‘Functional Connectivity’ Is a Sensitive Predictor of Epilepsy Diagnosis after the First Seizure

Background: Although epilepsy affects almost 1 % of the world population, diagnosis of this debilitating disease is still difficult. The EEG is an important tool for epilepsy diagnosis and classification, but the sensitivity of interictal epileptiform discharges (IEDs) on the first EEG is only 30–50%. Here we investigate whether using ‘functional connectivity ’ can improve the diagnostic sensitivity of the first interictal EEG in the diagnosis of epilepsy. Methodology/Principal Findings: Patients were selected from a database with 390 standard EEGs of patients after a first suspected seizure. Patients who were later diagnosed with epilepsy (i.e. $two seizures) were compared to matched nonepilepsy patients (with a minimum follow-up of one year). The synchronization likelihood (SL) was used as an index of functional connectivity of the EEG, and average SL per patient was calculated in seven frequency bands. In total, 114 patients were selected. Fifty-seven patients were diagnosed with epilepsy (20 had IEDs on their EEG) and 57 matched patients had other diagnoses. Epilepsy patients had significantly higher SL in the theta band than non-epilepsy patients. Furthermore, theta band SL proved to be a significant predictor of a diagnosis of epilepsy. When only those epilepsy patients without IEDs were considered (n = 74), theta band SL could predict diagnosis with specificity of 76 % and sensitivity of 62%. Conclusion/Significance: Theta band functional connectivity may be a useful diagnostic tool in diagnosing epilepsy

A closed loop brain-machine interface for epilepsy control using dorsal column electrical stimulation

Although electrical neurostimulation has been proposed as an alternative treatment for drug-resistant cases of epilepsy, current procedures such as deep brain stimulation, vagus, and trigeminal nerve stimulation are effective only in a fraction of the patients. Here we demonstrate a closed loop brain-machine interface that delivers electrical stimulation to the dorsal column (DCS) of the spinal cord to suppress epileptic seizures. Rats were implanted with cortical recording microelectrodes and spinal cord stimulating electrodes, and then injected with pentylenetetrazole to induce seizures. Seizures were detected in real time from cortical local field potentials, after which DCS was applied. This method decreased seizure episode frequency by 44% and seizure duration by 38%. We argue that the therapeutic effect of DCS is related to modulation of cortical theta waves, and propose that this closed-loop interface has the potential to become an effective and semi-invasive treatment for refractory epilepsy and other neurological disorders.We are grateful for the assistance from Jim Meloy for the design and production of the multielectrode arrays as well as setup development and maintenance, Laura Oliveira, Terry Jones, and Susan Halkiotis for administrative assistance and preparation of the manuscript. This work was funded by a grant from The Hartwell Foundation.info:eu-repo/semantics/publishedVersio

Single-neuron dynamics in human focal epilepsy

Epileptic seizures are traditionally characterized as the ultimate expression of monolithic, hypersynchronous neuronal activity arising from unbalanced runaway excitation. Here we report the first examination of spike train patterns in large ensembles of single neurons during seizures in persons with epilepsy. Contrary to the traditional view, neuronal spiking activity during seizure initiation and spread was highly heterogeneous, not hypersynchronous, suggesting complex interactions among different neuronal groups even at the spatial scale of small cortical patches. In contrast to earlier stages, seizure termination is a nearly homogenous phenomenon followed by an almost complete cessation of spiking across recorded neuronal ensembles. Notably, even neurons outside the region of seizure onset showed significant changes in activity minutes before the seizure. These findings suggest a revision of current thinking about seizure mechanisms and point to the possibility of seizure prevention based on spiking activity in neocortical neurons

Disrupted Functional Brain Connectivity in Partial Epilepsy: A Resting-State fMRI Study

Examining the spontaneous activity to understand the neural mechanism of brain disorder is a focus in recent resting-state fMRI. In the current study, to investigate the alteration of brain functional connectivity in partial epilepsy in a systematical way, two levels of analyses (functional connectivity analysis within resting state networks (RSNs) and functional network connectivity (FNC) analysis) were carried out on resting-state fMRI data acquired from the 30 participants including 14 healthy controls(HC) and 16 partial epilepsy patients. According to the etiology, all patients are subdivided into temporal lobe epilepsy group (TLE, included 7 patients) and mixed partial epilepsy group (MPE, 9 patients). Using group independent component analysis, eight RSNs were identified, and selected to evaluate functional connectivity and FNC between groups. Compared with the controls, decreased functional connectivity within all RSNs was found in both TLE and MPE. However, dissociating patterns were observed within the 8 RSNs between two patient groups, i.e, compared with TLE, we found decreased functional connectivity in 5 RSNs increased functional connectivity in 1 RSN, and no difference in the other 2 RSNs in MPE. Furthermore, the hierarchical disconnections of FNC was found in two patient groups, in which the intra-system connections were preserved for all three subsystems while the lost connections were confined to intersystem connections in patients with partial epilepsy. These findings may suggest that decreased resting state functional connectivity and disconnection of FNC are two remarkable characteristics of partial epilepsy. The selective impairment of FNC implicated that it is unsuitable to understand the partial epilepsy only from global or local perspective. We presumed that studying epilepsy in the multi-perspective based on RSNs may be a valuable means to assess the functional changes corresponding to specific RSN and may contribute to the understanding of the neuro-pathophysiological mechanism of epilepsy

Interictal Functional Connectivity of Human Epileptic Networks Assessed by Intracerebral EEG and BOLD Signal Fluctuations

In this study, we aimed to demonstrate whether spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal derived from resting state functional magnetic resonance imaging (fMRI) reflect spontaneous neuronal activity in pathological brain regions as well as in regions spared by epileptiform discharges. This is a crucial issue as coherent fluctuations of fMRI signals between remote brain areas are now widely used to define functional connectivity in physiology and in pathophysiology. We quantified functional connectivity using non-linear measures of cross-correlation between signals obtained from intracerebral EEG (iEEG) and resting-state functional MRI (fMRI) in 5 patients suffering from intractable temporal lobe epilepsy (TLE). Functional connectivity was quantified with both modalities in areas exhibiting different electrophysiological states (epileptic and non affected regions) during the interictal period. Functional connectivity as measured from the iEEG signal was higher in regions affected by electrical epileptiform abnormalities relative to non-affected areas, whereas an opposite pattern was found for functional connectivity measured from the BOLD signal. Significant negative correlations were found between the functional connectivities of iEEG and BOLD signal when considering all pairs of signals (theta, alpha, beta and broadband) and when considering pairs of signals in regions spared by epileptiform discharges (in broadband signal). This suggests differential effects of epileptic phenomena on electrophysiological and hemodynamic signals and/or an alteration of the neurovascular coupling secondary to pathological plasticity in TLE even in regions spared by epileptiform discharges. In addition, indices of directionality calculated from both modalities were consistent showing that the epileptogenic regions exert a significant influence onto the non epileptic areas during the interictal period. This study shows that functional connectivity measured by iEEG and BOLD signals give complementary but sometimes inconsistent information in TLE

Seizure prediction : ready for a new era

Acknowledgements: The authors acknowledge colleagues in the international seizure prediction group for valuable discussions. L.K. acknowledges funding support from the National Health and Medical Research Council (APP1130468) and the James S. McDonnell Foundation (220020419) and acknowledges the contribution of Dean R. Freestone at the University of Melbourne, Australia, to the creation of Fig. 3.Peer reviewedPostprin