Faculty Bibliography

OBJECTIVE:To develop an algorithm for the automatic quantitative description and detection of spikes in the intracranial EEG and quantify the relationship between prominent spikes and the seizure onset zone. METHODS:An algorithm was developed for the quantification of time-frequency properties of spikes (upslope, instantaneous energy, downslope) and their statistical representation in a univariate generalized extreme value distribution. Its performance was evaluated in comparison to expert detection of spikes in intracranial EEG recordings from 10 patients. It was subsequently used in 18 patients to detect prominent spikes and quantify their spatial relationship to the seizure onset area. RESULTS:The algorithm displayed an average sensitivity of 63.4% with a false detection rate of 3.2 per minute for the detection of individual spikes and an average sensitivity of 88.6% with a false detection rate of 1.4% for the detection of intracranial EEG contacts containing the most prominent spikes. Prominent spikes occurred closer to the seizure onset area than less prominent spikes but they overlapped with it only in a minority of cases (3/18). CONCLUSIONS:Automatic detection and quantification of the morphology of spikes increases their utility to localize the seizure onset area. Prominent spikes tend to originate mostly from contacts located in the close vicinity of the seizure onset area rather than from within it. SIGNIFICANCE/CONCLUSIONS:Quantitative analysis of time-frequency characteristics and spatial distribution of intracranial spikes provides complementary information that may be useful for the localization of the seizure-onset zone.

OBJECTIVE:Secondary generalization of seizures has devastating consequences for patient safety and quality of life. The aim of this intracranial electroencephalography (icEEG) study was to investigate the differences in onset and propagation patterns of temporal lobe seizures that remained focal versus those with secondary generalization, in order to better understand the mechanism of secondary generalization. METHODS:A total of 39 seizures were analyzed in nine patients who met the following criteria: (1) icEEG-video monitoring with at least one secondarily generalized tonic-clonic seizure (GTCS), (2) pathologically proven hippocampal sclerosis, and (3) no seizures for at least 1 year after anteromedial temporal lobe resection. Seizures were classified as focal or secondary generalized by behavioral analysis of video. Onset and propagation patterns were compared by analysis of icEEG. RESULTS:We obtained data from 22 focal seizures without generalization (FS), and 17 GTCS. Seizure-onset patterns did not differ between FS and GTCS, but there were differences in later propagation. All seizures started with low voltage fast activity, except for seven seizures in one patient (six FS, one GTCS), which started with sharply contoured theta activity. Fifteen of 39 seizures started from the hippocampus, and 24 seizures (including six seizures in a patient without hippocampal contacts) started from other medial temporal lobe areas. We observed involvement or more prominent activation of the posterior-lateral temporal regions in GTCS prior to propagation to the other cortical regions, versus FS, which had no involvement or less prominent activation of the posterior lateral temporal cortex. Occipital contacts were not involved at the time of clinical secondary generalization. SIGNIFICANCE/CONCLUSIONS:The posterior-lateral temporal cortex may serve as an important "gateway" controlling propagation of medial temporal lobe seizures to other cortical regions. Identifying the mechanisms of secondary generalization of focal seizures could lead to improved treatments to confine seizure spread.

Intracranial EEG (icEEG) provides a critical road map for epilepsy surgery but it has become increasingly difficult to interpret as technology has allowed the number of icEEG channels to grow. Borrowing methods from neuroimaging, we aimed to simplify data analysis and increase consistency between reviewers by using 3D surface projections of intracranial EEG poweR (3D-SPIER). We analyzed 139 seizures from 48 intractable epilepsy patients (28 temporal and 20 extratemporal) who had icEEG recordings, epilepsy surgery, and at least one year of post-surgical follow-up. We coregistered and plotted icEEG β frequency band signal power over time onto MRI-based surface renderings for each patient, to create color 3D-SPIER movies. Two independent reviewers interpreted the icEEG data using visual analysis vs. 3D-SPIER, blinded to any clinical information. Overall agreement rates between 3D-SPIER and icEEG visual analysis or surgery were about 90% for side of seizure onset, 80% for lobe, and just under 80% for sublobar localization. These agreement rates were improved when flexible thresholds or frequency ranges were allowed for 3D-SPIER, especially for sublobar localization. Interestingly, agreement was better for patients with good surgical outcome than for patients with poor outcome. Localization using 3D-SPIER was measurably faster and considered qualitatively easier to interpret than visual analysis. These findings suggest that 3D-SPIER could be an improved diagnostic method for presurgical seizure localization in patients with intractable epilepsy and may also be useful for mapping normal brain function.

Intracranial electro-encephalography (icEEG) provides a unique opportunity to record directly from the human brain and is clinically important for planning epilepsy surgery. However, traditional visual analysis of icEEG is often challenging. The typical simultaneous display of multiple electrode channels can prevent an in-depth understanding of the spatial-time course of brain activity. In recent decades, advances in the field of neuroimaging have provided powerful new tools for the analysis and display of signals in the brain. These methods can now be applied to icEEG to map electrical signal information onto a three-dimensional rendering of a patient's cortex and graphically observe the changes in voltage over time. This approach provides rapid visualization of seizures and normal activity propagating over the brain surface and can also illustrate subtle changes that might be missed by traditional icEEG analysis. In addition, the direct mapping of signal information onto accurate anatomical structures can assist in the precise targeting of sites for epilepsy surgery and help correlate electrical activity with behavior. Bringing icEEG data into a standardized anatomical space will also enable neuroimaging methods of statistical analysis to be applied. As new technologies lead to a dramatic increase in the rate of data acquisition, these novel visualization and analysis techniques will play an important role in processing the valuable information obtained through icEEG.

Impaired consciousness in epilepsy has a major negative impact on quality of life. Prior work suggests that complex partial seizures (CPS) and generalized tonic-clonic seizures (GTCS), which both cause loss of consciousness, affect similar frontoparietal networks. Milder involvement in CPS than in GTCS may spare some simple behavioral responses, resembling the minimally conscious state. However, this difference in responses has not been rigorously tested previously. During video-electroencephalography (EEG) monitoring, we administered a standardized prospective testing battery including responses to questions and commands, as well as tests for reaching/grasping a ball and visual tracking in 27 CPS (in 14 patients) and 7 GTCS (in six patients). Behavioral results were analyzed in the ictal and postictal periods based on video review. During both CPS and GTCS, patients were unable to respond to questions or commands. However, during CPS, patients often retained minimally conscious ball grasping and visual tracking responses. Patients were able to successfully grasp a ball in 60% or to visually track in 58% of CPS, and could carry out both activities in 52% of CPS. In contrast, during GTCS, preserved ball grasp (10%), visual tracking (11%), or both (7%), were all significantly less than in CPS. Postictal ball grasping and visual tracking were also somewhat better following CPS than GTCS. These findings suggest that impaired consciousness in CPS is more similar to minimally conscious state than to coma. Further work may elucidate the specific brain networks underlying relatively spared functions in CPS, ultimately leading to improved treatments aimed at preventing impaired consciousness.

PURPOSE/OBJECTIVE:Impaired consciousness in epileptic seizures has a major negative impact on patient quality of life. Prior work on epileptic unconsciousness has mainly used retrospective and nonstandardized methods. Our goal was to validate and to obtain initial data using a standardized prospective testing battery. METHODS:The responsiveness in epilepsy scale (RES) was used on 52 patients during continuous video-electroencephalography (EEG) monitoring. RES begins with higher-level questions and commands, and switches adaptively to more basic sensorimotor responses depending on patient performance. RES continues after seizures and includes postictal memory testing. Scoring was conducted based on video review. KEY FINDINGS/RESULTS:Testing on standardized seizure simulations yielded good intrarater and interrater reliability. We captured 59 seizures from 18 patients (35% of participants) during 1,420 h of RES monitoring. RES impairment was greatest during and after tonic-clonic seizures, less in partial seizures, and minimal in auras and subclinical seizures. In partial seizures, ictal RES impairment was significantly greater if EEG changes were present. Maximum RES impairment (lowest ictal score) was also significantly correlated with long postictal recovery time, and poor postictal memory. SIGNIFICANCE/CONCLUSIONS:We found that prospective testing of responsiveness during seizures is feasible and reliable. RES impairment was related to EEG changes during seizures, as well as to postictal memory deficits and recovery time. With a larger patient sample it is hoped that this approach can identify brain networks underlying specific components of impaired consciousness in seizures. This may allow the development of improved treatments targeted at preventing dysfunction in these networks.

Childhood absence epilepsy (CAE) typically starts between four and seven years of age. Onset before three years is rare and has not been previously reported from North America. We retrospectively reviewed the electroencephalography laboratory database and paediatric neurology clinic records (from January 2000 to June 2009) at our institution in order to identify patients with absence seizures beginning before age three. Information was collected for age, gender, neurodevelopment, antiepileptic drugs (AEDs) used, seizure control, follow-up, and side effects. Of 12 patients identified, mean age at onset was 20.5 months (range: 11 months to two years; follow-up: six months to 11 years). Seven of 12 patients had normal neurodevelopment and five had speech delay. Four patients were seizure-free without AEDs, three were seizure-free with a single AED, and five still had seizures with multiple AEDs. Three patients had recurrences after medication withdrawal. Other previously published series have identified better seizure control than that reported here, however, 16% of the 130 patients so far documented are reported to have poorly controlled epilepsy, indicating that early-onset CAE is not a homogeneous condition. The debate as to whether early-onset CAE is a distinct epilepsy syndrome therefore continues. We believe that early-onset CAE may be a distinct epilepsy syndrome, with some features that overlap with those of typical CAE, as well as unique distinguishing features. Large prospective multicentric studies would be necessary to definitely resolve this matter.