Identifying the origin of the source in multi-focal epilepsy patients [Poster]

The aim of this study, was firstly to identify the two neuronal sources in the brain which show the highest dipole strength; caused by the multi-focal epileptic activity using the Minimum-norm (MN) inverse solution technique on a realistic head model. The second aim was to study the dynamics of these two source signals so as to identify which part of the brain is activated first and which part follows, using time-frequency analysis. 1. The source analysis revealed the first two neuronal networks, which showed the highest dipolar strength, in each patient. 2. The power dynamics over the whole time duration and frequency gives valuable information in identifying the region of the brain which is activated first for each patient before the surgical procedure

Functional and effective connectivity during focal epileptic seizures [Poster]

The aim of this study was to investigate the dynamics of neuronal networks during focal seizures using dynamic imaging of coherent sources (DICS) (Gross et al. 2001) and renormalized partial directed coherence (RPDC) (Schelter et al. 2009). Ictal EEG recordings from a patient with drug resistant focal epilepsy, due to a focal cortical dysplasia (FCD) in the left parieto-occipital region, (shown by a high resolution 3-T MRI) were analyzed. DICS revealed the neuronal networks concomitant with the location of the FCD, shown by a high resolution 3-T MRI and areas of decreased metabolism shown by functional neuroimaging methods. The sources identified during the seizure onset and propagation phases were similar. Only the causality was different, showing that the strongest source, located in the occipito-temporal region, is most probably a pacemaker/seizure onset zone of the ictal neuronal networks in this case. The DICS analyses of pre-seizure phase showed the sources in the DMN areas of the brain. We can conclude that analyses of multiple habitual seizures of the same patients by the methods of DICS and RPDC gives us valuable information regarding the seizure onset zone and ictal networks. It can be a useful additive tool during the pre-epilepsy surgical investigations of the patients with drug resistant focal epilepsies

Testing the effects of pre-processing on voxel based morphometry analysis

Voxel based morphometry (VBM) is an automated analysis technique which allows voxel-wise comparison of mainly grey-matter volumes between two magnetic resonance images (MRI). Two main analysis processes in VBM are possible. One is cross-sectional data analysis, where one group is compared with another to depict see the regions in the brain, which show changes in their grey-matter volume. Second is longitudinal data analysis, where MRIs, taken at different time points, are compared to see the regions in the brain that show changes in their grey matter volume for one time point with respect to another time point. Both types of analyses require pre-processing steps before performing the statistical analysis. In this study, we examined grey matter differences for patients with blepharospasmus (BFS) before and after treatment, at two different time points. The main evidence base therapy for this condition is the “botulinum toxin” injection in the respective muscles. The main aim of this study was to look at the effects of different pre-processing steps, namely, normalization and smoothing on the results of the longitudinal data analysis. A second aim was to analyze structural grey-matter differences before and after the treatment. Our results showed that the DARTEL normalization and the lower width for smoothing as preprocessing steps delivered pathophysiological plausible results. The longitudinal analysis revealed significant temporal differences after the injection of the botulinum toxin injection mainly in patients with BFS

Source analysis of median nerve stimulated somatosensory evoked potentials and fields using simultaneously measured EEG and MEG signals

The sources of somatosensory evoked potentials (SEPs) and fields (SEFs), which is a standard paradigm, is investigated using multichannel EEG and MEG simultaneous recordings. The hypothesis that SEP & SEF sources are generated in the posterior bank of the central sulcus is tested, and analyses are compared based on EEG only, MEG only, bandpass filtered MEG, and both combined. To locate the sources, the forward problem is first solved by using the boundary-element method for realistic head models and by using a locally-fitted-sphere approach for averaged head models consisting of a set of connected volumes, typically representing the skull, scalp, and brain. The location of each dipole is then estimated using fixed MUSIC and current-density-reconstruction (CDR) algorithms. For both analyses, the results demonstrate that the band-pass filtered MEG can localize the sources accurately at the desired region as compared to only EEG and unfiltered MEG. For CDR analysis, it looks like MEG affects EEG during the combined analyses. The MUSIC algorithm gives better results than CDR, and when comparing the two head models, the averaged and the realistic head models showed the same result

Professor Dr. Kikunosuke Ohno : His Personality and Works (Ohno Commemorative Issue)

At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general conclusion multi-center studies would be helpful

Results of the spectral source absolute power for eyes open and eyes closed condition.

<p>Mean band power (with standard deviation) is shown for EEG (black bars), MEG (white bars), and EEG+MEG (grey bars). A) Eyes open condition. B) Eyes closed condition. Significant recording method differences are indicated by * (p < 0.05).</p

First column represents the recording method EEG in each frequency band showing the grand average statistical map of network of sources for the eyes closed (EC) condition.

<p>Second column represents the recording method MEG for each frequency band separately. Third column represents the combined approach (EEG+MEG). The numbers indicate the order of sources found for each frequency band separately.</p

This figure illustrates the information flow between the coherent sources in the brain for the FT task using EEG, Meg and MEG+EEG.

<p>The dashed line indicates significant bi-directional interaction and the bold lines with the arrow heads indicate the corresponding significant uni-directional interaction between the sources. The two dotted lines indicate the two additional interactions found between the sources for only the combined approach (MEG+EEG).</p

The mean and standard deviation of coherence and RPDC values between all the sources from all the subjects (separately for each recording method) for the condition EC.

<p>The mean and standard deviation of coherence and RPDC values between all the sources from all the subjects (separately for each recording method) for the condition EC.</p