Modelling large motion events in fMRI studies of patients with epilepsy

EEG-correlated fMRI can provide localisation information on the generators of epileptiform discharges in patients with focal epilepsy. To increase the technique's clinical potential, it is important to consider ways of optimising the yield of each experiment while minimizing the risk of false-positive activation. Head motion can lead to severe image degradation and result in false-positive activation and is usually worse in patients than in healthy subjects. We performed general linear model fMRI data analysis on simultaneous EEG–fMRI data acquired in 34 cases with focal epilepsy. Signal changes associated with large inter-scan motion events (head jerks) were modelled using modified design matrices that include ‘scan nulling’ regressors. We evaluated the efficacy of this approach by mapping the proportion of the brain for which F-tests across the additional regressors were significant. In 95% of cases, there was a significant effect of motion in 50% of the brain or greater; for the scan nulling effect, the proportion was 36%; this effect was predominantly in the neocortex. We conclude that careful consideration of the motion-related effects in fMRI studies of patients with epilepsy is essential and that the proposed approach can be effective

Evaluation of atlas-based segmentation of hippocampi in healthy humans

Introduction and aim: Region of interest (ROI)-based functional magnetic resonance imaging (fMRI) data analysis relies on extracting signals from a specific area which is presumed to be involved in the brain activity being studied. The hippocampus is of interest in many functional connectivity studies for example in epilepsy as it plays an important role in epileptogenesis. In this context, ROI may be defined using different techniques. Our study aims at evaluating the spatial correspondence of hippocampal ROIs obtained using three brain atlases with hippocampal ROI obtained using an automatic segmentation algorithm dedicated to the hippocampus. Material and methods: High-resolution volumetric T1-weighted MR images of 18 healthy volunteers (five females) were acquired on a 3T scanner. Individual ROIs for both hippocampi of each subject were segmented from the MR images using an automatic hippocampus and amygdala segmentation software called SACHA providing the gold standard ROI for comparison with the atlas-derived results. For each subject, hippocampal ROIs were also obtained using three brain atlases: PickAtlas available as a commonly used software toolbox; automated anatomical labeling (AAL) atlas included as a subset of ROI into PickAtlas toolbox and a frequency-based brain atlas by Hammers et al. The levels of agreement between the SACHA results and those obtained using the atlases were assessed based on quantitative indices measuring volume differences and spatial overlap. The comparison was performed in standard Montreal Neurological Institute space, the registration being obtained with SPM5 (http://www.fil.ion.ucl.ac.uk/spm/). Results: The mean volumetric error across all subjects was 73% for hippocampal ROIs derived from AAL atlas; 20% in case of ROIs derived from the Hammers atlas and 107% for ROIs derived from PickAtlas. The mean false-positive and false-negative classification rates were 60% and 10% respectively for the AAL atlas; 16% and 32% for the Hammers atlas and 6% and 72% for the PickAtlas. Conclusion: Though atlas-based ROI definition may be convenient, the resulting ROIs may be poor representations of the hippocampus in some studies critical to under- or oversampling. Performance of the AAL atlas was inferior to that of the Hammers atlas. Hippocampal ROIs derived from PickAtlas are highly significantly smaller, and this results in the worst performance out of three atlases. It is advisable that the defined ROIs should be verified with knowledge of neuroanatomy before using it for further data analysis

Localisation of epileptic foci using novel imaging modalities.

This review examines recent reports on the use of advanced techniques to map the regions and networks involved during focal epileptic seizure generation in humans

Nonlinear interferometer for tailoring the frequency spectrum of bright squeezed vacuum

We propose a method for tailoring the frequency spectrum of bright squeezed vacuum by generating it in a nonlinear interferometer, consisting of two down-converting nonlinear crystals separated by a dispersive medium. Due to a faster dispersive spreading of higher-order Schmidt modes, the spectral width of the radiation at the output is reduced as the length of the dispersive medium is increased. Preliminary results show 30\% spectral narrowing.Comment: 9 pages, 6 figure

EEG–fMRI of idiopathic and secondarily generalized epilepsies

We used simultaneous EEG and functional MRI (EEG–fMRI) to study generalized spike wave activity (GSW) in idiopathic and secondary generalized epilepsy (SGE). Recent studies have demonstrated thalamic and cortical fMRI signal changes in association with GSW in idiopathic generalized epilepsy (IGE). We report on a large cohort of patients that included both IGE and SGE, and give a functional interpretation of our findings. Forty-six patients with GSW were studied with EEG–fMRI; 30 with IGE and 16 with SGE. GSW-related BOLD signal changes were seen in 25 of 36 individual patients who had GSW during EEG–fMRI. This was seen in thalamus (60%) and symmetrically in frontal cortex (92%), parietal cortex (76%), and posterior cingulate cortex/precuneus (80%). Thalamic BOLD changes were predominantly positive and cortical changes predominantly negative. Group analysis showed a negative BOLD response in the cortex in the IGE group and to a lesser extent a positive response in thalamus. Thalamic activation was consistent with its known role in GSW, and its detection in individual cases with EEG–fMRI may in part be related to the number and duration of GSW epochs recorded. The spatial distribution of the cortical fMRI response to GSW in both IGE and SGE involved areas of association cortex that are most active during conscious rest. Reduction of activity in these regions during GSW is consistent with the clinical manifestation of absence seizures

Safety of localizing epilepsy monitoring intracranial electroencephalograph electrodes using MRI: radiofrequency-induced heating

Purpose: To investigate heating during postimplantation localization of intracranial electroencephalograph (EEG) electrodes by MRI. Materials and Methods: A phantom patient with a realistic arrangement of electrodes was used to simulate tissue heating during MRI. Measurements were performed using 1.5 Tesla (T) and 3T MRI scanners, using head- and body-transmit RF-coils. Two electrode-lead configurations were assessed: a standard condition with external electrode-leads physically separated and a fault condition with all lead terminations electrically shorted. Results: Using a head-transmit-receive coil and a 2.4 W/kg head-average specific absorption rate (SAR) sequence, at 1.5T the maximum temperature change remained within safe limits (<1°C). Under standard conditions, we observed greater heating (2.0°C) at 3T on one system and similar heating (<1°C) on a second, compared with the 1.5T system. In all cases these temperature maxima occurred at the grid electrode. In the fault condition, larger temperature increases were observed at both field strengths, particularly for the depth electrodes. Conversely, with a body-transmit coil at 3T significant heating (+6.4°C) was observed (same sequence, 1.2/0.5 W/kg head/body-average) at the grid electrode under standard conditions, substantially exceeding safe limits. These temperature increases neglect perfusion, a major source of heat dissipation in vivo. Conclusion: MRI for intracranial electrode localization can be performed safely at both 1.5T and 3T provided a head-transmit coil is used, electrode leads are separated, and scanner-reported SARs are limited as determined in advance for specific scanner models, RF coils and implant arrangements. Neglecting these restrictions may result in tissue injury

Properties of bright squeezed vacuum at increasing brightness

A bright squeezed vacuum (BSV) is a nonclassical macroscopic state of light, which is generated through high-gain parametric down-conversion or four-wave mixing. Although the BSV is an important tool in quantum optics and has a lot of applications, its theoretical description is still not complete. In particular, the existing description in terms of Schmidt modes with gain-independent shapes fails to explain the spectral broadening observed in the experiment as the mean number of photons increases. Meanwhile, the semiclassical description accounting for the broadening does not allow us to decouple the intermodal photon-number correlations. In this work, we present a new generalized theoretical approach to describe the spatial properties of a multimode BSV. In the multimode case, one has to take into account the complicated interplay between all involved modes: each plane-wave mode interacts with all other modes, which complicates the problem significantly. The developed approach is based on exchanging the (k, t ) and (ω, z) representations and solving a system of integrodifferential equations. Our approach predicts correctly the dynamics of the Schmidt modes and the broadening of the angular distribution with the increase in the BSV mean photon number due to a stronger pumping. Moreover, the model correctly describes various properties of a widely used experimental configuration with two crystals and an air gap between them, namely, an SU(1,1) interferometer. In particular, it predicts the narrowing of the intensity distribution, the reduction and shift of the side lobes, and the decline in the interference visibility as the mean photon number increases due to stronger pumping. The presented experimental results confirm the validity of the new approach. The model can be easily extended to the case of the frequency spectrum, frequency Schmidt modes, and other experimental configurations

The spatio-temporal mapping of epileptic networks: Combination of EEG–fMRI and EEG source imaging

Simultaneous EEG–fMRI acquisitions in patients with epilepsy often reveal distributed patterns of Blood Oxygen Level Dependant (BOLD) change correlated with epileptiform discharges. We investigated if electrical source imaging (ESI) performed on the interictal epileptiform discharges (IED) acquired during fMRI acquisition could be used to study the dynamics of the networks identified by the BOLD effect, thereby avoiding the limitations of combining results from separate recordings. Nine selected patients (13 IED types identified) with focal epilepsy underwent EEG–fMRI. Statistical analysis was performed using SPM5 to create BOLD maps. ESI was performed on the IED recorded during fMRI acquisition using a realistic head model (SMAC) and a distributed linear inverse solution (LAURA). ESI could not be performed in one case. In 10/12 remaining studies, ESI at IED onset (ESIo) was anatomically close to one BOLD cluster. Interestingly, ESIo was closest to the positive BOLD cluster with maximal statistical significance in only 4/12 cases and closest to negative BOLD responses in 4/12 cases. Very small BOLD clusters could also have clinical relevance in some cases. ESI at later time frame (ESIp) showed propagation to remote sources co-localised with other BOLD clusters in half of cases. In concordant cases, the distance between maxima of ESI and the closest EEG–fMRI cluster was less than 33 mm, in agreement with previous studies. We conclude that simultaneous ESI and EEG–fMRI analysis may be able to distinguish areas of BOLD response related to initiation of IED from propagation areas. This combination provides new opportunities for investigating epileptic networks