Publications (328) View all
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Article: Effect of the static magnetic field of the MR-scanner on ERPs: evaluation of visual, cognitive and motor potentials.
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ABSTRACT: This work investigates the influence of the static magnetic field of the MR-scanner on ERPs extracted from simultaneous EEG-fMRI recordings. The quality of the ERPs after BallistoCardioGraphic (BCG) artifact removal, as well as the reproducibility of the waveforms in different environments is investigated. We consider a Detection, a Go-Nogo and a Motor task, eliciting peaks that differ in amplitude, latency and scalp topography, repeated in two situations: outside the scanner room (0T) and inside the MR-scanner but without gradients (3T). The BCG artifact is removed by means of three techniques: the Average Artifact Subtraction (AAS) method, the Optimal Basis Set (OBS) method and the Canonical Correlation Analysis (CCA) approach. The performance of the three methods depends on the amount of averaged trials. Moreover, differences are found on both amplitude and latency of ERP components recorded in two environments (0T vs 3T). We showed that, while ERPs can be extracted from simultaneous EEG-fMRI data at 3T, the static magnetic field might affect the physiological processes under investigation. The reproducibility of the ERPs in different recording environments (0T vs 3T) is a relevant issue that deserves further investigation to clarify the equivalence of cognitive processes in both behavioral and imaging studies.Clinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology 05/2010; 121(5):672-85. · 3.12 Impact Factor -
Article: Source Extraction by Maximizing the Variance in the Conditional Distribution Tails
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ABSTRACT: This paper presents a method for signal extraction based on conditional second-order moments of the output of the extraction filter. The estimator of the filter is derived from an approximate maximum likelihood criterion conditioned on a presence indicator of the source of interest. The conditional moment is shown to be a contrast function under the conditions that 1) all cross-moments of the same order between the source signal of interest and the other source signals are null and 2) that the source of interest has the largest conditional moment among all sources. For the two-source two-observation case, this allows us to derive the theoretical recovery bounds of the contrast when the conditional cross-moment does not vanish. A comparison with empirical results confirms these bounds. Simulations show that the estimator is quite robust to additive Gaussian distributed noise. Also through simulations, we show that the error level induced by a rough approximation of the presence indicator shows a strong similarity with that of additive noise. The robustness, with respect both to noise and to inaccuracies in the prior information about the source presence, guarantees a wide applicability of the proposed method.IEEE Transactions on Signal Processing 02/2010; · 2.63 Impact Factor -
Conference Proceeding: Fan beam forced detection in Gate
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ABSTRACT: Fan beam collimators can obtain a higher sensitivity without loss in resolution at the cost of a reduced field of view. The geometric response has been studied both analytically and with numerical and Monte Carlo simulations, but a fast and accurate Monte Carlo simulator for fan beam geometry is not available. The goal of this work is therefore to accelerate <sup>99m</sup>Tc fan beam simulations in Gate, with full MC modeling of the collimator and detector in order to retain the characteristic hexagonal hole pattern of the collimator. To this end, two problems need to be solved: the long calculation time of particle transport in fan beam collimator geometry and the lack of dedicated variance reduction techniques. The first problem is solved by a dedicated tracking algorithm for fan beam collimator. The second problem is solved by the introduction of fan beam forced detection with variable solid angles. Our methods were validated with both analog Gate simulations and measurements. A good agreement was found for the hexagonal hole pattern, energy spectra, spatial resolution and sensitivity.Nuclear Science Symposium Conference Record (NSS/MIC), 2009 IEEE; 12/2009 -
Article: Automated identification of ERP peaks through Dynamic Time Warping: an application to developmental dyslexia.
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ABSTRACT: This article proposes a method to automatically identify and label event-related potential (ERP) components with high accuracy and precision. We present a framework, referred to as peak-picking Dynamic Time Warping (ppDTW), where a priori knowledge about the ERPs under investigation is used to define a reference signal. We developed a combination of peak-picking and Dynamic Time Warping (DTW) that makes the temporal intervals for peak-picking adaptive on the basis of the morphology of the data. We tested the procedure on experimental data recorded from a control group and from children diagnosed with developmental dyslexia. We compared our results with the traditional peak-picking. We demonstrated that our method achieves better performance than peak-picking, with an overall precision, recall and F-score of 93%, 86% and 89%, respectively, versus 93%, 80% and 85% achieved by peak-picking. We showed that our hybrid method outperforms peak-picking, when dealing with data involving several peaks of interest. The proposed method can reliably identify and label ERP components in challenging event-related recordings, thus assisting the clinician in an objective assessment of amplitudes and latencies of peaks of clinical interest.Clinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology 10/2009; 120(10):1819-27. · 3.12 Impact Factor -
Article: Removing muscle and eye artifacts using blind source separation techniques in ictal EEG source imaging.
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ABSTRACT: The contamination of muscle and eye artifacts during an ictal period of the EEG significantly distorts source estimation algorithms. Recent blind source separation (BSS) techniques based on canonical correlation (BSS-CCA) and independent component analysis with spatial constraints (SCICA) have shown much promise in the removal of these artifacts. In this study we want to use BSS-CCA and SCICA as a preprocessing step before the source estimation during the ictal period. Both the contaminated and cleaned ictal EEG were subjected to the RAP-MUSIC algorithm. This is a multiple dipole source estimation technique based on the separation of the EEG in signal and noise subspace. The source estimates were compared with the subtracted ictal SPECT (iSPECT) coregistered to magnetic resonance imaging (SISCOM) by means of the euclidean distance between the iSPECT activations and the dipole location estimates. SISCOM results in an image denoting the ictal onset zone with a propagation. We applied the artifact removal and the source estimation on 8 patients. Qualitatively, we can see that 5 out of 8 patients show an improvement of the dipoles. The dipoles are nearer to or have tighter clusters near the iSPECT activation. From the median of the distance measure, we could appreciate that 5 out of 8 patients show improvement. The results show that BSS-CCA and SCICA can be applied to remove artifacts, but the results should be interpreted with care. The results of the source estimation can be misleading due to excessive noise or modeling errors. Therefore, the accuracy of the source estimation can be increased by preprocessing the ictal EEG segment by BSS-CCA and SCICA. This is a pilot study where EEG source localization in the presurgical evaluation can be made more reliable, if preprocessing techniques such as BSS-CCA and SCICA are used prior to EEG source analysis on ictal episodes.Clinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology 07/2009; 120(7):1262-72. · 3.12 Impact Factor
