103 research outputs found
Combined EEG and MEG source analysis of epileptiform activity using calibrated realistic finite element head models
In dieser Arbeit wird eine neue Pipeline, welche die komplementären
Informationen der Elektroenzephalographie (EEG) und Magnetoenzephalographie
(MEG) berücksichtigen kann, vorgestellt und experimentell sowie methodisch
analysiert. Um das Vorwärtsproblem zu lösen, wird ein hochrealistisches
Finite-Elemente-Kopfmodell aus individuell gemessenen T1-gewichteten,
T2-gewichteten und Diffusion-Tensor (DT)-MRIs generiert. Dafür werden die
Kompartments Kopfhaut, spongioser Schädel, kompakter Schädel, Liquor
Cerebrospinalis (CSF), graue Substanz und weiße Substanz segmentiert und
ein individuelles Kopfmodell erstellt. Um eine sehr akkurate Quellenanalyse
zu garantieren werden die individuelle Kopfform, die Anisotropie der
weißen Substanz und die individuell kalibrierte Schädelleitfähigkeiten
berücksichtigt. Die Anisotropie der weißen Substanz wird anhand der
gemessenen DT-MRI Daten berechnet und in das segmentierte Kopfmodell
integriert. Da sich die Leitfähigkeit des schwach-leitenden Schädels für
verschiedene Probanden sehr stark unterscheidet und diese die Ergebnisse
der EEG Quellenanalyse stark beeinflusst, wird ein Fokus auf die
Untersuchung der Schädelleitfähigkeit gelegt. Um die individuelle
Schädelleitfähigkeit möglichst genau zu bestimmen werden simultan
gemessene somatosensorische Potentiale und Felder der Probanden verwendet
und ein Verfahren zur Kalibrierung der Schädelleitfähigkeit
durchgeführt. Wie in dieser Studie gezeigt, können individuell generierte
Kopfmodelle dazu verwendet werden um, in einem nicht-invasivem Verfahren,
interiktale Aktivität für Patienten, welche an medikamentenresistenter
Epilepsie leiden, mit einer sehr hohen Genauigkeit zu detektieren.
Außerdem werden diese akkuraten Kopfmodelle dazu verwendet um die
unterschiedlichen Sensitivitäten von EEG, MEG und einer kombinierten EEG
und MEG (EMEG) Quellenanalyse in Bezug auf verschiedene
Gewebeleitfähigkeiten zu untersuchen. Wie in dieser Studie gezeigt wird
liefert eine kombinierte EMEG Quellenanalyse zuverlässigere und robustere
Ergebnisse für die Lokalisierung epileptischer Aktivität als eine
einfache EEG oder MEG Quellenanalyse. Zuletzt werden die Auswirkungen einer
Spikemittelung sowie die Effekte verschiedener Signal-Rausch-Verhältnisse
(SNRs) anhand verschiedener Teilmittelungen untersucht.
Wie in dieser Arbeit gezeigt wird sind realistische Kopfmodelle mit
anisotroper weißer Substanz und kalibrierter Schädelleitfähigkeit nicht
nur für die EEG Quellenanalyse, sondern auch für die MEG und EMEG
Quellenanalyse vorteilhaft. Durch die Anwendung dieser akkuraten
Kopfmodelle konnte gezeigt werden, dass EMEG Quellenanalyse sehr gute
Quellenrekonstruktionen auch schon zu Beginn des epileptischen Spikes
liefert, wo nur eine sehr geringe SNR vorhanden ist. Da zu diesem Zeitpunkt
noch keine Ausbreitung der epileptischen Aktivität eingesetzt hat ist die
Lokalisation von frühen Quellen von besonderer Bedeutung. Während die
EMEG Quellenanalyse auch Ausbreitungseffekte für spätere Zeitpunkte genau
darstellen kann, können einfache EEG oder MEG Quellenanalysen diese nicht
oder nur teilweise darstellen. Die Validierung der Ausbreitung wird anhand
eines invasiv gemessenen Stereo-EEG durchgeführt. Durch die
durchgeführten Spikemittelungen und die SNR Analyse wird verdeutlicht,
dass durch eine Teilmittelung wichtige und exakte Informationen über den
Mittelpunkt sowie die Größe des epileptischen Gewebes gewonnen werden
können, welche weder durch eine einfachen noch einer "Grand-average"
Lokalisation des Spikes erreichbar sind. Eine weitere Anwendung einer
genauen EMEG Quellenanalyse ist die Bestimmung einer "region of interest"
anhand von standardisierten MRT Messungen. Diese kleinen Gebiete werden
dann später mit einer optimalen und höher aufgelösten MRT-Sequenz
gemessen. Dank dieses optimierte Verfahren können auch sehr kleine FCDs
entdeckt werden, welche auf dem standardisierten gemessenen MRT-Sequenzen
nicht erkennbar sind.
Die Pipeline, welche in dieser Arbeit entwickelt wird, kann auch für
gesunde Probanden angewendet werden. In einer ersten Studie wird eine
Quellenanalyse der somatosensorischen und auditorisch-induzierten Reize
durchgeführt. Die gewonnen Daten werden mit anderen Studien vergleichen
und mögliche Gemeinsamkeiten diskutiert. Eine weitere Anwendung der
realistischen Kopfmodelle ist die Untersuchung von Volumenleitungseffekten
in nicht-invasiven Hirnstimulationsmethoden wie transkranielle
Gleichstromstimulation und transkranielle Magnetstromstimulation.In this thesis, a new experimental and methodological analysis pipeline
for combining the complementary information contained in
electroencephalography (EEG) and magnetoencephalography (MEG) is
introduced. The forward problem is solved using high resolution finite
element head models that are constructed from individual T1 weighted, T2
weighted and diffusion tensor (DT-) MRIs. For this purpose, scalp, skull
spongiosa, skull compacta, cerebrospinal fluid, white matter (WM) and gray
matter (GM) are segmented and included into the head models. In order to
obtain highly accurate source reconstructions, the realistic geometry,
tissue conductivity anisotropy (i.e., WM tracts) and individually estimated
conductivity values are taken into account. To achieve this goal, the
brain anisotropy is modeled using the information obtained from DT-MRI. A
main focus is placed on the skull conductivity due to its high
inter-individual variance and different sensitivities of EEG and MEG source
reconstructions to it. In order to estimate individual skull conductivity
values that fit best to the constructed head models, simultaneously
acquired somatosensory evoked potential and field data measured for the
same individuals are analyzed. As shown in this work, the constructed head
models could be used to non-invasively localize interictal spike activity
in patients suffering from pharmaco-resistant focal epilepsy with higher
reliability. In addition, by using these advanced head models, tissue
sensitivities of EEG, MEG and combined EEG/MEG (EMEG) are compared by means
of altering the distinguished tissue types and their conductivities.
Finally, the effects of spike averaging and signal-to-noise-ratios (SNRs)
on source analysis are evaluated by localizing subaverages.
The results obtained in this thesis demonstrate the importance of using
anisotropic and skull conductivity calibrated realistic finite element
models not only for EEG but also for MEG and EMEG source analysis. By
employing such advanced finite element models, it is possible to
demonstrate that EMEG achieves accurate source reconstructions at early
instants in time (epileptic spike onset), i.e., time points with low SNR,
which are not yet subject to propagation and thus supposed to be closer to
the origin of the epileptic activity. It is also shown that EMEG is able to
reveal the propagation pathway at later time points in agreement with
invasive stereo-EEG, while EEG or MEG alone reconstruct only parts of it.
Spike averaging and SNR analysis reveal that subaveraging provides
important and accurate information about both the center of gravity and the
extent of the epileptogenic tissue that neither single nor grand-averaged
spike localizations could supply. Moreover, it is shown that accurate
source reconstructions obtained with EMEG can be used to determine a region
of interest, and new MRI sequences that acquire high resolution images in
this restricted area can detect FCDs that were not detectable with other
MRI sequences.
The pipelines proposed in this work are also tested for source analysis of
somatosensory and auditory evoked responses measured from healthy subjects
and the results are compared with the literature. In addition, the finite
element head models are also used to assess the volume conductor effects on
simulations of non-invasive brain stimulation techniques such as
transcranial direct current and transcranial magnetic stimulation
Estimation of Container Traffic at Seaports by Using Several Soft Computing Methods: A Case of Turkish Seaports
Container traffic forecasting is important for the operations and the design steps of a seaport facility. In this study, performances of the novel soft computing models were compared for the container traffic forecasting of principal Turkish seaports (Istanbul, Izmir, and Mersin seaports) with excessive container traffic. Four forecasting models were implemented based on Artificial Neural Network with Artificial Bee Colony and Levenberg-Marquardt Algorithms (ANN-ABC and ANN-LM), Multiple Nonlinear Regression with Genetic Algorithm (MNR-GA), and Least Square Support Vector Machine (LSSVM). Forecasts were carried out by using the past records of the gross domestic product, exports, and population of the Turkey as indicators of socioeconomic and demographic status. Performances of the forecasting models were evaluated with several performance metrics. Considering the testing period, the LSSVM, ANN-ABC, and ANN-LM models performed better than the MNR-GA model considering overall fitting and prediction performances of the extreme values in the testing data. The LSSVM model was found to be more reliable compared to the ANN models. Forecasting part of the study suggested that container traffic of the seaports will be increased up to 60%, 67%, and 95% at the 2023 for the Izmir, Mersin, and Istanbul seaports considering official growth scenarios of Turkey
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Face processing in young adults with autism and ADHD: an event related potentials study
Background: Atypicalities in perception and interpretation of faces and emotional facial expressions have been reported in both autism and attention-deficit/hyperactivity disorder (ADHD) during childhood and adulthood. Investigation of face processing during young adulthood (18 to 25 years), a transition period to full-fledged adulthood, could provide important information on the adult outcomes of autism and ADHD.
Methods: In this study, we investigated event-related potentials (ERPs) related to visual face processing in autism, ADHD, and co–occurring autism and ADHD in a large sample of young adults (N = 566). The groups were based on the Diagnostic Interview for ADHD in Adults 2.0 (DIVA-2) and the Autism Diagnostic Observation Schedule-2 (ADOS-2). We analyzed ERPs from two passive viewing tasks previously used in childhood investigations: (1) upright and inverted faces with direct or averted gaze; (2) faces expressing different emotions.
Results: Across both tasks, we consistently found lower amplitude and longer latency of N170 in participants with autism compared to those without. Longer P1 latencies and smaller P3 amplitudes in response to emotional expressions and longer P3 latencies for upright faces were also characteristic to the autistic group. Those with ADHD had longer N170 latencies, specific to the face-gaze task. Individuals with both autism and ADHD showed additional alterations in gaze modulation and a lack of the face inversion effect indexed by a delayed N170.
Conclusion: Alterations in N170 for autistic young adults is largely consistent with studies on autistic adults, and some studies in autistic children. These findings suggest that there are identifiable and measurable socio-functional atypicalities in young adults with autism
MEG-EEG Fusion by Kalman Filtering within a Source Analysis Framework*
Abstract-The fusion of data from multiple neuroimaging modalities may improve the temporal and spatial resolution of non-invasive brain imaging. In this paper, we present a novel method for the fusion of simultaneously recorded electroencephalograms (EEG) and magnetoencephalograms (MEG) within the framework of source analysis. This method represents an extension of a previously published spatio-temporal inverse solution method to the case of MEG or combined MEG-EEG signals. Moreover, we use a state-of-the-art realistic finite element (FE) head model especially calibrated for the MEG-EEG fusion problem. Using a real data set containing an epileptic spike, we validate the source analysis results of the spatio-temporal inverse solution using the results of the LORETA method and the findings from other structural and functional modalities. We show that the proposed fusion method, despite the low signal-to-noise ratio (SNR) of single spikes, points to the same brain area that was found by the other modalities. Furthermore, it correctly identifies the same source as the main generator for the MEG and EEG spikes
Genetic overlap between midfrontal theta signals and ADHD and ASD in a longitudinal twin cohort
Background:
Cognitive control has been strongly linked to midfrontal theta (4-8 Hz) brain activity. Such control processes are known to be impaired in those with psychiatric conditions, and neurodevelopmental diagnoses, including attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Temporal variability in theta in particular is associated with ADHD with shared genetic variance underlying the relationship. Here, we investigated the phenotypic and genetic relationships between theta phase variability, theta-related signals (N2, ERN, Pe), reaction time, and ADHD and ASD longitudinally in a large twin study of young adults to investigate the stability of the genetic relationships between these measures over time.
Methods:
Genetic multivariate liability threshold models were run on a longitudinal sample of 566 participants (283 twin pairs). Characteristics of ADHD and ASD were measured in childhood and in young adulthood, while EEG was recorded in young adulthood during an arrow flanker task.
Results:
Cross-trial theta phase variability in adulthood showed large positive phenotypic and genetic relationships with reaction time variability and both childhood and adult ADHD characteristics. Pe amplitude was negatively related phenotypically and genetically to ADHD and ASD at both time points.
Conclusions:
We show significant genetic associations between variability in theta signalling and ADHD. In a novel finding, we show that these relationships are stable across time, indicating a core dysregulation of the temporal coordination of control processes in ADHD that persists in those with childhood symptoms. Error processing, indexed by the Pe, was altered in both ADHD and ASD, with a strong genetic contribution
Dose-dependant preventive effect of a herbal compound on crystal formation in rat model
Introduction: To analyze the dose-dependent preventive effect of a plant-based herbal product on the new crystal formation in a rat model.
Materials and methods: A total of 42 rats were divided into 7 groups and zinc discs were placed into the bladder of rats to provide a nidus for the development of new crystal formation: Group 1: control, Group 2: 0.75 percent ethylene glycol (EG); Group 3: 0.75 percent EG plus 0.051 ml of the compound; Group 4: 0.75 percent EG plus 0.179 ml of the compound; Group 5: 0.75 percent EG plus 0.217 ml of the compound; Group 6: 0.75 percent EG plus 0.255 ml of the compound; Group 7 0.75 percent EG plus 0.332 of the compound).
The analysis and comparison focused on the disc weights, changes in urinary oxalate and calcium levels, urinary pH, and the histopathologic evaluation of the inflammatory changes in the bladder after 14 days.
Results: According to the evaluation of discs placed in the bladders of the animals, animals receiving the herbal compound on a dose-dependent basis showed a limited increase in the disc weights values after 14 days, despite a considerable increase in animals receiving EG alone (p = 0.001). Further evaluation of the increase in disc weights on a dose-dependent basis in different subgroups (from Groups 3 to 7) demonstrated that the limitation of crystal deposition began to be more prominent as the dose of herbal compound increased. This effect was more evident particularly in comparisons between group 7 and others, according to LSD multiple comparison tests (p = 0.001).
As anticipated, there has been no discernible change in the weight of the discs in the control group. Although urinary calcium levels in animals of Groups 2, 6, and 7 were significantly higher than the other groups, we were not able to demonstrate a close correlation between urinary oxalate levels and the increasing dose levels. Even though mean urine pH levels were statistically considerably higher in Group 3, there was no statistically significant correlation between the oxalate and calcium levels between all groups, and no association was seen with the administration of herbal agents. The transitional epithelium between the three groups of animals' bladder samples did not exhibit any appreciable difference according to pathological analysis.
Conclusions: In this animal model, the treatment of the compound was successful in lowering the amount of crystal deposition surrounding the zinc discs, most noticeably at a dosage of 0.332 ml, three times per day
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