Tubers from patients with tuberous sclerosis complex are characterized by changes in microtubule biology through ROCK2 signalling.

Most patients with tuberous sclerosis complex (TSC) develop cortical tubers that cause severe neurological disabilities. It has been suggested that defects in neuronal differentiation and/or migration underlie the appearance of tubers. However, the precise molecular alterations remain largely unknown. Here, by combining cytological and immunohistochemical analyses of tubers from nine TSC patients (four of them diagnosed with TSC2 germline mutations), we show that alteration of microtubule biology through ROCK2 signalling contributes to TSC neuropathology. All tubers showed a larger number of binucleated neurons than expected relative to control cortex. An excess of normal and altered cytokinetic figures was also commonly observed. Analysis of centrosomal markers suggested increased microtubule nucleation capacity, which was supported by the analysis of an expression dataset from cortical tubers and control cortex, and subsequently linked to under-expression of Rho-associated coiled-coil containing kinase 2 (ROCK2). Thus, augmented microtubule nucleation capacity was observed in mouse embryonic fibroblasts and human fibroblasts deficient in the Tsc2/TSC2 gene product, tuberin. Consistent with ROCK2 under-expression, microtubule acetylation was found to be increased with tuberin deficiency; this alteration was abrogated by rapamycin treatment and mimicked by HDAC6 inhibition. Together, the results of this study support the hypothesis that loss of TSC2 expression can alter microtubule organization and dynamics, which, in turn, deregulate cell division and potentially impair neuronal differentiation.

Automated detection of epileptic ripples in MEG using beamformer-based virtual sensors.

OBJECTIVE: In epilepsy, high-frequency oscillations (HFOs) are expressively linked to the seizure onset zone (SOZ). The detection of HFOs in the noninvasive signals from scalp electroencephalography (EEG) and magnetoencephalography (MEG) is still a challenging task. The aim of this study was to automate the detection of ripples in MEG signals by reducing the high-frequency noise using beamformer-based virtual sensors (VSs) and applying an automatic procedure for exploring the time-frequency content of the detected events. APPROACH: Two-hundred seconds of MEG signal and simultaneous iEEG were selected from nine patients with refractory epilepsy. A two-stage algorithm was implemented. Firstly, beamforming was applied to the whole head to delimitate the region of interest (ROI) within a coarse grid of MEG-VS. Secondly, a beamformer using a finer grid in the ROI was computed. The automatic detection of ripples was performed using the time-frequency response provided by the Stockwell transform. Performance was evaluated through comparisons with simultaneous iEEG signals. MAIN RESULTS: ROIs were located within the seizure-generating lobes in the nine subjects. Precision and sensitivity values were 79.18% and 68.88%, respectively, by considering iEEG-detected events as benchmarks. A higher number of ripples were detected inside the ROI compared to the same region in the contralateral lobe. SIGNIFICANCE: The evaluation of interictal ripples using non-invasive techniques can help in the delimitation of the epileptogenic zone and guide placement of intracranial electrodes. This is the first study that automatically detects ripples in MEG in the time domain located within the clinically expected epileptic area taking into account the time-frequency characteristics of the events through the whole signal spectrum. The algorithm was tested against intracranial recordings, the current gold standard. Further studies should explore this approach to enable the localization of noninvasively recorded HFOs to help during pre-surgical planning and to reduce the need for invasive diagnostics.

Influence of metallic artifact filtering on MEG signals for source localization during interictal epileptiform activity.

OBJECTIVE: Medical intractable epilepsy is a common condition that affects 40% of epileptic patients that generally have to undergo resective surgery. Magnetoencephalography (MEG) has been increasingly used to identify the epileptogenic foci through equivalent current dipole (ECD) modeling, one of the most accepted methods to obtain an accurate localization of interictal epileptiform discharges (IEDs). Modeling requires that MEG signals are adequately preprocessed to reduce interferences, a task that has been greatly improved by the use of blind source separation (BSS) methods. MEG recordings are highly sensitive to metallic interferences originated inside the head by implanted intracranial electrodes, dental prosthesis, etc and also coming from external sources such as pacemakers or vagal stimulators. To reduce these artifacts, a BSS-based fully automatic procedure was recently developed and validated, showing an effective reduction of metallic artifacts in simulated and real signals (Migliorelli et al 2015 J. Neural Eng. 12 046001). The main objective of this study was to evaluate its effects in the detection of IEDs and ECD modeling of patients with focal epilepsy and metallic interference. APPROACH: A comparison between the resulting positions of ECDs was performed: without removing metallic interference; rejecting only channels with large metallic artifacts; and after BSS-based reduction. Measures of dispersion and distance of ECDs were defined to analyze the results. MAIN RESULTS: The relationship between the artifact-to-signal ratio and ECD fitting showed that higher values of metallic interference produced highly scattered dipoles. Results revealed a significant reduction on dispersion using the BSS-based reduction procedure, yielding feasible locations of ECDs in contrast to the other two approaches. SIGNIFICANCE: The automatic BSS-based method can be applied to MEG datasets affected by metallic artifacts as a processing step to improve the localization of epileptic foci.

Automatic BSS-based filtering of metallic interference in MEG recordings: definition and validation using simulated signals.

OBJECTIVE: One of the principal drawbacks of magnetoencephalography (MEG) is its high sensitivity to metallic artifacts, which come from implanted intracranial electrodes and dental ferromagnetic prosthesis and produce a high distortion that masks cerebral activity. The aim of this study was to develop an automatic algorithm based on blind source separation (BSS) techniques to remove metallic artifacts from MEG signals. APPROACH: Three methods were evaluated: AMUSE, a second-order technique; and INFOMAX and FastICA, both based on high-order statistics. Simulated signals consisting of real artifact-free data mixed with real metallic artifacts were generated to objectively evaluate the effectiveness of BSS and the subsequent interference reduction. A completely automatic detection of metallic-related components was proposed, exploiting the known characteristics of the metallic interference: regularity and low frequency content. MAIN RESULTS: The automatic procedure was applied to the simulated datasets and the three methods exhibited different performances. Results indicated that AMUSE preserved and consequently recovered more brain activity than INFOMAX and FastICA. Normalized mean squared error for AMUSE decomposition remained below 2%, allowing an effective removal of artifactual components. SIGNIFICANCE: To date, the performance of automatic artifact reduction has not been evaluated in MEG recordings. The proposed methodology is based on an automatic algorithm that provides an effective interference removal. This approach can be applied to any MEG dataset affected by metallic artifacts as a processing step, allowing further analysis of unusable or poor quality data.

Reduction of metallic interference in MEG signals using AMUSE.

Magnetoencephalography is a technique that can noninvasively measure the brain signal. There are many advantages of using this technique rather than similar procedures such as the EEG for the evaluation of medical diseases. However, one of its main problems is its high sensitivity to sources causing metallic distortion of the signal, and the removal of this type of artifacts remains unsolved. In this study a technique for reducing metallic interference was presented. This algorithm was based on AMUSE, a second order blind source separation method, and a procedure for choosing the artifactual independent components was also presented. The results showed that the elimination of these artifacts would be possible by means of the application of this AMUSE-based interference reduction procedure.

Toward a definition of MEG spike: parametric description of spikes recorded simultaneously by MEG and depth electrodes.

There is not yet a formal definition of magnetoencephalography (MEG) spike. This study provides a parametric description and definition of clear-cut MEG spikes recorded simultaneously by MEG and depth electrodes (iEEG). A total number of 367 simultaneous MEG/iEEG spikes were selected for analysis. Distribution of morphologic spike parameters and detailed quantitative analysis of the basic morphologic characteristics of MEG spikes is provided.

Simultaneous magnetoencephalography and intracranial EEG registration: technical and clinical aspects.

The purpose of this study was to describe the methodology necessary for simultaneous recording of intracranial EEG (ICEEG) and magnetoencephalography (MEG) and to assess the sensitivity of whole-head MEG versus depth electrode EEG in the detection and localization of epileptic spikes. Interictal MEG and depth electrode activities from the temporal mesial and occipital lobes were simultaneously recorded from four candidates for epilepsy surgery. Implanted depth electrodes identified neocortical and mesial structures of ictal onset. Interictal spikes detected by these same depth electrodes were compared with simultaneous MEG events. MEG detections of ICEEG spikes, ICEEG versus MEG spike amplitudes, number of ICEEG contacts involved in the spike, and anatomic locations of MEG equivalent current dipoles were analyzed. MEG detected and localized 95% of the neocortical spikes, but only 25% to 60% of spikes from mesial structures. Mesial temporal spikes resulted in lower MEG spike amplitudes, when compared with neocortical spikes. Equivalent current dipoles of MEG spikes localized to the ictal onset zones in all four patients. MEG can detect and localize interictal epileptiform spikes that are recorded from depth electrodes in both neocortical and mesial structures, despite the lesser amplitude of spikes of mesial origin.