Precision treatments for epilepsy targeting the underlying genetic diagnoses are becoming a reality. Historically, the goal of epilepsy treatments was to reduce seizure frequency. In the era of precision medicine, however, outcomes such as prevention of epilepsy progression or even improvements in cognitive functions are both aspirational targets for any intervention. Developing methods, both in clinical trial design and in novel endpoints, will be necessary for measuring, not only seizures, but also the other neurodevelopmental outcomes that are predicted to be targeted by precision treatments. Biomarkers that quantitatively measure disease progression or network level changes are needed to allow for unbiased measurements of the effects of any gene-level treatments. Here, we discuss some of the promising electrophysiological biomarkers that may be of use in clinical trials of precision therapies, as well as the difficulties in implementing them.

Temporal lobe epilepsy is the most common type of epilepsy in adults, is often medically refractory, and due to broad actions and long-time scales, current systemic treatments have major negative side-effects. However, temporal lobe seizures tend to arise from discrete regions before overt clinical behaviour, making temporally and spatially specific treatment theoretically possible. Here we report the arrest of spontaneous seizures using a real-time, closed-loop, response system and in vivo optogenetics in a mouse model of temporal lobe epilepsy. Either optogenetic inhibition of excitatory principal cells, or activation of a subpopulation of GABAergic cells representing <5% of hippocampal neurons, stops seizures rapidly upon light application. These results demonstrate that spontaneous temporal lobe seizures can be detected and terminated by modulating specific cell populations in a spatially restricted manner. A clinical approach built on these principles may overcome many of the side-effects of currently available treatment options.

Stereoelectroencephalography (SEEG) is an increasingly popular invasive monitoring approach to epilepsy surgery in patients with drug-resistant epilepsies. The technique allows a three-dimensional definition of the epileptogenic zones (EZ) in the brain. It has been shown to be safe and effective in adults and older children but has been used sparingly in children less than two years old due to concerns about pin fixation in thin bone, registration accuracy, and bolt security. As such, most current series of pediatric invasive EEG explorations do not include young participants, and, when they do, SEEG is often not utilized for these patients. Recent national survey data further suggests SEEG is infrequently utilized in very young patients. We present a novel case of SEEG used to localize the EZ in a 17-month-old patient with thin cranial bone, an open fontanelle, and severe drug-resistant epilepsy due to tuberous sclerosis complex (TSC), with excellent accuracy, surgical results, and seizure remission.

UNLABELLED: Neural dynamics preceding seizures are of interest because they may shed light on mechanisms of seizure generation and could be predictive. In healthy animals, hippocampal network activity is shaped by behavioral brain state and, in epilepsy, seizures selectively emerge during specific brain states. To determine the degree to which changes in network dynamics before seizure are pathological or reflect ongoing fluctuations in brain state, dorsal hippocampal neurons were recorded during spontaneous seizures in a rat model of temporal lobe epilepsy. Seizures emerged from all brain states, but with a greater likelihood after REM sleep, potentially due to an observed increase in baseline excitability during periods of REM compared with other brains states also characterized by sustained theta oscillations. When comparing the firing patterns of the same neurons across brain states associated with and without seizures, activity dynamics before seizures followed patterns typical of the ongoing brain state, or brain state transitions, and did not differ until the onset of the electrographic seizure. Next, we tested whether disparate activity patterns during distinct brain states would influence the effectiveness of optogenetic curtailment of hippocampal seizures in a mouse model of temporal lobe epilepsy. Optogenetic curtailment was significantly more effective for seizures preceded by non-theta states compared with seizures that emerged from theta states. Our results indicate that consideration of behavioral brain state preceding a seizure is important for the appropriate interpretation of network dynamics leading up to a seizure and for designing effective seizure intervention. SIGNIFICANCE STATEMENT: Hippocampal single-unit activity is strongly shaped by behavioral brain state, yet this relationship has been largely ignored when studying activity dynamics before spontaneous seizures in medial temporal lobe epilepsy. In light of the increased attention on using single-unit activity for the prediction of seizure onset and closed-loop seizure intervention, we show a need for monitoring brain state to interpret correctly whether changes in neural activity before seizure onset is pathological or normal. Moreover, we also find that the brain state preceding a seizure determines the success of therapeutic interventions to curtail seizure duration. Together, these findings suggest that seizure prediction and intervention will be more successful if tailored for the specific brain states from which seizures emerge.

Temporal lobe epilepsy is often medically refractory and new targets for intervention are needed. We used a mouse model of temporal lobe epilepsy, on-line seizure detection, and responsive optogenetic intervention to investigate the potential for cerebellar control of spontaneous temporal lobe seizures. Cerebellar targeted intervention inhibited spontaneous temporal lobe seizures during the chronic phase of the disorder. We further report that the direction of modulation as well as the location of intervention within the cerebellum can affect the outcome of intervention. Specifically, on-demand optogenetic excitation or inhibition of parvalbumin-expressing neurons, including Purkinje cells, in the lateral or midline cerebellum results in a decrease in seizure duration. In contrast, a consistent reduction in spontaneous seizure frequency occurs uniquely with on-demand optogenetic excitation of the midline cerebellum, and was not seen with intervention directly targeting the hippocampal formation. These findings demonstrate that the cerebellum is a powerful modulator of temporal lobe epilepsy, and that intervention targeting the cerebellum as a potential therapy for epilepsy should be revisited.

The medial entorhinal cortex layer II (MEClayerII ) is a brain region critical for spatial navigation and memory, and it also demonstrates a number of changes in patients with, and animal models of, temporal lobe epilepsy (TLE). Prior studies of GABAergic microcircuitry in MEClayerII revealed that cholecystokinin-containing basket cells (CCKBCs) select their targets on the basis of the long-range projection pattern of the postsynaptic principal cell. Specifically, CCKBCs largely avoid reelin-containing principal cells that form the perforant path to the ipsilateral dentate gyrus and preferentially innervate non-perforant path forming calbindin-containing principal cells. We investigated whether parvalbumin containing basket cells (PVBCs), the other major perisomatic targeting GABAergic cell population, demonstrate similar postsynaptic target selectivity as well. In addition, we tested the hypothesis that the functional or anatomic arrangement of circuit selectivity is disrupted in MEClayerII in chronic TLE, using the repeated low-dose kainate model in rats. In control animals, we found that PVBCs innervated both principal cell populations, but also had significant selectivity for calbindin-containing principal cells in MEClayerII . However, the magnitude of this preference was smaller than for CCKBCs. In addition, axonal tracing and paired recordings showed that individual PVBCs were capable of contacting both calbindin and reelin-containing principal cells. In chronically epileptic animals, we found that the intrinsic properties of the two principal cell populations, the GABAergic perisomatic bouton numbers, and selectivity of the CCKBCs and PVBCs remained remarkably constant in MEClayerII . However, miniature IPSC frequency was decreased in epilepsy, and paired recordings revealed the presence of direct excitatory connections between principal cells in the MEClayerII in epilepsy, which is unusual in normal adult MEClayerII . Taken together, these findings advance our knowledge about the organization of perisomatic inhibition both in control and in epileptic animals. © 2015 Wiley Periodicals, Inc.

OBJECTIVE: Measuring cortico-cortical evoked potentials (CCEPs) is a promising tool for mapping epileptic networks, but it is not known how variability in brain state and stimulation technique might impact the use of CCEPs for epilepsy localization. We test the hypotheses that (1) CCEPs demonstrate systematic variability across trials and (2) CCEP amplitudes depend on the timing of stimulation with respect to endogenous, low-frequency oscillations. METHODS: We studied 11 patients who underwent CCEP mapping after stereo-electroencephalography electrode implantation for surgical evaluation of drug-resistant epilepsy. Evoked potentials were measured from all electrodes after each pulse of a 30 s, 1 Hz bipolar stimulation train. We quantified monotonic trends, phase dependence, and standard deviation (SD) of N1 (15-50 ms post-stimulation) and N2 (50-300 ms post-stimulation) amplitudes across the 30 stimulation trials for each patient. We used linear regression to quantify the relationship between measures of CCEP variability and the clinical seizure-onset zone (SOZ) or interictal spike rates. RESULTS: We found that N1 and N2 waveforms exhibited both positive and negative monotonic trends in amplitude across trials. SOZ electrodes and electrodes with high interictal spike rates had lower N1 and N2 amplitudes with higher SD across trials. Monotonic trends of N1 and N2 amplitude were more positive when stimulating from an area with higher interictal spike rate. We also found intermittent synchronization of trial-level N1 amplitude with low-frequency phase in the hippocampus, which did not localize the SOZ. SIGNIFICANCE: These findings suggest that standard approaches for CCEP mapping, which involve computing a trial-averaged response over a .2-1 Hz stimulation train, may be masking inter-trial variability that localizes to epileptogenic tissue. We also found that CCEP N1 amplitudes synchronize with ongoing low-frequency oscillations in the hippocampus. Further targeted experiments are needed to determine whether phase-locked stimulation could have a role in localizing epileptogenic tissue.

Epilepsy is a highly heterogeneous neurological disorder with variable etiology, manifestation, and response to treatment. It is imperative that new models of epileptiform brain activity account for this variability, to identify individual needs and allow clinicians to curate personalized care. Here, we use a hidden Markov model (HMM) to create a unique statistical model of interictal brain activity for 10 pediatric patients. We use magnetoencephalography (MEG) data acquired as part of standard clinical care for patients at the Childrens Hospital of Philadelphia. These data are routinely analyzed using excess kurtosis mapping (EKM); however, as cases become more complex (extreme multifocal and/or polymorphic activity), they become harder to interpret with EKM. We assessed the performance of the HMM against EKM for three patient groups, with increasingly complicated presentation. The difference in localization of epileptogenic foci for the two methods was 7 ± 2 mm (mean ± SD over all 10 patients); and 94% ± 13% of EKM temporal markers were matched by an HMM state visit. The HMM localizes epileptogenic areas (in agreement with EKM) and provides additional information about the relationship between those areas. A key advantage over current methods is that the HMM is a data-driven model, so the output is tuned to each individual. Finally, the model output is intuitive, allowing a user (clinician) to review the result and manually select the HMM epileptiform state, offering multiple advantages over previous methods and allowing for broader implementation of MEG epileptiform analysis in surgical decision-making for patients with intractable epilepsy.