Fabrice Bartolomei

Prof. Fabrice Bartolomei

Institut de Neuroscience des Systèmes, Aix-Marseille University, Marseille, France
orcid

Research Focus & Metrics

Academic Career Length

28Years (1999-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
20 May 2017 in Epilepsia
Verified
Journal Article
Open access
PDF file
FBFabrice Bartolomei
Fabrice Bartolomei
SLStanislas Lagarde
Stanislas Lagarde
FWFabrice Wendling
Fabrice Wendling
AMAileen McGonigal
Aileen McGonigal
VJViktor Jirsa
Viktor Jirsa
CBChristian Bénar
Christian Bénar
Summary: Epileptogenic networks are defined by the brain regions involved in the production and propagation of epileptic activities. In this review we describe the historical, methodologic, and conceptual bases of this model in the analysis of electrophysiologic intracerebral recordings. In the context of epilepsy surgery, the determination of cerebral regions producing seizures (i.e., the “epileptogenic zone”) is a crucial objective. In contrast with a traditional focal vision of focal drug‐resistant epilepsies, the concept of epileptogenic networks has been progressively introduced as a model better able to describe the complexity of seizure dynamics and realistically describe the distribution of epileptogenic anomalies in the brain. The concept of epileptogenic networks is historically linked to the development of the stereoelectroencephalography (SEEG) method and subsequent introduction of means of quantifying the recorded signals. Seizures, and preictal and interictal discharges produce clear patterns on SEEG. These patterns can be analyzed utilizing signal analysis methods that quantify high‐frequency oscillations or changes in functional connectivity. Dramatic changes in SEEG brain connectivity can be described during seizure genesis and propagation within cortical and subcortical regions, associated with the production of different patterns of seizure semiology. The interictal state is characterized by networks generating abnormal activities (interictal spikes) and also by modified functional properties. The introduction of novel approaches to large‐scale modeling of these networks offers new methods in the goal of better predicting the effects of epilepsy surgery. The epileptogenic network concept is a key factor in identifying the anatomic distribution of the epileptogenic process, which is particularly important in the context of epilepsy surgery.

13 June 2008 in Brain
Verified
Journal Article
Open access
PDF file
FBFabrice Bartolomei
Fabrice Bartolomei
PCPatrick Chauvel
Patrick Chauvel
FWFabrice Wendling
Fabrice Wendling
The identification of brain regions generating seizures (‘epileptogenic zone’, EZ) in patients with refractory partial epilepsy is crucial prior to surgery. During pre-surgical evaluation, this identification can be performed from the analysis of intracerebral EEG. In particular, the presence of high-frequency oscillations, often referred to as ‘rapid discharges’, has long been recognized as a characteristic electrophysiological pattern of the EZ. However, to date, there has been no attempt to make use of this specific pattern to quantitatively evaluate the degree of epileptogenicity in recorded structures. A novel quantitative measure that characterizes the epileptogenicity of brain structures recorded with depth electrodes is presented. This measure, called ‘Epileptogenicity Index’ (EI), is based on both spectral (appearance of fast oscillations replacing the background activity) and temporal (delay of appearance with respect to seizure onset) properties of intracerebral EEG signals. EI values were computed in mesial and lateral structures of the temporal lobe in a group of 17 patients with mesial temporal lobe epilepsy (MTLE). Statistically high EI values corresponded to structures involved early in the ictal process and producing rapid discharges at seizure onset. In all patients, these high values were obtained in more than one structure of the temporal lobe region. In the majority of patients, highest EI values were computed from signals recorded in mesial structures. In addition, when averaged over patients, EI values gradually decreased from structure to structure. For lateral neocortex, higher EI values were found in patients with normal MRI, in contrast with patients with hippocampal sclerosis. In this former sub-group of patients, a greater number of epileptogenic structures was also found. A statistically significant correlation was found between the duration of epilepsy and the number of structures disclosing high epileptogenicity suggesting that MTLE is a gradually evolving process in which the epileptogenicity of the temporal lobe tends to increase with time.

30 June 2017 in Epilepsia
Verified
Journal Article
Open access
PDF file
BFBirgit Frauscher
Birgit Frauscher
FBFabrice Bartolomei
Fabrice Bartolomei
KKKatsuhiro Kobayashi
Katsuhiro Kobayashi
JCJan Cimbalnik
Jan Cimbalnik
MKMaryse A. van ‘t Klooster
Maryse A. van ‘t Klooster
JGJean Gotman
Jean Gotman
Summary: Modern electroencephalographic (EEG) technology contributed to the appreciation that the EEG signal outside the classical Berger frequency band contains important information. In epilepsy, research of the past decade focused particularly on interictal high‐frequency oscillations (HFOs) > 80 Hz. The first large application of HFOs was in the context of epilepsy surgery. This is now followed by other applications such as assessment of epilepsy severity and monitoring of antiepileptic therapy. This article reviews the evidence on the clinical use of HFOs in epilepsy with an emphasis on the latest developments. It highlights the growing literature on the association between HFOs and postsurgical seizure outcome. A recent meta‐analysis confirmed a higher resection ratio for HFOs in seizure‐free versus non–seizure‐free patients. Residual HFOs in the postoperative electrocorticogram were shown to predict epilepsy surgery outcome better than preoperative HFO rates. The review further discusses the different attempts to separate physiological from epileptic HFOs, as this might increase the specificity of HFOs. As an example, analysis of sleep microstructure demonstrated a different coupling between HFOs inside and outside the epileptogenic zone. Moreover, there is increasing evidence that HFOs are useful to measure disease activity and assess treatment response using noninvasive EEG and magnetoencephalography. This approach is particularly promising in children, because they show high scalp HFO rates. HFO rates in West syndrome decrease after adrenocorticotropic hormone treatment. Presence of HFOs at the time of rolandic spikes correlates with seizure frequency. The time‐consuming visual assessment of HFOs, which prevented their clinical application in the past, is now overcome by validated computer‐assisted algorithms. HFO research has considerably advanced over the past decade, and use of noninvasive methods will make HFOs accessible to large numbers of patients. Prospective multicenter trials are awaited to gather information over long recording periods in large patient samples.

1 September 2006 in Clinical Neurophysiology
Verified
Journal Article
Closed access
FBFabrice Bartolomei
Fabrice Bartolomei
IBIngeborg Bosma
Ingeborg Bosma
MKMartin Klein
Martin Klein
JBJohannes C. Baayen
Johannes C. Baayen
JRJaap C. Reijneveld
Jaap C. Reijneveld
CSCornelis J. Stam
Cornelis J. Stam

13 November 2018 in Epilepsia
Verified
Journal Article
Closed access
PDF file
SLStanislas Lagarde
Stanislas Lagarde
SBSinziana Buzori
Sinziana Buzori
ATAgnès Trebuchon
Agnès Trebuchon
RCRomain Carron
Romain Carron
DSDidier Scavarda
Didier Scavarda
FBFabrice Bartolomei
Fabrice Bartolomei

22 December 2005 in Annals of Neurology
Verified
Journal Article
Closed access
PDF file
FBFabrice Bartolomei
Fabrice Bartolomei
IBIngeborg Bosma
Ingeborg Bosma
MKMartin Klein
Martin Klein
JBJohannes C. Baayen
Johannes C. Baayen
JRJaap C. Reijneveld
Jaap C. Reijneveld
CSCornelis J. Stam
Cornelis J. Stam