Cortical abnormalities in epilepsy revealed by local EEG synchrony
Introduction
Resective epilepsy surgery for refractory seizures targets the epileptogenic zone, the minimum region of cortex whose removal is both necessary and sufficient to abolish seizures (Luders and Awad, 1991, Engel, 2003). Analysis of intracranial EEG (ICEEG) ictal recordings to identify the epileptogenic zone is generally more specific than information provided by seizure semiology, neuroimaging or neuropsychological testing (Engel et al., 1990). Visual interpretation of the intracranial EEG (ICEEG) is a clinically reliable tool for identifying the epileptogenic zone in mesial temporal epilepsy (Pacia and Ebersole, 1999) but has more variable success in predicting surgical control of neocortical seizures, particularly in cases where neuroimaging does not show focal abnormalities (Alarcon et al., 1995, Ebersole, 1999, Jung et al., 1999).
While the interpretation of the ICEEG has traditionally been oriented toward paroxysmal epileptiform disturbances of cerebral activity, it is known that persistent non-epileptiform background abnormalities, for example focal delta range activity, are characteristic of dysfunctional cortical regions. Paroxysmal epileptiform discharges are thought to be more specific for epileptogenicity. Extending interictal ICEEG interpretation using quantitative techniques, however, has disclosed critical background features relevant to surgical decision-making that are not apparent to visual inspection. For example, very high frequency (> 100 Hz), low amplitude activity (< 5 μV) has been associated with the epileptogenic zone (Worrell et al., 2004, Alarcon et al., 1995, Allen et al., 1992), as has neuronal synchrony recorded from hippocampal microelectrodes (Colder et al., 1996) and spectrogram measurements of EEG amplitude (Asano et al., 2004). Such techniques may be used to detect signatures of cortical abnormality that are not necessarily associated with the well-known paroxysmal features, and that may be linked to seizures. Markers of abnormal tissue have the advantage that they may be more persistent and therefore more reliably detectable than paroxysmal features. To be useful in epilepsy surgical evaluations, such markers would be based on EEG features which closely relate to epileptogenic potential rather than being nonspecific correlates of dysfunction, as well as having a wide diagnostic index; that is, areas of abnormality should be consistently and markedly different from normal.
We hypothesize that enhanced local synchrony detected in ICEEG recordings may be a marker of epileptogenicity, reflecting abnormal functional connectivity within epileptogenic cortex. A mathematical model of a cortical neuronal network provides support for the view that greater connectivity per se among neurons, without alteration of individual firing thresholds, may be sufficient to confer an epileptogenic state (Traub et al., 2001). Accordingly, abnormally enhanced synchrony may be expected to be apparent in the background EEG, apart from spike discharges, as it reflects a fundamental property of the underlying cortex. Indeed, coherence, a normalized frequency-dependent measure of correlation, has been shown to be increased over tumors and regions thought to be part of the epileptogenic zone (Towle et al., 1998, Towle et el., 1999, Zaveri et al., 1999). Similarly, changes in phase synchrony, a related measured that has been used to detect EEG changes before seizure onset, also appear to be most prominent proximate to the epileptogenic zone (Lehnertz and Elger, 1995, Le Van Quyen et al., 2001, Le Van Quyen et al., 2005, Chavez et al., 2003, Mormann et al., 2003).
We report an investigation into spatial patterns of local synchrony in epilepsy patients with medically refractory partial epilepsy using a measure of phase coherence in wide-band ICEEG signals (Mormann et al., 2000). Based on synchrony measurements of the EEG signals recorded from orthogonally adjacent pairs of electrodes in subdural grids, we are able to define regions of local hypersynchrony (LH) in which there are markedly higher levels of synchrony compared to surrounding brain regions. Although the primary goal of this paper is to define the properties of these hypersynchronous regions, we also investigate a possible correlation with the epileptogenic zone. Cortical landmarks that may have the LH property include structural abnormalities identified on neuroimaging that have given rise to seizures, areas in which active paroxysmal activity is present, and areas adjacent to ictal onset zones.
Section snippets
Methods
Data were collected from patients undergoing ICEEG monitoring prior to resective surgery at Columbia University and New York University Medical Centers. IRB approval for the retrospective analysis of clinical data was obtained at both institutions. Arrays of platinum electrodes, 5 mm in diameter with 10 mm center-to-center spacing (AdTech), were implanted subdurally at sites determined clinically to be likely to encompass the seizure onset zone. Data were sampled at 250 Hz/channel and band-pass
Results
Nine patients were studied (9–54 years, mean 31 years). Epilepsy duration ranged from 1 month to 42 years (mean 18.8 years). The location of the subdural grids, associated pathology, the locations of the resections and LH regions, and surgical outcome are summarized in Table 1. Overall, the surgical resection included all locally hypersynchronous areas in two patients (5 and 6) and did not include all such regions in six patients (1, 2, 3, 7, 8 and 9). Seizure outcome following surgery was
Discussion
Mean phase coherence calculated on orthogonally adjacent electrode pairs provides spatial and temporal information about phase locking of local field potentials at neighboring sites in the neocortex. The distribution of the obtained measurements is characterized by a consistent positive skew, and may be explained by two sets of normally distributed values with differing means. Similar observations have been made for measurements of coherence in ECoG recordings (Towle et al., 1998). Our findings
Acknowledgments
Financial Interests: This work was supported by NINDS grants 1 K08 NS48871 R1A1 and 5 K12 NS001698.
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