48 research outputs found
Anisotropic EEG/MEG volume conductor modeling based on Diffusion Tensor Imaging
Die vorliegende Arbeit befasst sich mit der Volumenleitermodellierung auf
Basis der Finiten Elemente für EEG/MEG Untersuchungen unter Einbeziehung
von Anistropieinformation, die mit Hilfe der
Magnetresonanzdiffusionstensorbildgebung (MR-DTI) gewonnen wurde. Im ersten
Teil der Arbeit wurde der Einfluss unvollständig bestimmter
Wichtungsparamter (b-Matrix) auf die zu rekonstruierenden
Diffusionstensoren untersucht. Die Unvollständigkeit bezieht sich dabei auf
die Tatsache, dass im Allgemeinen nur die starken Diffusionsgradienten zur
Berechnung der b-Matrix herangezogen werden. Es wurde gezeigt, dass
besonders bei Aufnahmen mit hoher räumlicher Auflösung der Anteil der
Bildgradienten an der b-Matrix nicht mehr vernachlässigbar ist. Weiterhin
wurde gezeigt, wie man die b-Matrizen korrekt analytisch bestimmt und damit
einen systematischen Fehler vermeidet. Für den Fall, dass nicht ausreichend
Informationen zur Verfügung stehen um die analytische Bestimmung
durchzuführen, wurde eine Lösung vorgeschlagen, die es mit Hilfe von
Phantommessungen ermöglicht eine parametrisierte b-Matrix zu bestimmen. Der
zweite Teil widmet sich der Erstellung hochaufgelöster realistischer
Volumenleitermodelle detailliert beschrieben. Besonders die Transformation
der Diffusionstensordaten in Leitfähigkeitstensoren. Zudem wurde eine
Vorgehensweise beschrieben, die es erlaubt, einen T1-gewichteten
MR-Datensatz vollautomatisch in fünf verschiedene Gewebesegmente (weiches
Gewebe, graue und weiße Substanz, CSF und Schädelknochen) zu unterteilen.
Der dritte Teil der Arbeit befasst sich mit dem Einfluss der anisotropen
Leitfähigkeit in der weißen Hirnsubstanz auf EEG und MEG unter Verwendung
eines Tier- sowie eines Humanmodells. Um den Einfluss der verschiedenen
Methoden der Transformation von DTI Daten in Leitfähigkeitsdaten zu
untersuchen, wurden verschiedenen Modelle sowohl mit gemessener als auch
mit künstlicher Anisotropie erstellt. In der Tiermodellstudie wurden EEG
und in der Humanmodellstudie EEG und MEG Simulationen sowohl mit den
anisotropen Modellen als auch mit einem isotropen Modell durchgeführt und
miteinander verglichen. Dabei wurde gefunden, dass sowohl der
topographische Fehler (RDM) als auch der Magnitudenfehler stark durch das
Einbeziehen von Anisotropieinformationen beeinflusst wird. Es wurde auch
gezeigt, dass sowohl die Position als auch die Orientierung einer
dipolaren Quelle in Bezug auf das anisotrope Segment einen großen Effekt
auf die untersuchten Fehlermaße hat.In this work anisotropic electric tissue properties determined by
means of
diffusion tensor imaging were modeled into high resolution finite element
volume conductors. In first part of the work the influence of not
considering imaging gradient in the calculation of the b-matrices on the
correct determination of diffusion tensor data is shown and it was found
that especially with high resolution imaging protocols the contributions of
the imaging gradients is not negligible. It was also shown how correct
b-matrices considering all applied gradients can be calculated correctly.
For the case that information about the sequence are missing an
experimental approach of determining a parameterized b-matrix using phantom
measurements is proposed. In the second part the procedure of generating
anisotropic volume conductor models is regarded. The main focus of this
part was to facilitate the derivation of anisotropy information from DTI
measurements and the inclusion of this information into an anisotropic
volume conductor. It was shown, that it is possible to generate a
sophisticated high resolution anisotropic model without any manual steps
into five different tissue layers. The third part studied the influence of
anisotropic white matter employing an animal as well as a human model. To
compare the different ways of converting the anisotropy information from
DTI into conductivity information, different models were investigated,
having artificial as well as measured anisotropy. In the animal study the
EEG and in the human study the EEG and MEG forward solution was studies
using the anisotropic models and compared to the solution derived using an
isotropic model. It was found that both, the topography error (RDM) as well
as the magnitude error (MAG), are significantly affected if anisotropy is
considered in the volume conductor. It was also shown, that the position as
well as the orientation of the dipole with respect to white matter has a
large effect on the amount of the error quantities. Finally, it is claimed
that if one uses high resolution volume conductor models for EEG/MEG
studies, the anisotropy has to be considered, since the average error of
neglecting anisotropy is larger than the accuracy which can be achieved
using such models
Real-Time MEG Source Localization Using Regional Clustering
With its millisecond temporal resolution, Magnetoencephalography (MEG) is well suited for real-time monitoring of brain activity. Real-time feedback allows the adaption of the experiment to the subject’s reaction and increases time efficiency by shortening acquisition and off-line analysis. Two formidable challenges exist in real-time analysis: the low signal-to-noise ratio (SNR) and the limited time available for computations. Since the low SNR reduces the number of distinguishable sources, we propose an approach which downsizes the source space based on a cortical atlas and allows to discern the sources in the presence of noise. Each cortical region is represented by a small set of dipoles, which is obtained by a clustering algorithm. Using this approach, we adapted dynamic statistical parametric mapping for real-time source localization. In terms of point spread and crosstalk between regions the proposed clustering technique performs better than selecting spatially evenly distributed dipoles. We conducted real-time source localization on MEG data from an auditory experiment. The results demonstrate that the proposed real-time method localizes sources reliably in the superior temporal gyrus. We conclude that real-time source estimation based on MEG is a feasible, useful addition to the standard on-line processing methods, and enables feedback based on neural activity during the measurements.Deutsche Forschungsgemeinschaft (grant Ba 4858/1-1)National Institutes of Health (U.S.) (grants 5R01EB009048 and 2P41EB015896)Universitätsschule Jena (J21)German Academic Exchange Servic
Simulation of tangential and radial electric brain activity: different sensitivity in EEG and MEG
Based on the main direction of the neuronal currents with respect to the local skull curvature, it is common to distinguish between tangential brain activity originating mainly from the walls of the sulci and radial brain activity originating mainly from the gyri or the bottom of the sulci. It is well known that MEG is more sensitive to tangential activity while EEG is sensitive to both radial and tangential activity. Thus, it is surprising that studies in epileptic patients report cases were spikes are visible in MEG but not in EEG. Recently, it was discussed that a lower sensitivity of MEG to background activity might be the reason for the spike visibility in MEG but not in EEG. Consequently, we analyze the signalto-noise ratio (SNR) of simulated spikes at varying orientations and with varying background activity in realistic head models. For a fixed realistic background activity, we find a higher SNR for spikes in the MEG as long as the spike orientation is not more than 30 degrees deviating from the tangential direction. Vice versa the SNR for spikes in the EEG is higher as long as the spike orientation is not more than 45 degrees deviating from the radial direction. Our simulations provide a possible explanation for the experimentally observed differences in EEG and MEG signals
Neural distinctiveness of fatigue and low sleep quality in multiple sclerosis
Background and purpose
Fatigue and low sleep quality in multiple sclerosis (MS) are closely related symptoms. Here, the associations between the brain's functional connectivity (FC) and fatigue and low sleep quality were investigated to determine the degree of neural distinctiveness of these symptoms.
Method
A hundred and four patients with relapsing–remitting MS (age 38.9 ± 10.2 years, 66 females) completed the Modified Fatigue Impact Scale and the Pittsburgh Sleep Quality Index and underwent resting-state functional magnetic resonance imaging. FC was analyzed using independent-component analysis in sensorimotor, default-mode, fronto-parietal and basal-ganglia networks. Multiple linear regression models allowed us to test the association between FC and fatigue and sleep quality whilst controlling for one another as well as for demographic, disease-related and imaging variables.
Results
Higher fatigue correlated with lower sleep quality (r = 0.54, p < 0.0001). Higher fatigue was associated with lower FC of the precentral gyrus in the sensorimotor network, the precuneus in the posterior default-mode network and the superior frontal gyrus in the left fronto-parietal network, independently of sleep quality. Lower sleep quality was associated with lower FC of the left intraparietal sulcus in the left fronto-parietal network, independently of fatigue. Specific associations were found between fatigue and the sensorimotor network's global FC and between low sleep quality and the left fronto-parietal network's global FC.
Conclusion
Despite the high correlation between fatigue and low sleep quality in the clinical picture, our findings clearly indicate that, on the neural level, fatigue and low sleep quality in MS are associated with decreased FC in distinct functional brain networks