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Biomedical subjects

J F Mangin

Publications and source records attributed to J F Mangin.

At least 19 recordsLinked to original sources

Modulation of language areas with functional MR image-guided magnetic stimulation.

Repetitive transcranial magnetic stimulation (rTMS) can interfere with linguistic performance when delivered over language areas. At low frequency (1 Hz), rTMS is assumed to decrease cortical excitability; however, the degree of TMS effect on cortical language areas may depend on the localization of the stimulation coil with respect to the inter-individual anatomo-functional variations. Hence, we aimed at investigating individual brain areas involved in semantic and phonological auditory processes. We hypothesized that active rTMS targeted over Wernicke's area might modify the performance during a language-fragment-detection task. Sentences in native or foreign languages were presented to 12 right-handed male healthy volunteers during functional magnetic resonance imaging (fMRI). 3D-functional maps localized the posterior temporal activation (Wernicke) in each subject and MRI anatomical cortical landmarks were used to define Broca's pars opercularis (F3Op). A frameless stereotaxy system was used to guide the TMS coil position over Wernicke's and F3Op areas in each subject. Active and placebo randomized rTMS sessions were applied at 1 Hz, 110% of motor threshold, during the same language-fragment-detection task. Accuracy and response time (RT) were recorded. RT was significantly decreased by active rTMS compared to placebo over Wernicke's area, and was more decreased for native than for foreign languages. No significant RT change was observed for F3Op area. rTMS conditions did not impair participants' accuracy. Thus, low-frequency rTMS over Wernicke's area can speed-up the response to a task tapping on native language perception in healthy volunteers. This individually-guided stimulation study confirms that facilitatory effects are not confined to high-frequency rTMS.

Adult↗

MR diffusion-based inference of a fiber bundle model from a population of subjects.

This paper proposes a method to infer a high level model of the white matter organization from a population of subjects using MR diffusion imaging. This method takes as input for each subject a set of trajectories stemming from any tracking algorithm. Then the inference results from two nested clustering stages. The first clustering converts each individual set of trajectories into a set of bundles supposed to represent large white matter pathways. The second clustering matches these bundles across subjects in order to provide a list of candidates for the bundle model. The method is applied on a population of eleven subjects and leads to the inference of 17 such candidates.

Algorithms↗

Anatomically constrained surface parameterization for cortical localization.

We present here a method that aims at defining a surface-based coordinate system on the cortical surface. Such a system is needed for both cortical localization and intersubject matching in the framework of neuroimaging. We propose an automatic parameterization based on the spherical topology of the grey/white matter interface of each hemisphere and on the use of naturally organized and reproducible anatomical features. From those markers used as initial constraints, the coordinate system is propagated via a PDE solved on the cortical surface.

Algorithms↗

Brain anatomy in Turner syndrome: evidence for impaired social and spatial-numerical networks.

Analysis of brain structure in Turner syndrome (TS) provides the opportunity to identify the consequences of the loss of one X chromosome on brain anatomy and to characterize the neural bases underlying the specific cognitive profile of TS subjects which includes deficits in spatial-numerical processing and social cognition. Fourteen subjects with TS and fourteen controls were investigated using voxel-based analysis of high resolution anatomical and diffusion tensor images and using sulcal morphometry. The analysis of anatomical images provided evidence for macroscopical changes in cortical regions involved in social cognition such as the left superior temporal sulcus and orbito-frontal cortex and in a region involved in spatial and numerical cognition such as the right intraparietal sulcus. Diffusion tensor images showed a displacement of the grey-white matter interface of the left and right superior temporal sulcus and revealed bilateral microstructural anomalies in the temporal white matter. The analysis of fiber orientation suggests specific alterations of fiber tracts connecting posterior to anterior temporal regions. Last, sulcal morphometry confirmed the anomalies of the left and right superior temporal sulci and of the right intraparietal sulcus. Our results thus provide converging evidence of regionally specific structural changes in TS that are highly consistent with the hallmark symptoms associated with TS.

Adolescent↗

Object-based morphometry of the cerebral cortex.

Most of the approaches dedicated to automatic morphometry rely on a point-by-point strategy based on warping each brain toward a reference coordinate system. In this paper, we describe an alternative object-based strategy dedicated to the cortex. This strategy relies on an artificial neuroanatomist performing automatic recognition of the main cortical sulci and parcellation of the cortical surface into gyral patches. A set of shape descriptors, which can be compared across subjects, is then attached to the sulcus and gyrus related objects segmented by this process. The framework is used to perform a study of 142 brains of the International Consortium for Brain Mapping (ICBM) database. This study reveals some correlates of handedness on the size of the sulci located in motor areas, which was not detected previously using standard voxel based morphometry.

Algorithms↗

Object-based strategy for morphometry of the cerebral cortex.

Most of the approaches dedicated to automatic morphometry rely on a point-by-point strategy based on warping each brain towards a reference coordinate system. In this paper, we describe an alternative object-based strategy dedicated to the cortex. This strategy relies on an artificial neuroanatomist performing automatic recognition of the main cortical sulci and parcellation of the cortical surface into gyral patches. A set of shape descriptors, which can be compared across subjects, is then attached to the sulcus and gyrus related objects segmented by this process. The framework is used to perform a study of 142 brains of the ICBM database. This study reveals some correlates of handedness on the size of the sulci located in motor areas, which seem to be beyond the scope of the standard voxel based morphometry.

Algorithms↗

A primal sketch of the cortex mean curvature: a morphogenesis based approach to study the variability of the folding patterns.

In this paper, we propose a new representation of the cortical surface that may be used to study the cortex folding process and to recover some putative stable anatomical landmarks called sulcal roots usually buried in the depth of adult brains. This representation is a primal sketch derived from a scale space computed for the mean curvature of the cortical surface. This scale-space stems from a diffusion equation geodesic to the cortical surface. The primal sketch is made up of objects defined from mean curvature minima and saddle points. The resulting sketch aims first at highlighting significant elementary cortical folds, second at representing the fold merging process during brain growth. The relevance of the framework is illustrated by the study of central sulcus sulcal roots from antenatal to adult age. Some results are proposed for ten different brains. Some preliminary results are also provided for superior temporal sulcus.

Adult↗

Visualizing the neural bases of a disconnection syndrome with diffusion tensor imaging.

Disconnection syndromes are often conceptualized exclusively within cognitive box-and-arrow diagrams unrelated to brain anatomy. In a patient with alexia in his left visual field resulting from a posterior callosal lesion, we illustrate how diffusion tensor imaging can reveal the anatomical bases of a disconnection syndrome by tracking the degeneration of neural pathways and relating it to impaired fMRI activations and behavior. Compared to controls, an abnormal pattern of brain activity was observed in the patient during word reading, with a lack of activation of the left visual word form area (VWFA) by left hemifield words. Statistical analyses of diffusion images revealed a damaged fiber tract linking the left ventral occipito-temporal region to its right homolog across the lesioned area of corpus callosum and stopping close to the areas found active in fMRI. The behavioral disconnection syndrome could, thus, be related functionally to abnormal fMRI activations and anatomically to the absence of a connection between those activations. The present approach, based on the "negative tracking" of degenerated bundles, provides new perspectives on the understanding of human brain connections and disconnections.

Adult↗

What is the best similarity measure for motion correction in fMRI time series?

It has been shown that the difference of squares cost function used by standard realignment packages (SPM and AIR) can lead to the detection of spurious activations, because the motion parameter estimations are biased by the activated areas. Therefore, this paper describes several experiments aiming at selecting a better similarity measure to drive functional magnetic resonance image registration. The behaviors of the Geman-McClure (GM) estimator, of the correlation ratio, and of the mutual information (MI) relative to activated areas are studied using simulated time series and actual data stemming from a 3T magnet. It is shown that these methods are more robust than the usual difference of squares measure. The results suggest also that the measures built from robust metrics like the GM estimator may be the best choice, while MI is also an interesting solution. Some more work, however, is required to compare the various robust metrics proposed in the literature.

Algorithms↗

Role of the supplementary motor area in motor deficit following medial frontal lobe surgery.

OBJECTIVE: Patients undergoing surgical resection of medial frontal lesions may present a transient postoperative deficit that remains largely unpredictable. The authors studied the role of the supplementary motor area (SMA) in the occurrence of this deficit using fMRI. METHODS: Twenty-three patients underwent a preoperative fMRI before resection of medial frontal lesions. Tasks included self-paced flexion/extension of the left and right hand, successively. Preoperative fMRI data were compared with postoperative MRI data and with neurologic outcome. RESULTS: Following surgery, 11 patients had a motor deficit from which all patients recovered within a few weeks or months. The deficit was similar across patients, consisting of a global reduction in spontaneous movements contralateral to the operated side with variable severity. SMA activation was observed in all patients. The deficit was observed when the area activated in the posterior part of the SMA (SMA proper) was resected. CONCLUSIONS: fMRI is able to identify the area at risk in the SMA proper whose resection is highly related to the occurrence of the motor deficit. The clinical characteristics of this deficit support the role of the SMA proper in the initiation and execution of the movement.

Adult↗

Detection of fMRI activation using cortical surface mapping.

A methodology for fMRI data analysis confined to the cortex, Cortical Surface Mapping (CSM), is presented. CSM retains the flexibility of the General Linear Model based estimation, but the procedures involved are adapted to operate on the cortical surface, while avoiding to resort to explicit flattening. The methodology is tested by means of simulations and application to a real fMRI protocol. The results are compared with those obtained with a standard, volume-oriented approach (SPM), and it is shown that CSM leads to local differences in sensitivity, with generally higher sensitivity for CSM in two of the three subjects studied. The discussion provided is focused on the benefits of the introduction of anatomical information in fMRI data analysis, and the relevance of CSM as a step toward this goal.

Brain Mapping↗

Diffusion tensor imaging: concepts and applications.

The success of diffusion magnetic resonance imaging (MRI) is deeply rooted in the powerful concept that during their random, diffusion-driven displacements molecules probe tissue structure at a microscopic scale well beyond the usual image resolution. As diffusion is truly a three-dimensional process, molecular mobility in tissues may be anisotropic, as in brain white matter. With diffusion tensor imaging (DTI), diffusion anisotropy effects can be fully extracted, characterized, and exploited, providing even more exquisite details on tissue microstructure. The most advanced application is certainly that of fiber tracking in the brain, which, in combination with functional MRI, might open a window on the important issue of connectivity. DTI has also been used to demonstrate subtle abnormalities in a variety of diseases (including stroke, multiple sclerosis, dyslexia, and schizophrenia) and is currently becoming part of many routine clinical protocols. The aim of this article is to review the concepts behind DTI and to present potential applications.

Brain Diseases↗

Motion correction algorithms may create spurious brain activations in the absence of subject motion.

This paper describes several experiments that prove that standard motion correction methods may induce spurious activations in some motion-free fMRI studies. This artifact stems from the fact that activated areas behave like biasing outliers for the difference of square-based measures usually driving such registration methods. This effect is demonstrated first using a motion-free simulated time series including artificial activation-like signal changes. Several additional simulations explore the influence of activation amplitude and extent. The effect is finally highlighted on an actual time series obtained from a 3-T magnet. All the experiments are performed using four different realignment methods, which allows us to show that the problem may be overcome by methods based on a robust similarity measure like mutual information.

Algorithms↗

Cerebral mechanisms of word masking and unconscious repetition priming.

We used functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) to visualize the cerebral processing of unseen masked words. Within the areas associated with conscious reading, masked words activated left extrastriate, fusiform and precentral areas. Furthermore, masked words reduced the amount of activation evoked by a subsequent conscious presentation of the same word. In the left fusiform gyrus, this repetition suppression phenomenon was independent of whether the prime and target shared the same case, indicating that case-independent information about letter strings was extracted unconsciously. In comparison to an unmasked situation, however, the activation evoked by masked words was drastically reduced and was undetectable in prefrontal and parietal areas, correlating with participants' inability to report the masked words.

Adult↗

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.

Electroencephalography↗

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.

Algorithms↗

Diffusion tensor imaging study of subcortical gray matter in cadasil.

BACKGROUND AND PURPOSE: In cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), water diffusion changes suggestive of microstructural tissue alterations have been recently reported in abnormal- and normal-appearing white matter as seen on T2-weighted images. In the subcortical gray matter, typical lacunar infarcts are repeatedly observed. Whether microstructural tissue changes are also present outside these lesions within the putamen or thalamus remains unknown. METHODS: We used diffusion tensor imaging, an MRI method highly sensitive to cerebral microstructure, in 20 CADASIL patients and 12 controls. Both the trace of the diffusion tensor [Tr(D)] and an anisotropic diffusion index (volume ratio) of diffusion were measured within the putamen and thalamus outside typical lacunar infarcts as detected on both T1- and T2-weighted images. RESULTS: A significant increase in Tr(D) and a decrease in anisotropy were observed in the putamen and thalamus in patients. The right/left indices of Tr(D) in the thalamus, but not in the putamen, were strongly correlated with the corresponding indices calculated in the white matter of the centrum semiovale. In addition, the diffusion increase in the thalamus was positively correlated with Tr(D) and with the load of small deep infarcts within the white matter and negatively correlated with the Mini-Mental State Examination score. CONCLUSIONS: Our results suggest that microstructural tissue alterations are present in the putamen and thalamus, outside the typical lacunar infarcts in CADASIL. In the thalamus, these microstructural changes appear constant and are even observed in asymptomatic subjects. Some of these thalamic changes appear to result from degeneration of thalamocortical pathways secondary to ischemic white matter damage. The importance of this degenerative phenomenon in the pathophysiology of CADASIL requires further investigation.

Analysis of Variance↗

Structural group analysis of functional activation maps.

We present here a new method for cerebral activation detection over a group of subjects. This method is performed using individual activation maps of any sort. It aims at processing a group analysis while preserving individual information and at overcoming as far as possible limitations of the spatial normalization used to compare different subjects. We designed it such that it provides the individual occurrence of the activations detected at a group level. The localization can then be performed on the individual anatomy of each subject. The analysis starts with a hierarchical multiscale object-based description of each individual map. These descriptions are then compared, rather than comparing the images directly. The analysis is thus performed at an object level instead of voxel by voxel. It is made using a comparison graph, on which a labeling process is performed. The label field on the graph is modeled by a Markov random field, which allows us to introduce high-level rules of interrogation of the data. The process has been evaluated on simulated data and real data from a PET protocol.

Brain↗