin synthase III and IV mRNAs in ascomata of Tuber borchii Vittad.

A full-length genomic clone encoding a class III chitin synthase (CHS) and one DNA fragment corresponding to a class IV CHS were isolated from the mycorrhizal fungus Tuber borchii and used for an extensive expression analysis, together with a previously identified DNA fragment corresponding to a class II CHS. All three Chs mRNAs are constitutively expressed in vegetative mycelia, regardless of the age, mode of growth, and proliferation capacity of the hyphae. A strikingly different situation was observed in ascomata, where class III and IV, but not class II, mRNAs are differentially expressed in a maturation stage-dependent manner and accumulate, respectively, in sporogenic and vegetative hyphae. These data, the first on the expression of distinct Chs mRNAs during fruitbody development, point to the different cellular roles that can be played by distinct chitin synthases in the differentiation of spores of sexual origin (CHS III) or in ascoma enlargement promoted by the growth of vegetative hyphae (CHS IV).

Combined MEG and EEG source imaging by minimization of mutual information.

Though very frequently assumed, the necessity to operate a joint processing of simultaneous magnetoencephalography (MEG) and electroencephalography (EEG) recordings for functional brain imaging has never been clearly demonstrated. However, the very last generation of MEG instruments allows the simultaneous recording of brain magnetic fields and electrical potentials on the scalp. But the general fear regarding the fusion between MEG and EEG data is that the drawbacks from one modality will systematically spoil the performances of the other one without any consequent improvement. This is the case for instance for the estimation of deeper or radial sources with MEG. In this paper, we propose a method for a cooperative processing of MEG and EEG in a distributed source model. First, the evaluation of the respective performances of each modality for the estimation of every dipole in the source pattern is made using a conditional entropy criterion. Then, the algorithm operates a preprocessing of the MEG and EEG gain matrices which minimizes the mutual information between these two transfer functions, by a selective weighting of the MEG and EEG lead fields. This new combined EEG/MEG modality brings major improvements to the localization of active sources, together with reduced sensitivity to perturbations on data.

Chitin synthase genes in the arbuscular mycorrhizal fungus Glomus versiforme: full sequence of a gene encoding a class IV chitin synthase.

Chitin synthase genes of the arbuscular mycorrhizal fungus Glomus versiforme were sought in an investigation of the molecular basis of fungal growth. Three DNA fragments (Gvchs1, Gvchs2 and Gvchs3) corresponding to the conserved regions of distinct chitin synthase (chs) genes were amplified by means of the polymerase chain reaction (PCR) with two sets of degenerate primers. Gvchs1 and Gvchs2 encode two class I chitin synthases, whereas Gvchs3 encodes a class IV chitin synthase. A genomic library was used to obtain the Gvchs3 complete gene (1194 amino acids), which shows a very close similarity to the class IV chitin synthase from Neurospora crassa.