Dissertations / Theses on the topic 'Magnétoencéphalographie (MEG)'
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Corsi, Marie-Constance. "Magnétomètres à pompage optique à Hélium 4 : développement et preuve de concept en magnétocardiographie et en magnétoencéphalographie." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAT082/document.
Full textMagnetocardiography (MCG) and magnetoencephalography (MEG) are non-invasive techniques consisting in measuring respectively cardiac and brain magnetic fields. Despite their performance, the sensors currently used need a cryogenic cooling system which engenders technical and financial constraints. New cryogenic-free sensors have recently emerged: the OPMs (Optically-Pumped Magnetometers). Among them, vector 4He magnetometers developed by CEA-LETI which work at room-temperature. This thesis is focused on the development of 4He magnetometers dedicated to MCG and MEG.After having optimized the key-parameters of a first non-miniaturized prototype, a sensitivity inferior to 100 fT/sqrt(Hz) has been obtained along two axes. In order to meet biomedical constraints, a miniaturization of the device has been processed. In parallel, preclinical tests were carried out which have enabled us to design a gradiometer mode, a new packaging, and a magnetically isolated system. A noise analysis revealed that laser and HF discharge were the main sources of disturbance, and lead us to consider improvements such as a new detection mode. Eventually, a sensor, with a 1cm-sided cell, and an intrinsic sensitivity of 350 fT/√Hz has been developed.Then, device has been successfully tested in the frame of the MCG application from a healthy subject, preceded by a simulation study with a phantom which enables us to demonstrate its operability within a clinical environment. Moreover, we have proved the reproducibility of the measurements and the possibility to detect the main features of the cardiac cycle within a 30 s recording time. A specific optimization of the optical part has enabled us to obtain a 210 fT/sqrt(Hz) sensitivity between 3 and 300 Hz, suitable for the MEG application. After having tested our device with a phantom, three MEG experiments were performed with a healthy subject: auditory evoked field, visual evoked field and spontaneous activities have been detected. The obtained results form the first clinical proof of concept of the device for MCG and MEG applications
Lachat, Fanny. "L’attention conjointe dans tous ses états : études MEG, comportementale et dual-EEG." Paris 6, 2012. http://www.theses.fr/2012PA066097.
Full textCimatti, Zoé. "Caractérisation des oscillations hautes fréquences en magnétoencéphalographie : application à la crampe de l'écrivain." Paris 6, 2007. http://www.theses.fr/2007PA066317.
Full textVallaghé, Sylvain. "EEG and MEG forward modelling : computation and calibration." Nice, 2009. http://www.theses.fr/2008NICE4095.
Full textThis thesis focuses on the forward problem of electroencephalography (EEG) and magnetoencephalography (MEG). The first part deals with the calculation of the forward problem solution. We present a new finite element method (FEM) based on a regular hexahedral mesh and implicit descriptions of the domain, which allows to solve the forward problem in realistic geometries with a low computational cost. We add to this method some general reciprocal equations, derived by the adjoint method, in aim to efficiently compute the lead field of all kinds of EEG and MEG sensors. The second part is concerned with the choice of the electrical conductivities in the EEG head models. We first perform a global sensitivity analysis of the EEG topographies with respect to the conductivities for some classical head models with three or four layers. Following the results of this analysis, we then propose a method for conductivity calibration using somatosensory evoked potentials
Cottereau, Benoit. "Modèles hiérarchiques en imagerie MEG/EEG : application à la création rapide de cartes rétinotopiques." Paris 11, 2008. http://www.theses.fr/2008PA112042.
Full textWhen combined with image reconstruction techniques, magnetoencephalography (MEG) and electroencephalography (EEG) may open new windows for the observation and exploration of time-resolved brain processes at the local--regional spatial scale. The ill-posedness of the associated inverse problem however, necessitates the introduction of image models as regularizing priors. Basic priors -- e. G. Quadratic in the norm of the expected neural currents -- yield images of brain activity that are often too smeared for the satisfactory elucidation of specific neuroscience questions that focus on localization. On the other hand, more sophisticated prior image models -- even though they would theoretically improve the detection of sparse-focal current distributions -- suffer from scalability issues that imped their practical impact. In this PhD work, my primary objective was to reconcile the best of both approaches. I have derived a multiresolution imaging technique which proceeds iteratively to the fit of image models based on the parcellation of the cortical surface. This latter derives from anatomical and functional priors such as the curvature of the cortical manifold, and/or the coregistration to some atlas relevant to the neuroscience investigation. Technically, the multiresolution imaging technique is approached as an empirical model selection procedure optimized according to the least-generalized cross validation (GCV) error principle. Further, the piecewise current model is adequately approached using a compact parametric model based on equivalent current multipoles
Dumas, Thibaud. "Étude en MEG de la contribution de l’amygdale à la perception des personnes : de la perception des visages à la coprésence." Paris 6, 2013. http://www.theses.fr/2013PA066516.
Full textPerson perception is an essential component of our living in society and a main source of emotional and social signals. The amygdala is a key structure in emotional and social processes. However, little is known about the temporal dynamics of amygdala responses. I performed two magnetoencephalography (MEG) studies in order to investigate two components of person perception: face perception and person density perception. The first study is based on the implementation of a source estimation method of the amygdala magnetic activity in order to study the temporal dynamics of its contribution to the perception of fearful and neutral faces with direct or averted gaze. I showed amygdala responses to facial emotion as soon as 130-170 ms post-stimulus, and then between 310 and 350 ms, as well as sustained amygdala responses to gaze between 190 and 350 ms. The second study was focused on the study of amygdala contribution to the perception of real-life visual scenes varying in person density that were shot from Paris subway. We revealed a modulation of amygdala responses to the higher density between 170 and 210 ms, as well as a sustained effect of person density on orbitofrontal cortex (OFC) responses between 210 and 600 ms. An occipitolateral cortex response to person density was observed from 90-130 ms, and also concomitantly with amygdala and OFC responses. These studies provide new information about amygdala contribution to person perception with the implementation of an original source localization method of MEG signals
Gramfort, Alexandre. "Localisation et suivi d'activité fonctionnelle cérébrale en électro et magnétoencéphalographie: Méthodes et applications au système visuel humain." Phd thesis, Ecole nationale supérieure des telecommunications - ENST, 2009. http://tel.archives-ouvertes.fr/tel-00426852.
Full textChaumon, Maximilien. "Apprentissage implicite du contexte visuel et guidage de la perception : Expériences MEG et EEG intracrânien." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2008. http://tel.archives-ouvertes.fr/tel-00310152.
Full textNous proposons que l'activité gamma permet la création et l'affûtage d'une représentation neuronale par des mécanismes de plasticité dépendante de la synchronie des potentiels d'action (spike timing dependent plasticity, STDP). Cette représentation une fois créée serait activée très rapidement pour biaiser le traitement cérébral, permettant la prise en compte de l'expérience vécue dès les étapes précoces du traitement sensoriel.
Bonnefond, Mathilde. "Caractérisation des étapes de traitement élémentaire du raisonnement conditionnel à l’aide de l’EEG et de la MEG : effet de l’incertitude du conditionnel et des différences interindividuelles." Electronic Thesis or Diss., Lyon 2, 2009. http://www.theses.fr/2009LYO20101.
Full textThe conditional reasoning, based on statements of the form If P then Q, is one which has received the most attention from psychologists. The main arguments of conditional reasoning, as the Modus Ponens (MP), consist of three elements: the major premise (If P then Q), the minor premise (P) and conclusion (Q). These elements constitute three separate processing steps. However, the temporal dimension of reasoning has been partly neglected in the literature. The central objective of this thesis was to explore the temporal dimension by using an innovative approach combining the use of the measurement of premises reading time and of the electroencephalography (EEG) and magnetoencephalography ( MEG). We set three objectives: 1) Determine the sequence of processing steps of the basic argument MP 2) Determine how the uncertainty of a conditional theme is taken into account, 3) Highlight the interindividual differences in treatment a conditional statement, or basic theme by introducing the study of the AC argument, which allows to separate two populations: individuals who accept the conclusion of AC and individuals who reject it. The data reveals that all individuals have a tendency to focus more on P and Q in the processing of the conditional, with varying degrees in different individuals. When the premise P (or Q for participants that accept AC) is presented, it is integrated with the major premise to generate a conclusion Q encoded and stored in working memory before being compared with the conclusions presented. When the conditional is uncertain (Thematic conditional), this uncertainty about the sufficiency of P for Q (or Q for P) seems to be taken into account by the subjects at the major premise and is manifested by an less pronounced expectation of Q conclusion when the premise P has been presented
Pizzo, Francesca. "Neurophysiological biomarkers of epileptogenic networks in intracranial (stereoelectroencephalography-SEEG) and simultaneous SEEG-magnetoelectroencephalography recordings." Thesis, Aix-Marseille, 2019. http://www.theses.fr/2019AIXM0671.
Full textEpilepsy is a networks disease and understanding networks organization underlying this pathology is essential to assure the best therapeutic option for the patient. This thesis aims to provide insights in the investigation of pathological brain networks in patients studied by intracerebral recordings (stereoelectroncephalography - SEEG) during presurgical evaluation of epilepsy. To this purpose, we applied signal analysis methods to invasive and non-invasive recordings, using neurophysiological biomarkers of epileptogenicity (spikes, high frequency oscillations, epileptogenicity index). In the first work, we studied the relationship between the neocortex and nodular heterotopia, a malformation of cortical development. We have shown that the neocortex or the neocortex with the heterotopic lesion, is the leading structure of the epileptic networks and finally the malformative lesion is very rarely the most epileptogenic region. In the second work, we studied the relationship between the neocortex and other subcortical nuclei, in particular the thalamus. We have shown that the degree of epileptogenicity of thalamus is directly correlated with the extension of the epileptic network and is associated with poor surgical outcome. The third study was conducted on simultaneous intracerebral and surface recordings, SEEG -magnetoencephalography (MEG). We have demonstrated, through independent component analysis (ICA) on the MEG, that epileptic networks of deep brain structures can be recovered by surface recordings. These results confirm that quantified signal analysis is a powerful tool for understanding the complex epileptic networks studied by intracerebral recordings and MEG
Mattout, Jérémie. "Approches statistiques multivariées pour la localisation de l'activation cérébrale en magnétoencéphalographie et en imagerie par résonance magnétique fonctionnelle : vers une fusion d'informations multimodales." Paris 6, 2002. http://www.theses.fr/2002PA066440.
Full textDupré, la Tour Tom. "Nonlinear models for neurophysiological time series." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLT018/document.
Full textIn neurophysiological time series, strong neural oscillations are observed in the mammalian brain, and the natural processing tools are thus centered on narrow-band linear filtering.As this approach is too reductive, we propose new methods to represent these signals.We first focus on the study of phase-amplitude coupling (PAC), which consists in an amplitude modulation of a high frequency band, time-locked with a specific phase of a slow neural oscillation.We propose to use driven autoregressive models (DAR), to capture PAC in a probabilistic model. Giving a proper model to the signal enables model selection by using the likelihood of the model, which constitutes a major improvement in PAC estimation.%We first present different parametrization of DAR models, with fast inference algorithms and stability discussions.Then, we present how to use DAR models for PAC analysis, demonstrating the advantage of the model-based approach on three empirical datasets.Then, we explore different extensions to DAR models, estimating the driving signal from the data, PAC in multivariate signals, or spectro-temporal receptive fields.Finally, we also propose to adapt convolutional sparse coding (CSC) models for neurophysiological time-series, extending them to heavy-tail noise distribution and multivariate decompositions. We develop efficient inference algorithms for each formulation, and show that we obtain rich unsupervised signal representations
Lecaignard, Françoise. "Predictive coding in auditory processing : insights from advanced modeling of EEG and MEG mismatch responses." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1160/document.
Full textThis thesis aims at testing the predictive coding account of auditory perception. This framework rests on precision-weighted prediction errors elicited by unexpected sounds that propagate along a hierarchical organization in order to maintain the brain adapted to a varying acoustic environment. Using the mismatch negativity (MMN), a brain response to unexpected stimuli (deviants) that could reflect such errors, we could address the computational and neurophysiological underpinnings of predictive coding. Precisely, we manipulated the predictability of deviants and applied computational learning models and dynamic causal models (DCM) to electrophysiological responses (EEG, MEG) measured simultaneously. Deviant predictability was found to modulate deviance responses, a result supporting their interpretation as prediction errors. Such effect might involve the (high-level) implicit learning of sound sequence regularities that would in turn influence auditory processing in lower hierarchical levels. Computational modeling revealed the perceptual learning of sounds, resting on temporal integration exhibiting differences induced by our predictability manipulation. In addition, DCM analysis indicated predictability changes in the synaptic connectivity established by deviance processing. These results conform predictive coding predictions regarding both deviance processing and its modulation by deviant predictability and strongly support perceptual learning of auditory regularities achieved within an auditory hierarchy. Our findings also highlight the power of this mechanistic framework to elaborate and test new hypothesis enabling to improve our understanding of auditory processing
Bonnefond, Mathilde. "Caractérisation des étapes de traitement élémentaire du raisonnement conditionnel à l’aide de l’EEG et de la MEG : effet de l’incertitude du conditionnel et des différences interindividuelles." Thesis, Lyon 2, 2009. http://www.theses.fr/2009LYO20101/document.
Full textThe conditional reasoning, based on statements of the form If P then Q, is one which has received the most attention from psychologists. The main arguments of conditional reasoning, as the Modus Ponens (MP), consist of three elements: the major premise (If P then Q), the minor premise (P) and conclusion (Q). These elements constitute three separate processing steps. However, the temporal dimension of reasoning has been partly neglected in the literature. The central objective of this thesis was to explore the temporal dimension by using an innovative approach combining the use of the measurement of premises reading time and of the electroencephalography (EEG) and magnetoencephalography ( MEG). We set three objectives: 1) Determine the sequence of processing steps of the basic argument MP 2) Determine how the uncertainty of a conditional theme is taken into account, 3) Highlight the interindividual differences in treatment a conditional statement, or basic theme by introducing the study of the AC argument, which allows to separate two populations: individuals who accept the conclusion of AC and individuals who reject it. The data reveals that all individuals have a tendency to focus more on P and Q in the processing of the conditional, with varying degrees in different individuals. When the premise P (or Q for participants that accept AC) is presented, it is integrated with the major premise to generate a conclusion Q encoded and stored in working memory before being compared with the conclusions presented. When the conditional is uncertain (Thematic conditional), this uncertainty about the sufficiency of P for Q (or Q for P) seems to be taken into account by the subjects at the major premise and is manifested by an less pronounced expectation of Q conclusion when the premise P has been presented
Dupré, la Tour Tom. "Nonlinear models for neurophysiological time series." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLT018.
Full textIn neurophysiological time series, strong neural oscillations are observed in the mammalian brain, and the natural processing tools are thus centered on narrow-band linear filtering.As this approach is too reductive, we propose new methods to represent these signals.We first focus on the study of phase-amplitude coupling (PAC), which consists in an amplitude modulation of a high frequency band, time-locked with a specific phase of a slow neural oscillation.We propose to use driven autoregressive models (DAR), to capture PAC in a probabilistic model. Giving a proper model to the signal enables model selection by using the likelihood of the model, which constitutes a major improvement in PAC estimation.%We first present different parametrization of DAR models, with fast inference algorithms and stability discussions.Then, we present how to use DAR models for PAC analysis, demonstrating the advantage of the model-based approach on three empirical datasets.Then, we explore different extensions to DAR models, estimating the driving signal from the data, PAC in multivariate signals, or spectro-temporal receptive fields.Finally, we also propose to adapt convolutional sparse coding (CSC) models for neurophysiological time-series, extending them to heavy-tail noise distribution and multivariate decompositions. We develop efficient inference algorithms for each formulation, and show that we obtain rich unsupervised signal representations
Trübutschek, Darinka. "Characterizing the neuro-cognitive architecture of non-conscious working memory." Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS101.
Full textOur lives hinge on our ability to hold information online for immediate use. For over a century, cognitive neuroscientists have regarded such working memory as closely related to consciousness, with both functions sharing similar features and brain mechanisms. Recent work has challenged this view, demonstrating that non-conscious information may affect behavior for several seconds, and suggesting that there exists a genuine non-conscious working memory system. I here combine behavioral and modeling approaches with time-resolved magnetoencephalography and multivariate pattern analysis to put this proposal to the test. In a first study, I rule out alternative explanations for the long-lasting blindsight effect, showing that it results from a genuinely non-conscious process. Crucially, this non-conscious maintenance is not accompanied by persistent delay-period activity, but instead stores information in “activity-silent” brain states via transient changes in synaptic weights. In a second set of experiments, I systematically evaluate key properties of conscious working memory in the context of long-lasting blindsight. While even multiple items and their temporal order may be stored non-consciously, manipulating stored representations is associated with consciousness and sustained neural activity. Together, these results challenge theories that equate the maintenance of information in working memory with conscious activity sustained throughout the delay period, but also contradict the notion of a genuine non-conscious “working” memory. Instead, I propose the existence of activity-silent short-term memory
Papadopoulo, Théodore. "Contributions and perspectives to computer vision, image processing and EEG/MEG data analysis." Habilitation à diriger des recherches, Université Nice Sophia Antipolis, 2011. http://tel.archives-ouvertes.fr/tel-00847782.
Full textMaksymenko, Kostiantyn. "Nouvelles approches algorithmiques pour les problèmes directs et inverses en M/EEG." Thesis, Université Côte d'Azur (ComUE), 2019. http://www.theses.fr/2019AZUR4112.
Full textMagneto- and Electro-encephalography (M/EEG) are two non-invasive functional imaging modalities which measure the electromagnetic activity of the brain. These tools are used in cognitive studies as well as in clinical applications as, for example, epilepsy. Besides the presentation of some background material about the M/EEG modalities, this thesis describes two main contributions. The first one is a method for a fast approximation of a set of EEG forward problem solutions, parametrized by tissue conductivity values. This forward problem consists in computing how a specific cortical activity would be measured by EEG sensors. The main advantage of our method is that it significantly accelerates the computation time, while controlling the approximation error. Head tissue conductivity values vary across subjects and it might be interesting to estimate them from the EEG data. Our method is an important step towards an efficient solution of such a head tissues conductivity estimation problem. The second contribution is a novel source reconstruction method, which estimates extended cortical sources explaining the M/EEG measurements. The main originality of the method is that instead of providing a unique reconstruction, as the majority of the state-of-the-art methods do, it proposes several equally valid candidates. We validated both our contributions on simulated and real M/EEG data
Belaoucha, Brahim. "Utilisation de l’IRM de diffusion pour la reconstruction de réseaux d’activations cérébrales à partir de données MEG/EEG." Thesis, Université Côte d'Azur (ComUE), 2017. http://www.theses.fr/2017AZUR4027/document.
Full textUnderstanding how brain regions interact to perform a given task is a very challenging task. Electroencephalography (EEG) and Magnetoencephalography (MEG) are two non-invasive functional imaging modalities used to record brain activity with high temporal resolution. As estimating brain activity from these measurements is an ill-posed problem. We thus must set a prior on the sources to obtain a unique solution. It has been shown in previous studies that structural homogeneity of brain regions reflect their functional homogeneity. One of the main goals of this work is to use this structural information to define priors to constrain more anatomically the MEG/EEG source reconstruction problem. This structural information is obtained using diffusion magnetic resonance imaging (dMRI), which is, as of today, the unique non-invasive structural imaging modality that provides an insight on the structural organization of white matter. This makes its use to constrain the EEG/MEG inverse problem justified. In our work, dMRI information is used to reconstruct brain activation in two ways: (1) In a spatial method which uses brain parcels to constrain the sources activity. These parcels are obtained by our whole brain parcellation algorithm which computes cortical regions with the most structural homogeneity with respect to a similarity measure. (2) In a spatio-temporal method that makes use of the anatomical connections computed from dMRI to constrain the sources’ dynamics. These different methods are validated using synthetic and real data
N'Diaye, Karim. "Dynamique et topographie des réseaux neuronaux corticaux impliqués dans la perception du temps." Paris 6, 2006. http://www.theses.fr/2006PA066393.
Full textPhilippe, Anne-Charlotte. "Régularisation du problème inverse MEG par IRM de diffusion." Phd thesis, Université Nice Sophia Antipolis, 2013. http://tel.archives-ouvertes.fr/tel-00939159.
Full textPark, Hyeongdong. "Brain-body interactions in conscious experience : linking subjectivity, neural maps of visceral organs, and visual consciousness." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066055.
Full textReporting “I saw the stimulus” is the hallmark of conscious vision and implies two fundamental characteristics of conscious experience, namely qualitativeness and subjectivity. Qualitativeness refers to the vivid feeling of the stimulus, whereas subjectivity refers to the implicit awareness that the experience occurred for me. To account for the neural basis of subjectivity, we introduce a concept termed the neural subjective frame which corresponds to the basic biological mechanisms defining the subject as a biological entity, as an anchoring point from which the first-person statements of conscious experience can be expressed. I further propose that neural representation of visceral information could constitute the neural subjective frame. To experimentally test this proposal, using magnetoencephalography, we recorded neural events locked to heartbeats while participants conducted visual detection task. We found that neural responses to heartbeats before stimulus onset in ventral anterior cingulate and right posterior intraparietal lobule could predict the detection of faint visual stimulus. Larger amplitude of neural responses to heartbeats were accompanied by enhanced hit-rate and sensitivity, but without changes in decision criterion. Neither fluctuations in measured bodily parameters nor in overall cortical excitability could account for this finding. In addition, consciously seeing the stimulus decelerated heartbeat after participants responded and the heartbeat slowing effect could be predicted from the prestimulus neural responses to heartbeats in ventral anterior cingulate cortex. Our findings therefore support the hypothesis that neural mapping of visceral afferents shape perceptual subjective experience. Beyond conscious vision, our findings suggest that signals from internal body and their neural representations could be sources of fluctuations in multi-functional cortical areas
Adde, Geoffray. "Méthodes de traitement d'image appliquées au problème inverse en magnéto-électro-encéphalographie." Marne-la-vallée, ENPC, 2005. https://pastel.archives-ouvertes.fr/pastel-00001593.
Full textJmail, Nawel. "Séparation des activités cérébrales phasiques et oscillatoires en MEG, EEG et EEG intracérébral." Thesis, Aix-Marseille, 2012. http://www.theses.fr/2012AIXM5013/document.
Full textThe Oscillatory activities play a leading role in the development of healthy and pathological brain networks. In particular, at the clinical level, the oscillatory activities are of great importance in the diagnostic of epilepsy. In addition, the non-invasive electrophysiology methods are particularly suitable for understanding the large-scale brain networks. However, most studies in epilepsy have been directed to the interictal spikes, which are transitional activities. One issue that remains unresolved is the relationship between epileptic spikes and epileptic oscillatory activities. This thesis resolves two complementary problems. The first one is the suitable separation between the oscillatory and transitory activity, which is quite sensitive to the presence of the overlap in the time-frequency domain. This can lead to a contamination between the activities. We did evaluate three filtering methods: the FIR (classic methods), the stationary wavelet SWT and the parsimonious filter with the matching pursuit MP. The SWT gave good results in the reconstruction of transient activity and the MP in the reconstruction of oscillatory activity both for simulated data; also they provide a low false positive in automatic detection of oscillatory activity. The SWT and FIR gave the best results on real signals especially for source localization. In the simulated data, the MP is optimal since the atoms of the dictionary resembles to the simulated signals, which isn't guaranteed for real signals. The second problem is the comparison between network connectivity of transient and oscillatory activity, as measured in surface recordings (MEG) and invasive recordings SEEG
Abboud, Sami. "Les fonctions cognitives du cortex visuel dans la cécité précoce." Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS038/document.
Full textBlindness early in life leads to major changes in the functional architecture of the brain. The occipital lobes, no longer processing visual information, turn to processing auditory and tactile input and high-order cognitive functions such as language and memory. This functional reorganization offers a window into the influence of experience on brain development in humans. We studied the outcomes of this reorganization and its potential precursors. First, we used functional magnetic resonance imaging (fMRI) in order to delineate regions in the visual cortex according to their sensitivity to high-order cognitive functions. Then, using functional connectivity, we demonstrated distinct connections from those regions to the rest of the brain. Crucially, we found a functional correspondence between the visual regions and their connected brain networks. Then, using functional connectivity in neonates, we provided preliminary evidence in support of the proposition that innate connectivity biases underlie functional reorganization. Second, we focused on language, one of the reorganized functions in blindness, and used magnetoencephalography (MEG) to investigate verbal semantic processing. We found temporally equivalent but spatially different activation across the blind and the sighted. In the blind, the occipital cortex had a unique contribution to semantic category discrimination. However, the cerebral implementation of semantic categories was more variable in the blind than in the sighted. Our results advance the knowledge about brain
Bonini, Francesca. "Le rôle du cortex frontal médian dans la supervision de l'action chez l'homme : études électrophysiologiques." Thesis, Aix-Marseille, 2016. http://www.theses.fr/2016AIXM5023/document.
Full textThe capacity to evaluate the outcome of our actions is fundamental for adapting and optimizing behaviour. This capability depends on an action monitoring system in charge of assessing ongoing actions, detecting errors, and evaluating outcomes.Electrical brain activity evoked by negative outcomes is thought to originate within the medial part of the frontal cortex. Nonetheless, the underlying neuronal network is incompletely characterised in humans.In the two first studies, we investigated the anatomical substrates of action monitoring in humans using intracerebral local field potential (LFP) recordings of cerebral cortex from epileptic patients. Response evoked LFPs sensitive to outcome were recorded from the Supplementary Motor Area proper (SMA), while LFPs evoked exclusively by errors were recorded later in the medial prefrontal cortex. High-gamma-frequency activity (60-180 Hz) was modulated as a function of action outcome in a vast frontal and extra-frontal network.In a third study using simultaneous recording of electroencephalography (EEG) and magnetoencephalography (MEG), we found that error related activity was detected by EEG (but not by MEG), while feedback-related activity was detected by MEG, indicating that the sources of these two forms of outcome-modulated brain activity are different.To conclude the SMA is much more involved in action monitoring than previously thought. SMA rapidly and continuously assesses ongoing actions and likely engages more rostral prefrontal structures in the case of error. Processing of action errors and of negative externally delivered feedback therefore appears to be supported by distinct cortical networks
Chen, Sophie. "Implication de l'AMS dans le contrôle précis de la force par la préhension pouce-index. : Exploration du couplage fonctionnel corticomusculaire avec l'EEG et la MEG couplées à l'EMG et des réponses musculaires à la TMS." Thesis, Aix-Marseille, 2013. http://www.theses.fr/2013AIXM5085/document.
Full textThe human hand's opposable thumb plays a large role in human behavior, allowing for a grip far more precise than that of monkeys with opposable thumbs. However, it isn't well understood how the brain controls the hands in such a precise way. In these studies, we investigate how different parts of the brain dedicated to motor tasks, in particular the motor cortex (M1) and the supplementary motor area (SMA), contribute to a precise thumb-index finger grip. Our experiments suggest that some neurons in the SMA, in addition to those well-described in M1, may connect directly to the motoneurons in the spinal cord controlling the hand muscles. Moreover, we found that SMA communicates with the hand muscles as efficiently as M1, while in monkeys, SMA communicates less efficiently than M1. This functional difference in the SMA-muscles pathway between monkey and human may account for the higher capacity of the latter to precisely control the force produced by digits
Afdideh, Fardin. "Block-sparse models in multi-modality : application to the inverse model in EEG/MEG." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAT074/document.
Full textThree main challenges have been addressed in this thesis, in three chapters.First challenge is about the ineffectiveness of some classic methods in high-dimensional problems. This challenge is partially addressed through the idea of clustering the coherent parts of a dictionary based on the proposed characterisation, in order to create more incoherent atomic entities in the dictionary, which is proposed as a block structure identification framework. The more incoherent atomic entities, the more improvement in the exact recovery conditions. In addition, we applied the mentioned clustering idea to real-world EEG/MEG leadfields to segment the brain source space, without using any information about the brain sources activity and EEG/MEG signals. Second challenge raises when classic recovery conditions cannot be established for the new concept of constraint, i.e., block-sparsity. Therefore, as the second research orientation, we developed a general framework for block-sparse exact recovery conditions, i.e., four theoretical and one algorithmic-dependent conditions, which ensure the uniqueness of the block-sparse solution of corresponding weighted mixed-norm optimisation problem in an underdetermined system of linear equations. The mentioned generality of the framework is in terms of the properties of the underdetermined system of linear equations, extracted dictionary characterisations, optimisation problems, and ultimately the recovery conditions. Finally, the combination of different information of a same phenomenon is the subject of the third challenge, which is addressed in the last part of dissertation with application to brain source space segmentation. More precisely, we showed that by combining the EEG and MEG leadfields and gaining the electromagnetic properties of the head, more refined brain regions appeared
Kosem, Anne. "Cortical oscillations as temporal reference frames for perception." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2014. http://tel.archives-ouvertes.fr/tel-01069219.
Full textAdde, Geoffray. "Méthodes de Traitement d'Image Appliquées au Problème Inverse en Magnéto-Electro-Encéphalographie." Phd thesis, Ecole des Ponts ParisTech, 2005. http://pastel.archives-ouvertes.fr/pastel-00001593.
Full textZilber, Nicolas. "ERF and scale-free analyses of source-reconstructed MEG brain signals during a multisensory learning paradigm." Phd thesis, Université Paris Sud - Paris XI, 2014. http://tel.archives-ouvertes.fr/tel-00984990.
Full textDubarry, Anne-Sophie. "Linking neurophysiological data to cognitive functions : methodological developments and applications." Thesis, Aix-Marseille, 2016. http://www.theses.fr/2016AIXM5017.
Full textA major issue in Cognitive Psychology is to describe human cognitive functions. From the Neuroscientific perceptive, measurements of brain activity are collected and processed in order to grasp, at their best resolution, the relevant spatio-temporal features of the signal that can be linked with cognitive operations. The work of this thesis consisted in designing and implementing strategies in order to overcome spatial and temporal limitations of signal processing procedures used to address cognitive issues. In a first study we demonstrated that the distinction between picture naming classical temporal organizations serial-parallel, should be addressed at the level of single trials and not on the averaged signals. We designed and conducted the analysis of SEEG signals from 5 patients to show that the temporal organization of picture naming involves a parallel processing architecture to a limited degree only. In a second study, we combined SEEG, EEG and MEG into a simultaneous trimodal recording session. A patient was presented with a visual stimulation paradigm while the three types of signals were simultaneously recorded. Averaged activities at the sensor level were shown to be consistent across the three techniques. More importantly a fine-grained coupling between the amplitudes of the three recording techniques is detected at the level of single evoked responses. This thesis proposes various relevant methodological and conceptual developments. It opens up several perspectives in which neurophysiological signals shall better inform Cognitive Neuroscientific theories
Abdelaziz, Batoul. "Direct algorithms for solving some inverse source problems." Thesis, Compiègne, 2014. http://www.theses.fr/2014COMP1956/document.
Full textThis thesis deals with inverse source problems in 2 cases : stationary sources in 2D and 3D elliptic equations and a non-stationary source in a diffusion equation. the main form of sources considered are pointwise sources (monopoles, dipoles and multipolar sources) having compact support within a finite number of small subdomains modeling EEG/MEG problems and Bioluminescence Tomography (BLT) problems. The purpose o this thesis is mainly to propose robust identification methods that enable us to reconstruct the number, the intensity and the location of the sources. Direct algebraic methods are used to identify the stationary siurces and a quasi-algebraic method mixed with an optimieation method is employed to recover sources with time-variable intensities. Numerical results are shown to prove the robustness of our identification algorithms
Rastelli, Federica. "Attention et conscience : étude comportementale et magnétoencéphalographique de la négligence spatiale unilatérale." Paris 6, 2007. http://www.theses.fr/2007PA066497.
Full textOswald, Victor. "Corrélats neuronaux de la mémoire de travail en magnétoencéphalographie à l’état de repos." Thèse, 2015. http://hdl.handle.net/1866/13899.
Full textLacombe, Jacinthe. "Substrats neuronaux du traitement visuel et sémantique des mots dans le vieillissement normal : apports de la MEG." Thèse, 2014. http://hdl.handle.net/1866/11929.
Full textWhile it has long been assumed that the organization of the brain network underlying semantic processing remains intact in normal aging, mainly due to older adults’ intact behavioral performance on semantic tasks, several recent studies suggest that brain changes underlying semantic processing operate during aging. These changes appear to affect mainly the brain regions responsible for the executive aspects of semantic memory (SM), involved in semantic search and selection processes, as well as the strategic manipulation of semantic knowledge. However, the specific mechanisms underlying cerebral reorganization of semantic processing in normal aging are not well understood, partly because of methodological differences among studies. Recent literature also suggests that brain changes may be observed in relation to visual perceptual aspects of word processing in older adults. Since reading words is a dynamic interactive process between low-level perceptual functions and higher-order processes such as semantic processing, there may be age-related changes in terms of brain interactions between perceptual and semantic aspects of word processing. The general aim of this thesis was to characterize the cortical changes and the time course of brain signal associated with semantic and perceptual processing of words, as well as the modulations between semantic and perceptual processes in normal aging, using magnetoencephalography (MEG) as the investigative method. Firstly (Chapter 2), the patterns of brain activation of two groups of healthy younger and older adults were compared relative to a semantic task participants carried out during MEG acquisition, by focusing on the signal around the N400, a component associated with semantic processing. The results indicate that brain changes associated with normal aging mainly affect structures involved in the executive aspects of semantic processing. Greater activation was observed in prefrontal cortex for younger relative to older adults, while the latter group of participants activated the temporoparietal region to a greater extent than young adults. Moreover, the left anterior temporal lobe (ATL), considered to be a central and amodal region of semantic processing, was also more activated by older than younger participants. Secondly (Chapter 3), specific patterns of brain activation of younger and healthy older adults were compared in relation to visual perceptual processing, by focusing on the 200 first milliseconds of cortical signal during word processing. The results show that the age-related brain changes affect the fusiform gyrus, as well as the semantic network, with greater activation found in these regions in the group of older participants relative to younger participants, while no difference in activation of the visual extrastriate cortex was found between groups. The theoretical implications of the results of these two studies are discussed. Finally, limitations of this thesis and future perspectives are addressed (Chapter 4).
Alamian, Golnoush. "Investigation of neural activity in Schizophrenia during resting-state MEG : using non-linear dynamics and machine-learning to shed light on information disruption in the brain." Thesis, 2020. http://hdl.handle.net/1866/25254.
Full textPsychiatric disorders affect nearly a quarter of the world’s population. These typically bring about debilitating behavioural, functional and/or cognitive problems, for which the underlying neural mechanisms are poorly understood. These symptoms can significantly reduce the quality of life of affected individuals, impact those close to them, and bring on an economic burden on society. Hence, targeting the baseline neurophysiology associated with psychopathologies, by identifying more robust biomarkers, would improve the development of effective treatments. The first goal of this thesis is thus to contribute to a better characterization of neural dynamic alterations in mental health illnesses, specifically in schizophrenia and mood disorders. Accordingly, the first chapter of this thesis presents two systematic literature reviews, which investigate the resting-state changes in brain connectivity in schizophrenia, depression and bipolar disorder patients. Great strides have been made in neuroimaging research in identifying alterations in functional connectivity. However, these two reviews reveal a gap in the knowledge about the temporal basis of the neural mechanisms involved in the disruption of information integration in these pathologies, particularly in schizophrenia. Therefore, the second goal of this thesis is to characterize the baseline temporal neural alterations of schizophrenia. We present two studies for which we hypothesize that the resting temporal dysconnectivity could serve as a key biomarker in schizophrenia. These studies explore temporal integration deficits in schizophrenia by quantifying neural alterations of scale-free dynamics using resting-state magnetoencephalography (MEG) data. Specifically, we use (1) long-range temporal correlation (LRTC) analysis on oscillatory activity and (2) multifractal analysis on arrhythmic brain activity. In addition, we develop classification models (based on supervised machine-learning) to detect the cortical and sub-cortical features that allow for a robust division of patients and healthy controls. Given that these studies are based on MEG spontaneous brain activity, recorded at rest with either eyes-open or eyes-closed, we then explored the possibility of finding a distinctive feature that would combine both types of resting-state recordings. Thus, the third study investigates whether alterations in spectral amplitude between eyes-open and eyes-closed conditions can be used as a possible marker for schizophrenia. Overall, the three studies show changes in the scale-free dynamics of schizophrenia patients at rest that suggest a deterioration of the temporal processing of information in patients, which might relate to their cognitive and behavioural symptoms. The multimodal approach of this thesis, combining MEG, non-linear analyses and machine-learning, improves the characterization of the resting spatiotemporal neural organization of schizophrenia patients and healthy controls. Our findings provide new evidence for the temporal dysconnectivity hypothesis in schizophrenia. The results extend on previous studies by characterizing scale-free properties of deep brain structures and applying advanced non-linear metrics that are underused in the field of psychiatry. The results of this thesis contribute significantly to the identification of novel biomarkers in schizophrenia and show the importance of clarifying the temporal properties of altered intrinsic neural dynamics. Moreover, the presented studies offer a methodological framework that can be extended to other psychopathologies, such as depression.