Biomedical subjects

M Pélégrini-Issac

Publications and source records attributed to M Pélégrini-Issac.

6 recordsLinked to original sources

PubMed2006

Neuroanatomical correlates of penile erection evoked by photographic stimuli in human males.

The objective of this study was to identify the cerebral correlates of the early phase, and of low to moderate levels, of penile tumescence using for the first time a volumetric measure of the penile response. We hypothesized that (i) regions whose response had been found correlated with circumferential penile responses in previous studies would be identified with volumetric plethysmography and (ii) that other brain regions, including the amygdalae, would be found using the more sensitive volumetric measurement. In ten healthy males, functional magnetic resonance imaging (fMRI) was used to study brain responses to sexually stimulating photographs and to various categories of control photographs. Both ratings of perceived erection and penile plethysmography demonstrated an erectile response to the presentation of sexually stimulating photographs. Regions where the BOLD signal was correlated with penile volumetric responses included the right medial prefrontal cortex, the right and left orbitofrontal cortices, the insulae, the paracentral lobules, the right ventral lateral thalamic nucleus, the right anterior cingulate cortex and regions involved in motor imagery and motor preparation (supplementary motor areas, left ventral premotor area). This study suggests that the development of low levels of penile tumescence in response to static sexual stimuli is controlled by a network of frontal, parietal, insular and cingulate cortical areas and that penile tumescence reciprocally induces activation in somatosensory regions of the brain.

Adult↗

PubMed2006

Federating distributed and heterogeneous information sources in neuroimaging: the NeuroBase Project.

The NeuroBase project aims at studying the requirements for federating, through the Internet, information sources in neuroimaging. These sources are distributed in different experimental sites, hospitals or research centers in cognitive neurosciences, and contain heterogeneous data and image processing programs. More precisely, this project consists in creating of a shared ontology, suitable for supporting various neuroimaging applications, and a computer architecture for accessing and sharing relevant distributed information. We briefly describe the semantic model and report in more details the architecture we chose, based on a media-tor/wrapper approach. To give a flavor of the future deployment of our architecture, we de-scribe a demonstrator that implements the comparison of distributed image processing tools applied to distributed neuroimaging data.

Databases as Topic↗

PubMed2005

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.

Algorithms↗

PubMed2004

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.

Adult↗

PubMed2003

Individual differences in prefrontal cortical activation on the Tower of London planning task: implication for effortful processing.

Solving challenging ('effortful') problems is known to involve the dorsal and dorsolateral prefrontal cortex in normal volunteers, although there is considerable individual variation. In this functional magnetic resonance imaging study, we show that healthy subjects with different levels of performance in the Tower of London planning task exhibit different patterns of brain activation. All subjects exhibited significant bilateral activation in the dorsolateral prefrontal cortex, the anterior and posterior cingulate areas and the parietal cortex. However, 'standard performers' (performance < 70% correct) and 'superior performers' (performance >70% correct) differed in the patterns of activation exhibited. Superior performers showed a significantly more spatially extended activation in the left dorsolateral prefrontal cortex than did standard performers, whereas the latter group tended to show increased activation of the anterior cingulate region.

Adolescent↗

PubMed2002

Estimating the effective degrees of freedom in univariate multiple regression analysis.

The general linear model provides the most widely applied statistical framework for analyzing functional MRI (fMRI) data. With the increasing temporal resolution of recent scanning protocols, and more elaborate data preprocessing schemes, data independency is no longer a valid assumption. In this paper, we revise the statistical background of the general linear model in the presence of temporal autocorrelations. First, when detecting the activation signal, we explicitly account for the temporal autocorrelation structure, which yields a generalized F-test and the associated corrected (or effective) degrees of freedom (DOF). The proposed approach is data driven and thus independent of any specific preprocessing method. Then, for event-related protocols, we propose a new model for the temporal autocorrelations ("damped oscillator" model) and compare this model to another, previously used in the field (first-order autoregressive model, or AR(1) model). In the case of long fMRI time series, an efficient approximation for the number of effective DOF is provided for both models. Finally, the validity of our approach is assessed using simulated and real fMRI data and is compared with more conventional methods.

Analysis of Variance↗