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5e Interfaces Glaxo Smith Kline 2001 : odysée de l'EEG Vérone, Italie - 2 et 3 mars 2001
Dipole modeling of interictal and ictal EEG and MEG paroxysms
Isabelle Merlet
(MEG) signals. These methods have been applied to interictal spikes for more than 20 years and suggest that interictal paroxysms might be generated by a network of cortical structures rather than by a focal area. In this review we address the questions of (1) the spatial extend of this network in different types of epilepsies, (2) the spatial relationship between this network and other structural of functional abnormalities as assessed by Magnetic Resonance Imaging (MRI) or Positron Emission Tomography (PET), and (3) the reliability of dipole sources of interictal and ictal paroxysms. Dipole modeling results suggest that, in temporal lobe epilepsies, both neocortical and mesio-temporal structures are involved during interictal spikes; frontal lobe epilepsies are often characterized by more complex source distributions, that, in general, involve a large area and bilateral frontal structures. In addition, dipole modeling results are also found in close agreement with MRI data in cases where focal dysplasia or heterotopia are diagnosed. Nevertheless, in most other cases, sources of interictal spikes and MRI lesions, though overlapping in space, are not totally congruent. The best concordance between sources of interictal spikes and glucose hypometabolism on PET data is usually found for temporal lobe epilepsies. Most often, intracranial and intracerebral recordings validate both the localization and the time activation of interictal spike dipoles. However, results obtained for ictal discharges are less reliable, which therefore addresses the usefulness of dipole modeling procedures in assessing sources of ictal discharges. In conclusion, dipole modeling results can rarely be used in planning a selective surgery without invasive recordings. However, the studies reviewed in this paper strongly suggest that their analysis, in combination with other non-invasive data, might be useful to better delineate the epileptogenic zone, and help the implantation of intracerebral electrodes.
Influence of the critical EEG pattern on blood flow variations measured by single photon computed emission tomography
Arnaud Biraben, A. Bernard, Eric Seigneret, Jean-Marie Scarabin
patients with partial epilepsy. These two techniques reflect the temporal and spatial dimensions of the epileptic fit. More recently, ictal Single Photon Computed Tomography (SPECT) compared with interictal SPECT allows anatomo-clinical correlations. SPECT reflects variations of the regional cerebral blood flow (rCBF) during the seizure. These variations of the rCBF are linked with the electrical activity but the relations between electrical activity and rCBF have not been well studied and it is still difficult to compare ictal/interictal SPECT with the SEEG and EcoG data to delineate the EZ. From the few published studies, we know that, if the injection of the SPECT tracer is performed at the onset of the seizure, while the fast ictal discharge is still going on, we shall observe a local hyperperfusion in the region where the discharge started and in the region where it propagated secondarily. If the tracer injection is performed late during the seizure, or after the end of it, we shall observe a local hypoperfusion in these regions, this has also a good localizing value. Time of injection must be known, as it represents a key issue for SPECT interpretation.
Localization of distributed sources and comparison with functional MRI
Göran Lantz, Laurent Spinelli, Rolando Grave de Peralta Menendez, Margitta Seeck, Christoph M. Michel
functions with high spatial and temporal resolution. Single photon emission computer tomography (SPECT), positron emission tomography (PET), functional magnetic resonance imaging (fMRI) and high resolution electro- and magnetoencephalography (EEG and MEG) are currently intensively applied techniques to functional studies, each one having specific properties concerning spatial and temporal resolution.
The success of these methods in basic neuroscience research has led to the demand for applying them to clinical questions. Diseases of the central nervous system that lead to brain dysfunction can be ideally explored using these techniques. Of particular importance are those diseases in which a focal neuronal dysfunction is the primary cause and where surgical resection of this focus might be the cure. This is often the case for epilepsy, where a discrete primary focus might exist from which pathological rhythms evolve and propagate throughout the brain, leading to seizures that severely handicap the patient.
Surgical resection of the primary focus is only possible if the focus can be exactly localized and adequately separated from functionally important areas. This is where these new functional imaging tools become important. The use of SPECT and PET for focus localization has been most extensively studied and their specificity and sensitivity are intensively discussed. In the last few years functional MRI has evolved as a new interesting tool in epileptic focus localization. The most important limitation of these techniques, however, is the temporal resolution. Since epileptic activity can propagate very fast, several hyper- or hypoactive regions are seen in the images and primary areas cannot be distinguished from regions of propagation. The only methods that have sufficient temporal resolution to follow neuronal activity in real time are the electrophysiological measures, i.e. the EEG and the MEG. Localization of the sources in the brain that produced a given surface electromagnetic field has become possible through algorithms that solve the so-called "inverse problem". Several different algorithms exist and many groups begun to apply them to epileptic data with the aim to localize the focus of the pathological electrical discharges.
This review article discusses the use of distributed EEG source localization procedures in the presurgical evaluation of patients with intractable focal epilepsy. In contrast to equivalent dipole models, distributed localization methods do not localize one active point in the brain but rather assume extended active areas, which is generally the case in epileptic activity. The methods shown here are based on linear numerical methods and are therefore less prone to errors when working with scattered solution spaces such as the one defined by anatomical constraints. Solutions constraint to the gray matter determined in the individual MRI are shown here. We illustrate three methods to increase the spatial resolution of the source localization procedures: One is to increase the number of recording channels to more than 100, the second to use linear methods of high precision to detect focal sources (EPIFOCUS), and the third to combine EEG source localization with EEG-triggered functional magnetic resonance imaging. The importance of EEG source localization for the interpretation of fMRI data will be particularly discussed in view of the important difference of the temporal resolution by the two methods. The localization methods can be applied to interictal as well as to ictal activity. In case of analysis of ictal EEG we propose to use full scalp frequency analysis to determine the time period of seizure onset and to localize the sources of the initial dominant frequency.
Event-related variations in the activity of EEG-rhythms. Application to the physiology and the pathology of movements.
William Szurhaj, Etienne Labyt, Jean-Louis Bourriez, François Cassim, Luc Defebvre, Jean-Jacques Hauser, Jean-Daniel Guieu, Philippe Derambure
as evoked potentials. There is another type of change in the ongoing EEG, which is time-locked but not phase-locked to an event: the EEG rhythm reactivity, also called "Event-Related Desynchronization and Synchronization" (ERD/ERS) by Pfurtscheller. These changes are often visible to the naked eye but they cannot be extracted by the averaging technique. Their quantification requires another method, which was suggested by Pfurtscheller and Aranibar in 1977. This method consists in measuring the temporal evolution of the power of EEG signal within a given frequency band before, during, and after an event. ERD corresponds to the decrease in power of an EEG rhythm related to an event. Conversely, ERS corresponds to an increase in amplitude of an EEG rhythm related to the event. ERD represents the activation of the subjacent cortical areas. ERS would partly traduce the setting at rest of the cortex; it would also be related to the somesthetics afferents inputs. This method can be applied to the study of cortical activation in many situations: memory tasks, auditory processing, attention, anticipatory behavior, and voluntary movement. Thus, a voluntary self-paced movement of the dominant hand is preceded by an ERD of mu and beta rhythms occurring respectively 2 000 and 1 500 ms before the movement onset. This ERD is recorded over the contralateral central region. It becomes bilateral at the movement onset and reaches its maximum at the movement offset. It is then followed by an ERS of the beta rhythms. We show that ERD/ERS phenomena vary with the type of movement, and that their study allows exploring the modifications of cortical excitability that are observed in Parkinson's disease and in epilepsy with focal motor seizures.
Modeling EEG signals and interpreting measures of relationship during temporal-lobe seizures: an approach to the study of epileptogenic networks
Fabrice Wendling, Fabrice Bartolomei
methods, and more specially those dedicated to the estimation of signal interdependencies. In order to evaluate quantities provided by these methods and in order to relate them to the notion of functional coupling between cerebral structures, we developed a neurophysiologically relevant model able to generate EEG signals from organized networks of neural populations. We showed [2, 3] that the model can produce realistic multichannel epileptiform signals (when compared to real SEEG signals) under certain conditions (excitation/inhibition ratio within populations, uni/bi-directional coupling between populations). In this paper, the model framework is used to evaluate the performance of nonlinear regression analysis as a method to characterize couplings between cerebral structures from SEEG signals they produce. Two quantities, a nonlinear correlation coefficient and a direction index, respectively related to coupling parameters in the model (degree/direction) are presented. These two quantities are measured on real SEEG signals recorded in patients suffering from temporal lobe epilepsy and candidate for surgical treatment. Results show that the characterization of functional couplings leads to the identification of networks referred to as "epileptogenic networks" and that might be responsible for the triggering of seizures. These results also corroborate our previous results on the classification of temporal lobe epilepsies [4, 5] showing that a recurrent seizure pattern exists that can be classified on the basis of interactions between medial and lateral neocortical structures. From the identified networks, it is also possible to describe "propagation networks" with a different organization is different and which play a major role in the clinical expression of seizures.
Seizure anticipation by non-linear EEG analysis
Michel Le Van Quyen
new perspectives for studying the mechanisms of epileptogenesis as well as for possible therapeutic interventions which represent a major breakthrough. In this review we present and discuss the results from our group in this domain using nonlinear analysis of brain signals, as well as the limitations of this method and the remaining questions.
Synchrony, from cognition to seizure
Jack R. Foucher
contrast them with the "critical" one for their differentiation and their non-rhythmic properties. Lastly we will speculate on their significance in the recently described seizure anticipation paradigm and on the possibility that they could share common generators.
