Functional Connectivity Estimated from Intracranial EEG Predicts Surgical Outcome in Intractable Temporal Lobe Epilepsy

This project aimed to determine if a correlation-based measure of functional connectivity can identify epileptogenic zones from intracranial EEG signals, as well as to investigate the prognostic significance of such a measure on seizure outcome following temporal lobe lobectomy. To this end, we retrospectively analyzed 23 adult patients with intractable temporal lobe epilepsy (TLE) who underwent an invasive stereo-EEG (SEEG) evaluation between January 2009 year and January 2012. A follow-up of at least one year was required. The primary outcome measure was complete seizure-freedom at last follow-up. Functional connectivity between two areas in the temporal lobe that were sampled by two SEEG electrode contacts was defined as Pearson’s correlation coefficient of interictal activity between those areas. SEEG signals were filtered between 5 and 50 Hz prior to computing this correlation. The mean and standard deviation of the off diagonal elements in the connectivity matrix were also calculated. Analysis of the mean and standard deviation of the functional connections for each patient reveals that 90% of the patients who had weak and homogenous connections were seizure free one year after temporal lobectomy, whereas 85% of the patients who had stronger and more heterogeneous connections within the temporal lobe had recurrence of seizures. This suggests that temporal lobectomy is ineffective in preventing seizure recurrence for patients in whom the temporal lobe is characterized by weakly connected, homogenous networks. This pilot study shows promising potential of a simple measure of functional brain connectivity to identify epileptogenicity and predict the outcome of epilepsy surgery.

[1]  Wei Liao,et al.  Disrupted Causal Connectivity in Mesial Temporal Lobe Epilepsy , 2013, PloS one.

[2]  Naoaki Tanaka,et al.  Clinical applications of magnetoencephalography , 2009, Human brain mapping.

[3]  K. Lehnertz,et al.  Spatial Distribution of Neuronal Complexity Loss in Neocortical Lesional Epilepsies , 2000, Epilepsia.

[4]  H H Morris,et al.  Predictors of outcome after temporal lobectomy for the treatment of intractable epilepsy , 2006, Neurology.

[5]  Steven M. Pincus,et al.  Localization-related epilepsy exhibits significant connectivity away from the seizure-onset area , 2009, Neuroreport.

[6]  K. Lehnertz,et al.  Neuronal Complexity Loss in Interictal EEG Recorded with Foramen Ovale Electrodes Predicts Side of Primary Epileptogenic Area in Temporal Lobe Epilepsy: A Replication Study , 1998, Epilepsia.

[7]  Graeme D. Jackson,et al.  Cortical and thalamic resting-state functional connectivity is altered in childhood absence epilepsy , 2012, Epilepsy Research.

[8]  John S. Duncan,et al.  Motor system hyperconnectivity in juvenile myoclonic epilepsy: a cognitive functional magnetic resonance imaging study , 2011, Brain : a journal of neurology.

[9]  Jean Gotman,et al.  Seizure Anticipation: Do Mathematical Measures Correlate with Video‐EEG Evaluation? , 2005, Epilepsia.

[10]  M. Brazier Spread of seizure discharges in epilepsy: anatomical and electrophysiological considerations. , 1972, Experimental neurology.

[11]  G. Jackson,et al.  Functional connectivity networks are disrupted in left temporal lobe epilepsy , 2006, Annals of neurology.

[12]  Helmut Laufs,et al.  Functional imaging of seizures and epilepsy: evolution from zones to networks. , 2012, Current opinion in neurology.

[13]  Paul L. Nunez,et al.  REST: A good idea but not the gold standard , 2010, Clinical Neurophysiology.

[14]  Mark R. Bower,et al.  Synchrony in normal and focal epileptic brain: the seizure onset zone is functionally disconnected. , 2010, Journal of neurophysiology.

[15]  Mark P Richardson,et al.  Large scale brain models of epilepsy: dynamics meets connectomics , 2012, Journal of Neurology, Neurosurgery & Psychiatry.

[16]  Jorge Sepulcre,et al.  Localization of focal epileptic discharges using functional connectivity magnetic resonance imaging. , 2011, Journal of neurosurgery.

[17]  G. Avanzini,et al.  Enhanced frontocentral EEG connectivity in photosensitive generalized epilepsies: A partial directed coherence study , 2012, Epilepsia.

[18]  T S Walczak,et al.  Predicting long-term seizure outcome after resective epilepsy surgery , 2005, Neurology.

[19]  S. Spencer Neural Networks in Human Epilepsy: Evidence of and Implications for Treatment , 2002, Epilepsia.

[20]  Peter Rappelsberger,et al.  The reference problem and mapping of coherence: A simulation study , 2005, Brain Topography.

[21]  M. Brazier Studies of the EEG activity of limbic structures in man. , 1968, Electroencephalography and clinical neurophysiology.

[22]  R. Goodman,et al.  Cortical abnormalities in epilepsy revealed by local EEG synchrony , 2007, NeuroImage.

[23]  D. Tucker,et al.  EEG coherency. I: Statistics, reference electrode, volume conduction, Laplacians, cortical imaging, and interpretation at multiple scales. , 1997, Electroencephalography and clinical neurophysiology.

[24]  G. Karl Steinke,et al.  Brain Rhythms Reveal a Hierarchical Network Organization , 2011, PLoS Comput. Biol..

[25]  H. Lüders,et al.  Presurgical evaluation of epilepsy. , 2001, Brain : a journal of neurology.

[26]  J Gotman,et al.  Interhemispheric interactions in seizures of focal onset: data from human intracranial recordings. , 1987, Electroencephalography and clinical neurophysiology.

[27]  Nikos Makris,et al.  Automatically parcellating the human cerebral cortex. , 2004, Cerebral cortex.

[28]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[29]  L. Jehi Functional Connectivity in Mesial Temporal Lobe Epilepsy: A Dynamic Concept , 2012, Epilepsy currents.

[30]  Guillermo J. Ortega,et al.  Complex network analysis of human ECoG data , 2008, Neuroscience Letters.

[31]  Cheng Luo,et al.  Disrupted Functional Brain Connectivity in Partial Epilepsy: A Resting-State fMRI Study , 2012, PloS one.

[32]  Norman Tepley,et al.  An assessment of MEG coherence imaging in the study of temporal lobe epilepsy , 2011, Epilepsia.

[33]  M A B BRAZIER,et al.  Cross-correlation and autocorrelation studies of electroencephalographic potentials. , 1952, Electroencephalography and clinical neurophysiology.

[34]  J. Pastor,et al.  Synchronization Clusters of Interictal Activity in the Lateral Temporal Cortex of Epileptic Patients: Intraoperative Electrocorticographic Analysis , 2008, Epilepsia.

[35]  M. Kramer,et al.  Epilepsy as a Disorder of Cortical Network Organization , 2012, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[36]  J. Régis,et al.  Enhanced EEG functional connectivity in mesial temporal lobe epilepsy , 2008, Epilepsy Research.

[37]  Justin Dauwels,et al.  Localization of seizure onset area from intracranial non-seizure EEG by exploiting locally enhanced synchrony , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[38]  Regula S Briellmann,et al.  Temporal lobectomy: long-term seizure outcome, late recurrence and risks for seizure recurrence. , 2004, Brain : a journal of neurology.

[39]  P. Chauvel,et al.  Role of resting state functional connectivity MRI in presurgical investigation of mesial temporal lobe epilepsy , 2010, Journal of Neurology, Neurosurgery & Psychiatry.

[40]  Jean Gotman,et al.  Functional connectivity in patients with idiopathic generalized epilepsy , 2011, Epilepsia.

[41]  Riitta Salmelin,et al.  Magnetoencephalography: From SQUIDs to neuroscience Neuroimage 20th Anniversary Special Edition , 2012, NeuroImage.

[42]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

[43]  F. Mormann,et al.  Mean phase coherence as a measure for phase synchronization and its application to the EEG of epilepsy patients , 2000 .