Literature DB >> 15661121

A method to identify reproducible subsets of co-activated structures during interictal spikes. Application to intracerebral EEG in temporal lobe epilepsy.

J Bourien1, F Bartolomei, J J Bellanger, M Gavaret, P Chauvel, F Wendling.   

Abstract

OBJECTIVE: We present a novel quantitative method to statistically analyze the distribution of multichannel intracerebral interictal spikes (multi-IIS) in stereoelectroencephalographic (SEEG) recordings. The method automatically extracts groups of brain structures conjointly and frequently involved in the generation of interictal activity. These groups are referred to as 'subsets of co-activated structures' (SCAS). We applied the method to long duration interictal recordings in patients with mesial temporal lobe epilepsy (MTLE) and analyzed the reproducibility of subsets of structures involved in the generation of multi-IIS for each patient and among patients.
METHODS: Fifteen patients underwent long-term intracerebral EEG recording (SEEG technique) using depth electrodes. A 1 h period of continuous interictal EEG recording was selected for each patient with precautions regarding the time after anesthesia pre-SEEG, the temporal distance with respect to seizures, the vigilance state of the patient, and the anti-epileptic drug withdrawal. A research of SCAS was conducted on each recording using the developed method that includes 3 steps: (i) automatic detection of monochannel intracerebral interictal spikes (mono-IIS), (ii) formation of multi-IIS using a temporal sliding window, and (iii) extraction of SCAS. In the third step, statistical tests are used to evaluate the frequency of multi-IIS as well as their significance (with respect to the 'random distribution of mono-IIS' case).
RESULTS: In each patient, several thousands of multi-IIS (mean+/-SD, 3322+/-2190) were formed and several SCAS (mean+/-SD, 3.80+/-1.47) were automatically extracted. Results show that reproducible subsets of brain structures are involved in the generation of interictal activity. Although SCAS were found to be variable from one patient to another, some invariant information was pointed up. In all patients, multi-IIS distribute over two distinct groups of structures: mesial structures (15/15) and lateral structures (7/15). Moreover, two particular structures, the internal temporal pole and the temporo-basal cortex, may be conjointly involved with either the first or the second group. Finally, some extracted SCAS seem to match well-defined anatomo-functional circuits of the temporal lobe. CONCLUSIONS AND SIGNIFICANCE: During interictal activity in MTLE, similar subsets of temporal lobe structures are involved in the generation of spikes. This paper brings statistical evidence for the existence of these subsets and presents a method to automatically extract them from SEEG recordings. Interictal activity is spatially organized in the temporal lobe and preferentially involves two functional systems of the temporal lobe (either mesial or lateral).

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Year:  2005        PMID: 15661121     DOI: 10.1016/j.clinph.2004.08.010

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  27 in total

1.  A candidate mechanism underlying the variance of interictal spike propagation.

Authors:  Helen R Sabolek; Waldemar B Swiercz; Kyle P Lillis; Sydney S Cash; Gilles Huberfeld; Grace Zhao; Linda Ste Marie; Stéphane Clemenceau; Greg Barsh; Richard Miles; Kevin J Staley
Journal:  J Neurosci       Date:  2012-02-29       Impact factor: 6.167

2.  Time-domain features of epileptic spikes as potential bio-markers of the epileptogenesis process.

Authors:  Clement Huneau; Sophie Demont-Guignard; Pascal Benquet; Benoit Martin; Fabrice Wendling
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2010

3.  Maximum decoding abilities of temporal patterns and synchronized firings: application to auditory neurons responding to click trains and amplitude modulated white noise.

Authors:  Boris Gourévitch; Jos J Eggermont
Journal:  J Comput Neurosci       Date:  2009-04-17       Impact factor: 1.621

4.  Reference-based source separation method for identification of brain regions involved in a reference state from intracerebral EEG.

Authors:  Samareh Samadi; Ladan Amini; Delphine Cosandier-Rimélé; Hamid Soltanian-Zadeh; Christian Jutten
Journal:  IEEE Trans Biomed Eng       Date:  2013-02-14       Impact factor: 4.538

5.  Genetic Programming and Frequent Itemset Mining to Identify Feature Selection Patterns of iEEG and fMRI Epilepsy Data.

Authors:  Otis Smart; Lauren Burrell
Journal:  Eng Appl Artif Intell       Date:  2015-03       Impact factor: 6.212

6.  The seizure onset zone drives state-dependent epileptiform activity in susceptible brain regions.

Authors:  Joshua M Diamond; Julio I Chapeton; William H Theodore; Sara K Inati; Kareem A Zaghloul
Journal:  Clin Neurophysiol       Date:  2019-07-02       Impact factor: 3.708

7.  Electrophysiological Brain Connectivity: Theory and Implementation.

Authors:  Bin He; Laura Astolfi; Pedro A Valdes-Sosa; Daniele Marinazzo; Satu Palva; Christian G Benar; Christoph M Michel; Thomas Koenig
Journal:  IEEE Trans Biomed Eng       Date:  2019-05-07       Impact factor: 4.538

8.  Unsupervised Learning of Spatiotemporal Interictal Discharges in Focal Epilepsy.

Authors:  Maxime O Baud; Jonathan K Kleen; Gopala K Anumanchipalli; Liberty S Hamilton; Yee-Leng Tan; Robert Knowlton; Edward F Chang
Journal:  Neurosurgery       Date:  2018-10-01       Impact factor: 4.654

9.  Analysis of intracerebral EEG recordings of epileptic spikes: insights from a neural network model.

Authors:  Sophie Demont-Guignard; Pascal Benquet; Urs Gerber; Fabrice Wendling
Journal:  IEEE Trans Biomed Eng       Date:  2009-07-31       Impact factor: 4.538

Review 10.  Spatial analysis of intracerebral electroencephalographic signals in the time and frequency domain: identification of epileptogenic networks in partial epilepsy.

Authors:  Fabrice Wendling; Fabrice Bartolomei; Lotfi Senhadji
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2009-01-28       Impact factor: 4.226

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