Functional brain networks in epilepsy: recent advances in noninvasive mapping.

PURPOSE OF REVIEW Epilepsy is one of the most frequent chronic neurological disorders. Recent evidences strongly suggest that epilepsy is due to a dysfunction within an epileptic network, rather than due to the pathological activity of single sources. The aim of this article is to review the recent advances on functional connectivity revealed by noninvasive neuroimaging techniques. RECENT FINDINGS Functional connectivity detected through hemodynamic [functional MRI (fMRI)] and electro-magnetic techniques (EEG/MEG) in patients with epilepsy gives an insight into the physiopathogenesis of epileptic network underlying focal epilepsies and specific epileptic syndromes. An increasing number of studies suggest a relevance for surgical cases, both for localizing the focus and for predicting postsurgical cognitive impairment, based on the interactions between pathological and physiological networks. SUMMARY fMRI and EEG/MEG functional connectivity are complementary techniques and help in identifying the interactions between epileptic activity and physiological networks at different scales. Neuropsychological and neuropsychiatric impairment can be explained by such interactions. fMRI and EEG/MEG functional connectivity help in localizing important drivers of epileptic activity and can also help in predicting postsurgical outcome. Given the large number of methods applied, strict validation, mostly obtained in surgical series, is of utmost importance to understand the benefits and limitations of each technique.

[1]  B. W. van Dijk,et al.  Opportunities and methodological challenges in EEG and MEG resting state functional brain network research , 2015, Clinical Neurophysiology.

[2]  A. R. Anwar,et al.  Neuronal Networks in West Syndrome as Revealed by Source Analysis and Renormalized Partial Directed Coherence , 2012, Brain Topography.

[3]  Linda Douw,et al.  Epilepsy surgery outcome and functional network alterations in longitudinal MEG: A minimum spanning tree analysis , 2014, NeuroImage.

[4]  S Warach,et al.  Monitoring the patient's EEG during echo planar MRI. , 1993, Electroencephalography and clinical neurophysiology.

[5]  Georg Northoff,et al.  Resting-state functional magnetic resonance imaging: review of neurosurgical applications. , 2014, Neurosurgery.

[6]  Dustin Scheinost,et al.  Altered functional connectivity in seizure onset zones revealed by fMRI intrinsic connectivity , 2014, Neurology.

[7]  F. H. Lopes da Silva,et al.  Epileptic Neuronal Networks: Methods of Identification and Clinical Relevance , 2012, Front. Neurol..

[8]  Jeffery A. Hall,et al.  Electroencephalography/functional magnetic resonance imaging responses help predict surgical outcome in focal epilepsy , 2013, Epilepsia.

[9]  T. Valiante,et al.  Default mode network connectivity indicates episodic memory capacity in mesial temporal lobe epilepsy , 2013, Epilepsia.

[10]  C. Michel,et al.  Electric source imaging of interictal activity accurately localises the seizure onset zone , 2013, Journal of Neurology, Neurosurgery & Psychiatry.

[11]  Yu-Chien Wu,et al.  Improved mapping of interictal epileptiform discharges with EEG‐fMRI and voxel‐wise functional connectivity analysis , 2014, Epilepsia.

[12]  J. Foong,et al.  Temporal lobe epilepsy and affective disorders: the role of the subgenual anterior cingulate cortex , 2014, Journal of Neurology, Neurosurgery & Psychiatry.

[13]  Baxter P. Rogers,et al.  Evolution of Functional Connectivity of Brain Networks and Their Dynamic Interaction in Temporal Lobe Epilepsy , 2015, Brain Connect..

[14]  J. Gotman,et al.  Detection of abnormal resting-state networks in individual patients suffering from focal epilepsy: an initial step toward individual connectivity assessment , 2014, Front. Neurosci..

[15]  Karl J. Friston,et al.  Imaging the interaction: Epileptic discharges, working memory, and behavior , 2012, Human brain mapping.

[16]  Graeme D. Jackson,et al.  Insights into the Mechanisms of Absence Seizure Generation Provided by EEG with Functional MRI , 2014, Front. Neurol..

[17]  Taufik A. Valiante,et al.  Linking DMN connectivity to episodic memory capacity: What can we learn from patients with medial temporal lobe damage? , 2014, NeuroImage: Clinical.

[18]  M. Zijlmans,et al.  Different ways to analyze EEG–fMRI in focal epilepsy: Does it matter? , 2013, Clinical Neurophysiology.

[19]  H. Laufs,et al.  Decoding Wakefulness Levels from Typical fMRI Resting-State Data Reveals Reliable Drifts between Wakefulness and Sleep , 2014, Neuron.

[20]  Patrick Dupont,et al.  Correspondence between large‐scale ictal and interictal epileptic networks revealed by single photon emission computed tomography (SPECT) and electroencephalography (EEG)–functional magnetic resonance imaging (fMRI) , 2015, Epilepsia.

[21]  J. Gotman,et al.  Neuroimage: Clinical Patient-specific Connectivity Pattern of Epileptic Network in Frontal Lobe Epilepsy , 2022 .

[22]  M. Walker,et al.  Epileptic Networks in Focal Cortical Dysplasia Revealed Using Electroencephalography–Functional Magnetic Resonance Imaging , 2011, Annals of neurology.

[23]  Behavioral and Movement Disorders due to Long-Lasting Myoclonic Status Epilepticus Misdiagnosed as ADHD in a Patient With Juvenile Myoclonic Epilepsy , 2016, Clinical EEG and neuroscience.

[24]  J. Gotman.  Epileptic networks studied with EEG‐fMRI , 2008, Epilepsia.

[25]  M. Sperling,et al.  Early and Late Age of Seizure Onset have a Differential Impact on Brain Resting-State Organization in Temporal Lobe Epilepsy , 2014, Brain Topography.

[26]  Josemir W Sander.  The epidemiology of epilepsy revisited , 2003, Current opinion in neurology.

[27]  M. Symms,et al.  Factors affecting reorganisation of memory encoding networks in temporal lobe epilepsy , 2015, Epilepsy Research.

[28]  Margitta Seeck,et al.  Dynamic directed interictal connectivity in left and right temporal lobe epilepsy , 2015, Epilepsia.

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

[30]  Margot J. Taylor,et al.  Resilience of developing brain networks to interictal epileptiform discharges is associated with cognitive outcome. , 2014, Brain : a journal of neurology.

[31]  V. Iragui,et al.  Frontolimbic brain networks predict depressive symptoms in temporal lobe epilepsy , 2014, Epilepsy Research.

[32]  P. Avanzini,et al.  The visual system in eyelid myoclonia with absences , 2014, Annals of neurology.

[33]  Stephan Wolff,et al.  EEG-fMRI in myoclonic astatic epilepsy (Doose syndrome) , 2014, Neurology.

[34]  Alan C. Evans,et al.  Multi-level bootstrap analysis of stable clusters in resting-state fMRI , 2009, NeuroImage.

[35]  Christoph M. Michel,et al.  Head model and electrical source imaging: A study of 38 epileptic patients☆ , 2014, NeuroImage: Clinical.

[36]  Fahmeed Hyder,et al.  Increased resting functional connectivity in spike‐wave epilepsy in WAG/Rij rats , 2013, Epilepsia.

[37]  Jean Gotman,et al.  Epileptic Discharges Affect the Default Mode Network – fMRI and Intracerebral EEG Evidence , 2013, PloS one.

[38]  M. Brodie,et al.  Definition of drug resistant epilepsy: Consensus proposal by the ad hoc Task Force of the ILAE Commission on Therapeutic Strategies , 2011 .

[39]  M. Symms,et al.  Levetiracetam reduces abnormal network activations in temporal lobe epilepsy , 2014, Neurology.

[40]  Gavin P. Winston,et al.  Memory fMRI predicts verbal memory decline after anterior temporal lobe resection , 2015, Neurology.

[41]  John S. Duncan,et al.  Motor co-activation in siblings of patients with juvenile myoclonic epilepsy: an imaging endophenotype? , 2014, Brain : a journal of neurology.

[42]  Ivanka Savic,et al.  Juvenile myoclonic epilepsy — Neuroimaging findings , 2013, Epilepsy & Behavior.

[43]  Aaron E. L. Warren,et al.  Lennox‐Gastaut syndrome and phenotype: Secondary network epilepsies , 2014, Epilepsia.

[44]  C. Bénar,et al.  Interictal networks in Magnetoencephalography , 2014, Human brain mapping.

[45]  Laura Astolfi,et al.  The physiological plausibility of time-varying Granger-causal modeling: Normalization and weighting by spectral power , 2014, NeuroImage.

[46]  L. Tassi,et al.  Intracranial time–frequency correlates of seizure-related negative BOLD response in the sensory-motor network , 2015, Clinical Neurophysiology.

[47]  G. Holmes,et al.  Hippocampal interictal epileptiform activity disrupts cognition in humans , 2013, Neurology.