EEG-fMRI in the presurgical evaluation of temporal lobe epilepsy.

Drug-resistant temporal lobe epilepsy (TLE) often requires thorough investigation to define the epileptogenic zone for surgical treatment. We used simultaneous interictal scalp EEG-fMRI to evaluate its value for predicting long-term postsurgical outcome

Multiview classification and dimensionality reduction of scalp and intracranial EEG data through tensor factorisation

Electroencephalography (EEG) signals arise as a mixture of various neural processes that occur in different spatial, frequency and temporal locations. In classification paradigms, algorithms are developed that can distinguish between these processes. In this work, we apply tensor factorisation to a set of EEG data from a group of epileptic patients and factorise the data into three modes; space, time and frequency with each mode containing a number of components or signatures. We train separate classifiers on various feature sets corresponding to complementary combinations of those modes and components and test the classification accuracy of each set. The relative influence on the classification accuracy of the respective spatial, temporal or frequency signatures can then be analysed and useful interpretations can be made. Additionaly, we show that through tensor factorisation we can perform dimensionality reduction by evaluating the classification performance with regards to the number mode components and by rejecting components with insignificant contribution to the classification accuracy

Combined EEG-fMRI and ESI improves localisation of paediatric focal epilepsy

OBJECTIVE: Surgical treatment in epilepsy is effective if the epileptogenic zone (EZ) can be correctly localized and characterized. Here we use simultaneous Electroencephalography-functional MRI (EEG-fMRI) data to derive EEG-fMRI and Electrical Source Imaging (ESI) maps. Their yield and their individual and combined ability to 1) localize the epileptogenic zone and 2) predict seizure outcome was then evaluated. METHODS: Fifty-three children with drug-resistant epilepsy underwent EEG-fMRI. Interictal discharges were mapped using both EEG-fMRI haemodynamic responses and Electrical Source Imaging (ESI). A single localization was derived from each individual test (EEG-fMRI global maxima (GM)/ESI maxima) and from the combination of both maps (EEG-fMRI/ESI spatial intersection). To determine the localisation accuracy and its predictive performance the individual and combined test localisations were compared to the presumed EZ and to the postsurgical outcome. RESULTS: Fifty-two/53 patients had significant maps; 47/53 for EEG-fMRI; 44/53 for ESI; 34/53 had both. The epileptogenic zone was well characterised in 29 patients; 26 had an EEG-fMRI GM localisation which was correct in 11; 22 patients had ESI localisation which was correct in 17; 12 patients had combined EEG-fMRI and ESI which was correct in 11. Seizure outcome following resection was correctly predicted by EEG-fMRI GM in 8/20 patients, by the ESI maxima in 13/16. The combined EEG-fMRI/ESI region entirely predicted outcome in 9/9 patients including 3 with no lesion visible on MRI. INTERPRETATION: EEG-fMRI combined with ESI provides a simple unbiased localisation that may predict surgery better than each individual test including in MRI-negative patients

Combined EEG-fMRI and ESI improves localisation of paediatric focal epilepsy

OBJECTIVE: Surgical treatment in epilepsy is effective if the epileptogenic zone (EZ) can be correctly localized and characterized. Here we use simultaneous Electroencephalography-functional MRI (EEG-fMRI) data to derive EEG-fMRI and Electrical Source Imaging (ESI) maps. Their yield and their individual and combined ability to 1) localize the epileptogenic zone and 2) predict seizure outcome was then evaluated. METHODS: Fifty-three children with drug-resistant epilepsy underwent EEG-fMRI. Interictal discharges were mapped using both EEG-fMRI haemodynamic responses and Electrical Source Imaging (ESI). A single localization was derived from each individual test (EEG-fMRI global maxima (GM)/ESI maxima) and from the combination of both maps (EEG-fMRI/ESI spatial intersection). To determine the localisation accuracy and its predictive performance the individual and combined test localisations were compared to the presumed EZ and to the postsurgical outcome. RESULTS: Fifty-two/53 patients had significant maps; 47/53 for EEG-fMRI; 44/53 for ESI; 34/53 had both. The epileptogenic zone was well characterised in 29 patients; 26 had an EEG-fMRI GM localisation which was correct in 11; 22 patients had ESI localisation which was correct in 17; 12 patients had combined EEG-fMRI and ESI which was correct in 11. Seizure outcome following resection was correctly predicted by EEG-fMRI GM in 8/20 patients, by the ESI maxima in 13/16. The combined EEG-fMRI/ESI region entirely predicted outcome in 9/9 patients including 3 with no lesion visible on MRI. INTERPRETATION: EEG-fMRI combined with ESI provides a simple unbiased localisation that may predict surgery better than each individual test including in MRI-negative patients

Neural substrates of individual differences in human fear learning: Evidence from concurrent fMRI, fear-potentiated startle, and US-expectancy data

To provide insight into individual differences in fear learning, we examined the emotional and cognitive expressions of discriminative fear conditioning in direct relation to its neural substrates. Contrary to previous behavioral–neural (fMRI) research on fear learning—in which the emotional expression of fear was generally indexed by skin conductance—we used fear-potentiated startle, a more reliable and specific index of fear. While we obtained concurrent fear-potentiated startle, neuroimaging (fMRI), and US-expectancy data, healthy participants underwent a fear-conditioning paradigm in which one of two conditioned stimuli (CS(+) but not CS(–)) was paired with a shock (unconditioned stimulus [US]). Fear learning was evident from the differential expressions of fear (CS(+) > CS(–)) at both the behavioral level (startle potentiation and US expectancy) and the neural level (in amygdala, anterior cingulate cortex, hippocampus, and insula). We examined individual differences in discriminative fear conditioning by classifying participants (as conditionable vs. unconditionable) according to whether they showed successful differential startle potentiation. This revealed that the individual differences in the emotional expression of discriminative fear learning (startle potentiation) were reflected in differential amygdala activation, regardless of the cognitive expression of fear learning (CS–US contingency or hippocampal activation). Our study provides the first evidence for the potential of examining startle potentiation in concurrent fMRI research on fear learning

Whole-brain high-resolution metabolite mapping with 3D compressed-sensing SENSE low-rank ¹ H FID-MRSI.

There is a growing interest in the neuroscience community to map the distribution of brain metabolites in vivo. Magnetic resonance spectroscopic imaging (MRSI) is often limited by either a poor spatial resolution and/or a long acquisition time, which severely restricts its applications for clinical and research purposes. Building on a recently developed technique of acquisition-reconstruction for 2D MRSI, we combined a fast Cartesian <sup>1</sup> H-FID-MRSI acquisition sequence, compressed-sensing acceleration, and low-rank total-generalized-variation constrained reconstruction to produce 3D high-resolution whole-brain MRSI with a significant acquisition time reduction. We first evaluated the acceleration performance using retrospective undersampling of a fully sampled dataset. Second, a 20 min accelerated MRSI acquisition was performed on three healthy volunteers, resulting in metabolite maps with 5 mm isotropic resolution. The metabolite maps exhibited the detailed neurochemical composition of all brain regions and revealed parts of the underlying brain anatomy. The latter assessment used previous reported knowledge and a atlas-based analysis to show consistency of the concentration contrasts and ratio across all brain regions. These results acquired on a clinical 3 T MRI scanner successfully combined 3D <sup>1</sup> H-FID-MRSI with a constrained reconstruction to produce detailed mapping of metabolite concentrations at high resolution over the whole brain, with an acquisition time suitable for clinical or research settings

Towards high-quality simultaneous EEG-fMRI at 7T: Detection and reduction of EEG artifacts due to head motion.

The enhanced functional sensitivity offered by ultra-high field imaging may significantly benefit simultaneous EEG-fMRI studies, but the concurrent increases in artifact contamination can strongly compromise EEG data quality. In the present study, we focus on EEG artifacts created by head motion in the static B0 field. A novel approach for motion artifact detection is proposed, based on a simple modification of a commercial EEG cap, in which four electrodes are non-permanently adapted to record only magnetic induction effects. Simultaneous EEG-fMRI data were acquired with this setup, at 7T, from healthy volunteers undergoing a reversing-checkerboard visual stimulation paradigm. Data analysis assisted by the motion sensors revealed that, after gradient artifact correction, EEG signal variance was largely dominated by pulse artifacts (81-93%), but contributions from spontaneous motion (4-13%) were still comparable to or even larger than those of actual neuronal activity (3-9%). Multiple approaches were tested to determine the most effective procedure for denoising EEG data incorporating motion sensor information. Optimal results were obtained by applying an initial pulse artifact correction step (AAS-based), followed by motion artifact correction (based on the motion sensors) and ICA denoising. On average, motion artifact correction (after AAS) yielded a 61% reduction in signal power and a 62% increase in VEP trial-by-trial consistency. Combined with ICA, these improvements rose to a 74% power reduction and an 86% increase in trial consistency. Overall, the improvements achieved were well appreciable at single-subject and single-trial levels, and set an encouraging quality mark for simultaneous EEG-fMRI at ultra-high field

Minor Actinides Transmutation Scenario Studies in PWR with Innovative Fuels

With the innovative fuels (CORAIL, APA, MIX, MOX-UE) in current PWRs, it is theoretically possible to obtain different plutonium and minor actinides transmutation scenarios, in homogeneous mode, with a significant reduction of the waste radio-toxicity inventory and of the thermal output of the high level waste. Regarding each minor actinide element transmutation in PWRs, conclusions are : neptunium : a solution exists but the gain on the waste radio-toxicity inventory is not significant, americium : a solution exists but it is necessary to transmute americium with curium to obtain a significant gain, curium: Cm244 has a large impact on radiation and residual power in the fuel cycle; a solution remains to be found, maybe separating it and keeping it in interim storage for decay into Pu240 able to be transmuted in reactor