46 research outputs found

    State dependency of inhibitory control performance: an electrical neuroimaging study

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    Behavioral and brain responses to stimuli not only depend on their physical features but also on the individuals' neurocognitive states before stimuli onsets. While the influence of pre-stimulus fluctuations in brain activity on low-level perceptive processes is well established, the state dependency of high-order executive processes remains unclear. Using a classical inhibitory control Go/NoGo task, we examined whether and how fluctuations in the brain activity during the period preceding the stimuli triggering inhibition influenced inhibitory control performance. Seventeen participants completed the Go/NoGo task while 64-channel electroencephalogram was recorded. We compared the event-related potentials preceding the onset of the NoGo stimuli associated with inhibition failures false alarms (FA) vs. successful inhibition correct rejections (CR) with data-driven statistical analyses of global measures of the topography and strength of the scalp electric field. Distributed electrical source estimations were used to localize the origin of the event-related potentials modulations. We observed differences in the global field power of the event-related potentials (FA > CR) without concomitant topographic modulations over the 40 ms period immediately preceding NoGo stimuli. This result indicates that the same brain networks were engaged in the two conditions, but more strongly before FA than CR. Source estimations revealed that this effect followed from a higher activity before FA than CR within bilateral inferior frontal gyri and the right inferior parietal lobule. These findings suggest that uncontrolled quantitative variations in pre-stimulus activity within attentional and control brain networks influence inhibition performance. The present data thereby demonstrate the state dependency of cognitive processes of up to high- order executive levels

    Grabbing your ear: rapid auditory-somatosensory multisensory interactions in low-level sensory cortices are not constrained by stimulus alignment.

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    Multisensory interactions are observed in species from single-cell organisms to humans. Important early work was primarily carried out in the cat superior colliculus and a set of critical parameters for their occurrence were defined. Primary among these were temporal synchrony and spatial alignment of bisensory inputs. Here, we assessed whether spatial alignment was also a critical parameter for the temporally earliest multisensory interactions that are observed in lower-level sensory cortices of the human. While multisensory interactions in humans have been shown behaviorally for spatially disparate stimuli (e.g. the ventriloquist effect), it is not clear if such effects are due to early sensory level integration or later perceptual level processing. In the present study, we used psychophysical and electrophysiological indices to show that auditory-somatosensory interactions in humans occur via the same early sensory mechanism both when stimuli are in and out of spatial register. Subjects more rapidly detected multisensory than unisensory events. At just 50 ms post-stimulus, neural responses to the multisensory 'whole' were greater than the summed responses from the constituent unisensory 'parts'. For all spatial configurations, this effect followed from a modulation of the strength of brain responses, rather than the activation of regions specifically responsive to multisensory pairs. Using the local auto-regressive average source estimation, we localized the initial auditory-somatosensory interactions to auditory association areas contralateral to the side of somatosensory stimulation. Thus, multisensory interactions can occur across wide peripersonal spatial separations remarkably early in sensory processing and in cortical regions traditionally considered unisensory

    Grabbing Your Ear: Rapid Auditory-Somatosensory Multisensory Interactions in Low-level Sensory Cortices Are Not Constrained by Stimulus Alignment

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    Multisensory interactions are observed in species from single-cell organisms to humans. Important early work was primarily carried out in the cat superior colliculus and a set of critical parameters for their occurrence were defined. Primary among these were temporal synchrony and spatial alignment of bisensory inputs. Here, we assessed whether spatial alignment was also a critical parameter for the temporally earliest multisensory interactions that are observed in lower-level sensory cortices of the human. While multisensory interactions in humans have been shown behaviorally for spatially disparate stimuli (e.g. the ventriloquist effect), it is not clear if such effects are due to early sensory level integration or later perceptual level processing. In the present study, we used psychophysical and electrophysiological indices to show that auditory-somatosensory interactions in humans occur via the same early sensory mechanism both when stimuli are in and out of spatial register. Subjects more rapidly detected multisensory than unisensory events. At just 50 ms post-stimulus, neural responses to the multisensory ‘whole' were greater than the summed responses from the constituent unisensory ‘parts'. For all spatial configurations, this effect followed from a modulation of the strength of brain responses, rather than the activation of regions specifically responsive to multisensory pairs. Using the local auto-regressive average source estimation, we localized the initial auditory-somatosensory interactions to auditory association areas contralateral to the side of somatosensory stimulation. Thus, multisensory interactions can occur across wide peripersonal spatial separations remarkably early in sensory processing and in cortical regions traditionally considered unisensor

    Conventional and Reciprocal Approaches to the Forward and Inverse Problems of Electroencephalography

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    Le problĂšme inverse en Ă©lectroencĂ©phalographie (EEG) est la localisation de sources de courant dans le cerveau utilisant les potentiels de surface sur le cuir chevelu gĂ©nĂ©rĂ©s par ces sources. Une solution inverse implique typiquement de multiples calculs de potentiels de surface sur le cuir chevelu, soit le problĂšme direct en EEG. Pour rĂ©soudre le problĂšme direct, des modĂšles sont requis Ă  la fois pour la configuration de source sous-jacente, soit le modĂšle de source, et pour les tissues environnants, soit le modĂšle de la tĂȘte. Cette thĂšse traite deux approches bien distinctes pour la rĂ©solution du problĂšme direct et inverse en EEG en utilisant la mĂ©thode des Ă©lĂ©ments de frontiĂšres (BEM): l’approche conventionnelle et l’approche rĂ©ciproque. L’approche conventionnelle pour le problĂšme direct comporte le calcul des potentiels de surface en partant de sources de courant dipolaires. D’un autre cĂŽtĂ©, l’approche rĂ©ciproque dĂ©termine d’abord le champ Ă©lectrique aux sites des sources dipolaires quand les Ă©lectrodes de surfaces sont utilisĂ©es pour injecter et retirer un courant unitaire. Le produit scalaire de ce champ Ă©lectrique avec les sources dipolaires donne ensuite les potentiels de surface. L’approche rĂ©ciproque promet un nombre d’avantages par rapport Ă  l’approche conventionnelle dont la possibilitĂ© d’augmenter la prĂ©cision des potentiels de surface et de rĂ©duire les exigences informatiques pour les solutions inverses. Dans cette thĂšse, les Ă©quations BEM pour les approches conventionnelle et rĂ©ciproque sont dĂ©veloppĂ©es en utilisant une formulation courante, la mĂ©thode des rĂ©sidus pondĂ©rĂ©s. La rĂ©alisation numĂ©rique des deux approches pour le problĂšme direct est dĂ©crite pour un seul modĂšle de source dipolaire. Un modĂšle de tĂȘte de trois sphĂšres concentriques pour lequel des solutions analytiques sont disponibles est utilisĂ©. Les potentiels de surfaces sont calculĂ©s aux centroĂŻdes ou aux sommets des Ă©lĂ©ments de discrĂ©tisation BEM utilisĂ©s. La performance des approches conventionnelle et rĂ©ciproque pour le problĂšme direct est Ă©valuĂ©e pour des dipĂŽles radiaux et tangentiels d’excentricitĂ© variable et deux valeurs trĂšs diffĂ©rentes pour la conductivitĂ© du crĂąne. On dĂ©termine ensuite si les avantages potentiels de l’approche rĂ©ciproquesuggĂ©rĂ©s par les simulations du problĂšme direct peuvent ĂȘtres exploitĂ©s pour donner des solutions inverses plus prĂ©cises. Des solutions inverses Ă  un seul dipĂŽle sont obtenues en utilisant la minimisation par mĂ©thode du simplexe pour Ă  la fois l’approche conventionnelle et rĂ©ciproque, chacun avec des versions aux centroĂŻdes et aux sommets. Encore une fois, les simulations numĂ©riques sont effectuĂ©es sur un modĂšle Ă  trois sphĂšres concentriques pour des dipĂŽles radiaux et tangentiels d’excentricitĂ© variable. La prĂ©cision des solutions inverses des deux approches est comparĂ©e pour les deux conductivitĂ©s diffĂ©rentes du crĂąne, et leurs sensibilitĂ©s relatives aux erreurs de conductivitĂ© du crĂąne et au bruit sont Ă©valuĂ©es. Tandis que l’approche conventionnelle aux sommets donne les solutions directes les plus prĂ©cises pour une conductivitĂ© du crĂąne supposĂ©ment plus rĂ©aliste, les deux approches, conventionnelle et rĂ©ciproque, produisent de grandes erreurs dans les potentiels du cuir chevelu pour des dipĂŽles trĂšs excentriques. Les approches rĂ©ciproques produisent le moins de variations en prĂ©cision des solutions directes pour diffĂ©rentes valeurs de conductivitĂ© du crĂąne. En termes de solutions inverses pour un seul dipĂŽle, les approches conventionnelle et rĂ©ciproque sont de prĂ©cision semblable. Les erreurs de localisation sont petites, mĂȘme pour des dipĂŽles trĂšs excentriques qui produisent des grandes erreurs dans les potentiels du cuir chevelu, Ă  cause de la nature non linĂ©aire des solutions inverses pour un dipĂŽle. Les deux approches se sont dĂ©montrĂ©es Ă©galement robustes aux erreurs de conductivitĂ© du crĂąne quand du bruit est prĂ©sent. Finalement, un modĂšle plus rĂ©aliste de la tĂȘte est obtenu en utilisant des images par resonace magnĂ©tique (IRM) Ă  partir desquelles les surfaces du cuir chevelu, du crĂąne et du cerveau/liquide cĂ©phalorachidien (LCR) sont extraites. Les deux approches sont validĂ©es sur ce type de modĂšle en utilisant des vĂ©ritables potentiels Ă©voquĂ©s somatosensoriels enregistrĂ©s Ă  la suite de stimulation du nerf mĂ©dian chez des sujets sains. La prĂ©cision des solutions inverses pour les approches conventionnelle et rĂ©ciproque et leurs variantes, en les comparant Ă  des sites anatomiques connus sur IRM, est encore une fois Ă©valuĂ©e pour les deux conductivitĂ©s diffĂ©rentes du crĂąne. Leurs avantages et inconvĂ©nients incluant leurs exigences informatiques sont Ă©galement Ă©valuĂ©s. Encore une fois, les approches conventionnelle et rĂ©ciproque produisent des petites erreurs de position dipolaire. En effet, les erreurs de position pour des solutions inverses Ă  un seul dipĂŽle sont robustes de maniĂšre inhĂ©rente au manque de prĂ©cision dans les solutions directes, mais dĂ©pendent de l’activitĂ© superposĂ©e d’autres sources neurales. Contrairement aux attentes, les approches rĂ©ciproques n’amĂ©liorent pas la prĂ©cision des positions dipolaires comparativement aux approches conventionnelles. Cependant, des exigences informatiques rĂ©duites en temps et en espace sont les avantages principaux des approches rĂ©ciproques. Ce type de localisation est potentiellement utile dans la planification d’interventions neurochirurgicales, par exemple, chez des patients souffrant d’épilepsie focale rĂ©fractaire qui ont souvent dĂ©jĂ  fait un EEG et IRM.The inverse problem of electroencephalography (EEG) is the localization of current sources within the brain using surface potentials on the scalp generated by these sources. An inverse solution typically involves multiple calculations of scalp surface potentials, i.e., the EEG forward problem. To solve the forward problem, models are needed for both the underlying source configuration, the source model, and the surrounding tissues, the head model. This thesis treats two distinct approaches for the resolution of the EEG forward and inverse problems using the boundary-element method (BEM): the conventional approach and the reciprocal approach. The conventional approach to the forward problem entails calculating the surface potentials starting from source current dipoles. The reciprocal approach, on the other hand, first solves for the electric field at the source dipole locations when the surface electrodes are reciprocally energized with a unit current. A scalar product of this electric field with the source dipoles then yields the surface potentials. The reciprocal approach promises a number of advantages over the conventional approach, including the possibility of increased surface potential accuracy and decreased computational requirements for inverse solutions. In this thesis, the BEM equations for the conventional and reciprocal approaches are developed using a common weighted-residual formulation. The numerical implementation of both approaches to the forward problem is described for a single-dipole source model. A three-concentric-spheres head model is used for which analytic solutions are available. Scalp potentials are calculated at either the centroids or the vertices of the BEM discretization elements used. The performance of the conventional and reciprocal approaches to the forward problem is evaluated for radial and tangential dipoles of varying eccentricities and two widely different skull conductivities. We then determine whether the potential advantages of the reciprocal approach suggested by forward problem simulations can be exploited to yield more accurate inverse solutions. Single-dipole inverse solutions are obtained using simplex minimization for both the conventional and reciprocal approaches, each with centroid and vertex options. Again, numerical simulations are performed on a three-concentric-spheres model for radial and tangential dipoles of varying eccentricities. The inverse solution accuracy of both approaches is compared for the two different skull conductivities and their relative sensitivity to skull conductivity errors and noise is assessed. While the conventional vertex approach yields the most accurate forward solutions for a presumably more realistic skull conductivity value, both conventional and reciprocal approaches exhibit large errors in scalp potentials for highly eccentric dipoles. The reciprocal approaches produce the least variation in forward solution accuracy for different skull conductivity values. In terms of single-dipole inverse solutions, conventional and reciprocal approaches demonstrate comparable accuracy. Localization errors are low even for highly eccentric dipoles that produce large errors in scalp potentials on account of the nonlinear nature of the single-dipole inverse solution. Both approaches are also found to be equally robust to skull conductivity errors in the presence of noise. Finally, a more realistic head model is obtained using magnetic resonance imaging (MRI) from which the scalp, skull, and brain/cerebrospinal fluid (CSF) surfaces are extracted. The two approaches are validated on this type of model using actual somatosensory evoked potentials (SEPs) recorded following median nerve stimulation in healthy subjects. The inverse solution accuracy of the conventional and reciprocal approaches and their variants, when compared to known anatomical landmarks on MRI, is again evaluated for the two different skull conductivities. Their respective advantages and disadvantages including computational requirements are also assessed. Once again, conventional and reciprocal approaches produce similarly small dipole position errors. Indeed, position errors for single-dipole inverse solutions are inherently robust to inaccuracies in forward solutions, but dependent on the overlapping activity of other neural sources. Against expectations, the reciprocal approaches do not improve dipole position accuracy when compared to the conventional approaches. However, significantly smaller time and storage requirements are the principal advantages of the reciprocal approaches. This type of localization is potentially useful in the planning of neurosurgical interventions, for example, in patients with refractory focal epilepsy in whom EEG and MRI are often already performed

    Multimodal Integration: fMRI, MRI, EEG, MEG

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    This chapter provides a comprehensive survey of the motivations, assumptions and pitfalls associated with combining signals such as fMRI with EEG or MEG. Our initial focus in the chapter concerns mathematical approaches for solving the localization problem in EEG and MEG. Next we document the most recent and promising ways in which these signals can be combined with fMRI. Specically, we look at correlative analysis, decomposition techniques, equivalent dipole tting, distributed sources modeling, beamforming, and Bayesian methods. Due to difculties in assessing ground truth of a combined signal in any realistic experiment difculty further confounded by lack of accurate biophysical models of BOLD signal we are cautious to be optimistic about multimodal integration. Nonetheless, as we highlight and explore the technical and methodological difculties of fusing heterogeneous signals, it seems likely that correct fusion of multimodal data will allow previously inaccessible spatiotemporal structures to be visualized and formalized and thus eventually become a useful tool in brain imaging research

    Multimodal image analysis of the human brain

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    Gedurende de laatste decennia heeft de snelle ontwikkeling van multi-modale en niet-invasieve hersenbeeldvorming technologieën een revolutie teweeg gebracht in de mogelijkheid om de structuur en functionaliteit van de hersens te bestuderen. Er is grote vooruitgang geboekt in het beoordelen van hersenschade door gebruik te maken van Magnetic Reconance Imaging (MRI), terwijl Elektroencefalografie (EEG) beschouwd wordt als de gouden standaard voor diagnose van neurologische afwijkingen. In deze thesis focussen we op de ontwikkeling van nieuwe technieken voor multi-modale beeldanalyse van het menselijke brein, waaronder MRI segmentatie en EEG bronlokalisatie. Hierdoor voegen we theorie en praktijk samen waarbij we focussen op twee medische applicaties: (1) automatische 3D MRI segmentatie van de volwassen hersens en (2) multi-modale EEG-MRI data analyse van de hersens van een pasgeborene met perinatale hersenschade. We besteden veel aandacht aan de verbetering en ontwikkeling van nieuwe methoden voor accurate en ruisrobuuste beeldsegmentatie, dewelke daarna succesvol gebruikt worden voor de segmentatie van hersens in MRI van zowel volwassen als pasgeborenen. Daarenboven ontwikkelden we een geïntegreerd multi-modaal methode voor de EEG bronlokalisatie in de hersenen van een pasgeborene. Deze lokalisatie wordt gebruikt voor de vergelijkende studie tussen een EEG aanval bij pasgeborenen en acute perinatale hersenletsels zichtbaar in MRI

    Techniques for imaging small impedance changes in the human head due to neuronal depolarisation

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    A new imaging modality is being developed, which may be capable of imaging small impedance changes in the human head due to neuronal depolarization. One way to do this would be by imaging the impedance changes associated with ion channels opening in neuronal membranes in the brain during activity. The results of previous modelling and experimental studies indicated that impedance changes between 0.6%and 1.7% locally in brain grey matter when recorded at DC. This reduces by a further of 10% if measured at the surface of the head, due to distance and the effect of the resistive skull. In principle, this could be measured using Electrical Impedance Tomography (ElT) but it is close to its threshold of detectability. With the inherent limitation in the use of electrodes, this work proposed two new schemes. The first is a magnetic measurement scheme based on recording the magnetic field with Superconducting Quantum Interference Devices (SQUIDs), used in Magnetoencephalography (MEG) as a result of a non-invasive injection of current into the head. This scheme assumes that the skull does not attenuate the magnetic field. The second scheme takes into consideration that the human skull is irregular in shape, with less and varying conductivity as compared to other head tissues. Therefore, a key issue is to know through which electrodes current can be injected in order to obtain high percentage changes in surface potential when there is local conductivity change in the head. This model will enable the prediction of the current density distribution at specific regions in the brain with respect to the varying skull and local conductivities. In the magnetic study, the head was modelled as concentric spheres, and realistic head shapes to mimic the scalp, skull, Cerebrospinal Auid (CSF) and brain using the Finite Element Method (FEM). An impedance change of 1 % in a 2cm-radius spherical volume depicting the physiological change in the brain was modelled as the region of depolarisation. The magnetic field, 1 cm away from the scalp, was estimated on injecting a constant current of 100 ”A into the head from diametrically opposed electrodes. However, in the second scheme, only the realistic FEM of the head was used, which included a specific region of interest; the primary visual cortex (V1). The simulated physiological change was the variation in conductivity of V1 when neurons were assumed to be firing during a visual evoked response. A near DC current of 100 ”A was driven through possible pairs of 31 electrodes using ElT techniques. For a fixed skull conductivity, the resulting surface potentials were calculated when the whole head remained unperturbed, or when the conductivity of V1 changed by 0.6%, 1 %, and 1.6%. The results of the magnetic measurement predicted that standing magnetic field was about 10pT and the field changed by about 3fT (0.03%) on depolarization. For the second scheme, the greatest mean current density through V1 was 0.020 ± 0.005 ”Amm-2, and occurred with injection through two electrodes positioned near the occipital cortex. The corresponding maximum change in potential from baseline was 0.02%. Saline tank experiments confirmed the accuracy of the estimated standing potentials. As the noise density in a typical MEG system in the frequency band is about 7fT/√Hz, it places the change at the limit of detectability due to low signal to noise ratio. This is therefore similar to electrical recording, as in conventional ElT systems, but there may be advantages to MEG in that the magnetic field direcdy traverses the skull and instrumentation errors from the electrode-skin interface will be obviated. This has enabled the estimation of electrode positions most likely to permit recording of changes in human experiments and suggests that the changes, although tiny, may just be discernible from noise

    Development of simultaneous electroencephalography and near-infrared optical topography for applications to neurovascular coupling and neonatal seizures

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    This thesis describes the development and preliminary application of methods for performing simultaneous electroencephalography (EEG) and near-infrared (NIR) imaging of the brain. The simultaneous application of EEG and NIR imaging has many benefits because of the complementary nature of the two modalities, and has significant potential in the study of the relationship between neuronal activity and cerebral haemodynamics. This work goes beyond previous experiments which have combined EEG and limited-channel near-infrared spectroscopy by designing and implementing an arrangement which allows dense near-infrared optical topography and EEG to be performed over the same cortical area, with as simple an application method as possible. These application methods are described in detail, as is their extensive testing using novel dual-modality phantoms and an in-vivo EEG-NIR imaging experiment in a healthy adult. These methods are subsequently applied to the study of neonates in the clinical environment. An intricate EEG-NIR imaging experiment is designed and implemented in an investigation of functional activation in the healthy neonatal visual cortex. This series of experiments also acts as a further test of the suitability of our EEG-NIR imaging methods for clinical application. The results of these experiments are presented. The EEG-NIR imaging arrangement is then applied to four neurologically damaged infants in the neonatal intensive care unit, each of whom had been diagnosed with seizures. The results of these studies are presented, and a potentially significant haemodynamic feature, which is not present in agematched controls, is identified. The importance and physiological implications of our findings are discussed, as is the suitability of a combined EEG and NIR imaging approach to the study and monitoring of neonatal brain injury
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