Toward a Mechanistic Understanding of Epileptic Networks

Distinct Features of Interictal Activity Predict Seizure Localization and Burden in a Mouse Model of Childhood Epilepsy

The epileptic brain is distinguished by spontaneous seizures and interictal epileptiform discharges (IEDs). Basic patterns of mesoscale brain activity outside of seizures and IEDs are also frequently disrupted in the epileptic brain and likely influence disease symptoms, but are poorly understood. We aimed to quantify how interictal brain activity differs from that in healthy individuals, and identify what features of interictal activity influence seizure occurrence in a genetic mouse model of childhood epilepsy. Neural activity across the majority of the dorsal cortex was monitored with widefield Ca2+ imaging in mice of both sexes expressing a human Kcnt1 variant (Kcnt1m/m ) and wild-type controls (WT). Ca2+ signals during seizures and interictal periods were classified according to their spatiotemporal features. We identified 52 spontaneous seizures, which emerged and propagated within a consistent set of susceptible cortical areas, and were predicted by a concentration of total cortical activity within the emergence zone. Outside of seizures and IEDs, similar events were detected in Kcnt1m/m and WT mice, suggesting that the spatial structure of interictal activity is similar. However, the rate of events whose spatial profile overlapped with where seizures and IEDs emerged was increased, and the characteristic global intensity of cortical activity in individual Kcnt1m/m mice predicted their epileptic activity burden. This suggests that cortical areas with excessive interictal activity are vulnerable to seizures, but epilepsy is not an inevitable outcome. Global scaling of the intensity of cortical activity below levels found in the healthy brain may provide a natural mechanism of seizure protection.SIGNIFICANCE STATEMENT Defining the scope and structure of an epilepsy-causing gene variant's effects on mesoscale brain activity constitutes a major contribution to our understanding of how epileptic brains differ from healthy brains, and informs the development of precision epilepsy therapies. We provide a clear roadmap for measuring how severely brain activity deviates from normal, not only in pathologically active areas, but across large portions of the brain and outside of epileptic activity. This will indicate where and how activity needs to be modulated to holistically restore normal function. It also has the potential to reveal unintended off-target treatment effects and facilitate therapy optimization to deliver maximal benefit with minimal side-effect potential.

Seizure onset patterns predict outcome after stereo-electroencephalography-guided laser amygdalohippocampotomy

OBJECTIVE

Stereotactic laser amygdalohippocampotomy (SLAH) is an appealing option for patients with temporal lobe epilepsy, who often require intracranial monitoring to confirm mesial temporal seizure onset. However, given limited spatial sampling, it is possible that stereotactic electroencephalography (stereo-EEG) may miss seizure onset elsewhere. We hypothesized that stereo-EEG seizure onset patterns (SOPs) may differentiate between primary onset and secondary spread and predict postoperative seizure control. In this study, we characterized the 2-year outcomes of patients who underwent single-fiber SLAH after stereo-EEG and evaluated whether stereo-EEG SOPs predict postoperative seizure freedom.

METHODS

This retrospective five-center study included patients with or without mesial temporal sclerosis (MTS) who underwent stereo-EEG followed by single-fiber SLAH between August 2014 and January 2022. Patients with causative hippocampal lesions apart from MTS or for whom the SLAH was considered palliative were excluded. An SOP catalogue was developed based on literature review. The dominant pattern for each patient was used for survival analysis. The primary outcome was 2-year Engel I classification or recurrent seizures before then, stratified by SOP category.

RESULTS

Fifty-eight patients were included, with a mean follow-up duration of 39 ± 12 months after SLAH. Overall 1-, 2-, and 3-year Engel I seizure freedom probability was 54%, 36%, and 33%, respectively. Patients with SOPs, including low-voltage fast activity or low-frequency repetitive spiking, had a 46% 2-year seizure freedom probability, compared to 0% for patients with alpha or theta frequency repetitive spiking or theta or delta frequency rhythmic slowing (log-rank test, p = .00015).

SIGNIFICANCE

Patients who underwent SLAH after stereo-EEG had a low probability of seizure freedom at 2 years, but SOPs successfully predicted seizure recurrence in a subset of patients. This study provides proof of concept that SOPs distinguish between hippocampal seizure onset and spread and supports using SOPs to improve selection of SLAH candidates.

Neural Circuit Changes in Neurological Disorders: Evidence from in vivo Two-photon Imaging

Neural circuits, such as synaptic plasticity and neural activity, are critical components of healthy brain function. The consequent dynamic remodeling of neural circuits is an ongoing procedure affecting neuronal activities. Disruption of this essential process results in diseases. Advanced microscopic applications such as two-photon laser scanning microscopy have recently been applied to understand neural circuit changes during disease since it can visualize fine structural and functional cellular activation in living animals. In this review, we have summarized the latest work assessing the dynamic rewiring of postsynaptic dendritic spines and modulation of calcium transients in neurons of the intact living brain, focusing on their potential roles in neurological disorders (e.g. Alzheimer's disease, stroke, and epilepsy). Understanding the fine changes that occurred in the brain during disease is crucial for future clinical intervention developments.

Predictors of seizure outcomes in patients with diffuse low-grade glioma-related epilepsy after complete glioma removal

AIMS

We aimed to identify predictors of postoperative seizures in patients with diffuse low-grade glioma (DLGG)-related epilepsy after complete tumor resection in this study.

METHODS

We retrospectively collected data from individuals with DLGG-related epilepsy whose tumors were completely resected at Xiangya Hospital, Central South University between January 2014 and January 2020. The predictors of seizure outcomes were assessed by employing univariate analysis and a multivariate logistic regression model in a backward binary logistic regression model.

RESULTS

Among the 118 cases that met the inclusion criteria, 83.05% were seizure-free following an average follow-up of 4.27 ± 1.65 years, all of whom were classified as International League Against Epilepsy class I outcome. Univariate and multivariate analyses indicated that seizure duration of >6 years (odds ratio [OR], 6.62; 95% confidence interval [CI], 1.76-24.98; p = 0.005) and first clinical symptoms other than seizures (OR, 4.51; 95% CI, 1.43-14.23; p = 1.010) were both independent predictors of unfavorable seizure outcomes.

CONCLUSION

Our results imply that satisfactory seizure outcomes can be achieved in most patients with DLGG-related epilepsy after complete tumor resection. Patients with seizure duration of >6 years or first clinical symptoms other than seizures were more likely to experience postoperative seizure recurrence.

Abnormal brain functional network dynamics in sleep-related hypermotor epilepsy

AIMS

This study aimed to use resting-state functional magnetic resonance imaging (rs-fMRI) to determine the temporal features of functional connectivity states and changes in connectivity strength in sleep-related hypermotor epilepsy (SHE).

METHODS

High-resolution T1 and rs-fMRI scanning were performed on all the subjects. We used a sliding-window approach to construct a dynamic functional connectivity (dFC) network. The k-means clustering method was performed to analyze specific FC states and related temporal properties. Finally, the connectivity strength between the components was analyzed using network-based statistics (NBS) analysis. The correlations between the abovementioned measures and disease duration were analyzed.

RESULTS

After k-means clustering, the SHE patients mainly exhibited two dFC states. The frequency of state 1 was higher, which was characterized by stronger connections within the networks; state 2 occurred at a relatively low frequency, characterized by stronger connections between networks. SHE patients had greater fractional time and a mean dwell time in state 2 and had a larger number of state transitions. The NBS results showed that SHE patients had increased connectivity strength between networks. None of the properties was correlated with illness duration among patients with SHE.

CONCLUSION

The patterns of dFC patterns may represent an adaptive and protective mode of the brain to deal with epileptic seizures.

Interictal Connectivity Revealed by Granger Analysis of Stereoelectroencephalography: Association With Ictal Onset Zone, Resection, and Outcome

BACKGROUND

Stereoelectroencephalography (sEEG) facilitates electrical sampling and evaluation of complex deep-seated, dispersed, and multifocal locations. Granger causality (GC), previously used to study seizure networks using interictal data from subdural grids, may help identify the seizure-onset zone from interictal sEEG recordings.

OBJECTIVE

To examine whether statistical analysis of interictal sEEG helps identify surgical target sites and whether surgical resection of highly ranked nodes correspond to favorable outcomes.

METHODS

Ten minutes of extraoperative recordings from sequential patients who underwent sEEG evaluation were analyzed (n = 20). GC maps were compared with clinically defined surgical targets using rank order statistics. Outcomes of patients with focal resection/ablation with median follow-up of 3.6 years were classified as favorable (Engel 1, 2) or poor (Engel 3, 4) to assess their relationship with the removal of highly ranked nodes using the Wilcoxon rank-sum test.

RESULTS

In 12 of 20 cases, the rankings of contacts (based on the sum of outward connection weights) mapped to the seizure-onset zone showed higher causal node connectivity than predicted by chance ( P ≤ .02). A very low aggregate probability ( P < 10 -18 , n = 20) suggests that causal node connectivity predicts seizure networks. In 8 of 16 with outcome data, causal connectivity in the resection was significantly greater than in the remaining contacts ( P ≤ .05). We found a significant association between favorable outcome and the presence of highly ranked nodes in the resection ( P < .05).

CONCLUSION

Granger analysis can identify seizure foci from interictal sEEG and correlates highly ranked nodes with favorable outcome, potentially informing surgical decision-making without reliance on ictal recordings.

Graph theoretical measures of fast ripples support the epileptic network hypothesis

The epileptic network hypothesis and epileptogenic zone hypothesis are two theories of ictogenesis. The network hypothesis posits that coordinated activity among interconnected nodes produces seizures. The epileptogenic zone hypothesis posits that distinct regions are necessary and sufficient for seizure generation. High-frequency oscillations, and particularly fast ripples, are thought to be biomarkers of the epileptogenic zone. We sought to test these theories by comparing high-frequency oscillation rates and networks in surgical responders and non-responders, with no appreciable change in seizure frequency or severity, within a retrospective cohort of 48 patients implanted with stereo-EEG electrodes. We recorded inter-ictal activity during non-rapid eye movement sleep and semi-automatically detected and quantified high-frequency oscillations. Each electrode contact was localized in normalized coordinates. We found that the accuracy of seizure onset zone electrode contact classification using high-frequency oscillation rates was not significantly different in surgical responders and non-responders, suggesting that in non-responders the epileptogenic zone partially encompassed the seizure onset zone(s) (P > 0.05). We also found that in the responders, fast ripple on oscillations exhibited a higher spectral content in the seizure onset zone compared with the non-seizure onset zone (P < 1 × 10⁻⁵). By contrast, in the non-responders, fast ripple had a lower spectral content in the seizure onset zone (P < 1 × 10⁻⁵). We constructed two different networks of fast ripple with a spectral content >350 Hz. The first was a rate–distance network that multiplied the Euclidian distance between fast ripple-generating contacts by the average rate of fast ripple in the two contacts. The radius of the rate–distance network, which excluded seizure onset zone nodes, discriminated non-responders, including patients not offered resection or responsive neurostimulation due to diffuse multifocal onsets, with an accuracy of 0.77 [95% confidence interval (CI) 0.56–0.98]. The second fast ripple network was constructed using the mutual information between the timing of the events to measure functional connectivity. For most non-responders, this network had a longer characteristic path length, lower mean local efficiency in the non-seizure onset zone, and a higher nodal strength among non-seizure onset zone nodes relative to seizure onset zone nodes. The graphical theoretical measures from the rate–distance and mutual information networks of 22 non- responsive neurostimulation treated patients was used to train a support vector machine, which when tested on 13 distinct patients classified non-responders with an accuracy of 0.92 (95% CI 0.75–1). These results indicate patients who do not respond to surgery or those not selected for resection or responsive neurostimulation can be explained by the epileptic network hypothesis that is a decentralized network consisting of widely distributed, hyperexcitable fast ripple-generating nodes.

Diffusion tractography predicts propagated high-frequency activity during epileptic spasms

OBJECTIVE

Determine the structural networks that constrain propagation of ictal oscillations during epileptic spasm events, and compare observed propagation patterns across patients with successful or unsuccessful surgical outcomes.

METHODS

Subdural electrode recordings of 18 young patients (age 1-11 years) were analyzed during epileptic spasm events to determine ictal networks and quantify the amplitude and onset time of ictal oscillations across the cortical surface. Corresponding structural networks were generated with diffusion MRI tractography by seeding the cortical region associated with the earliest average oscillation onset time, and white matter pathways connecting active electrode regions within the ictal network were isolated. Properties of this structural network were used to predict oscillation onset times and amplitudes, and this relationship was compared across patients who did and did not achieve seizure freedom following resective surgery.

RESULTS

Onset propagation patterns were relatively consistent across each patients' spasm events. An electrode's average ictal oscillation onset latency was most significantly associated with the length of direct corticocortical tracts connecting to the area with the earliest average oscillation onset (p < .001, model R²  = 0.54). Moreover, patients demonstrating a faster propagation of ictal oscillation signals within the corticocortical network were more likely to have seizure recurrence following resective surgery (p = .039). Ictal oscillation amplitude was also associated with connecting tractography length and weighted fractional anisotropy (FA) measures along these pathways (p = .002/.030, model R²  = 0.31/0.25). Characteristics of analogous corticothalamic pathways did not show significant associations with ictal oscillation onset latency or amplitude.

SIGNIFICANCE

Spatiotemporal propagation patterns of high-frequency activity in epileptic spasms align with length and FA measures from onset-originating corticocortical pathways. Considering data in this individualized framework may help inform surgical decision making and expectations of surgical outcomes.

Epidemic models characterize seizure propagation and the effects of epilepsy surgery in individualized brain networks based on MEG and invasive EEG recordings

Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients. However, seizure-freedom is currently achieved in only 2/3 of the patients after surgery. In this study we have developed an individualized computational model based on MEG brain networks to explore seizure propagation and the efficacy of different virtual resections. Eventually, the goal is to obtain individualized models to optimize resection strategy and outcome. We have modelled seizure propagation as an epidemic process using the susceptible-infected (SI) model on individual brain networks derived from presurgical MEG. We included 10 patients who had received epilepsy surgery and for whom the surgery outcome at least one year after surgery was known. The model parameters were tuned in in order to reproduce the patient-specific seizure propagation patterns as recorded with invasive EEG. We defined a personalized search algorithm that combined structural and dynamical information to find resections that maximally decreased seizure propagation for a given resection size. The optimal resection for each patient was defined as the smallest resection leading to at least a 90% reduction in seizure propagation. The individualized model reproduced the basic aspects of seizure propagation for 9 out of 10 patients when using the resection area as the origin of epidemic spreading, and for 10 out of 10 patients with an alternative definition of the seed region. We found that, for 7 patients, the optimal resection was smaller than the resection area, and for 4 patients we also found that a resection smaller than the resection area could lead to a 100% decrease in propagation. Moreover, for two cases these alternative resections included nodes outside the resection area. Epidemic spreading models fitted with patient specific data can capture the fundamental aspects of clinically observed seizure propagation, and can be used to test virtual resections in silico. Combined with optimization algorithms, smaller or alternative resection strategies, that are individually targeted for each patient, can be determined with the ultimate goal to improve surgery outcome. MEG-based networks can provide a good approximation of structural connectivity for computational models of seizure propagation, and facilitate their clinical use.

Visualizing Oscillations in Brain Slices With Genetically Encoded Voltage Indicators

Genetically encoded voltage indicators (GEVIs) expressed pan-neuronally were able to optically resolve bicuculline induced spontaneous oscillations in brain slices of the mouse motor cortex. Three GEVIs were used that differ in their timing of response to voltage transients as well as in their voltage ranges. The duration, number of cycles, and frequency of the recorded oscillations reflected the characteristics of each GEVI used. Multiple oscillations imaged in the same slice never originated at the same location, indicating the lack of a “hot spot” for induction of the voltage changes. Comparison of pan-neuronal, Ca²⁺/calmodulin-dependent protein kinase II α restricted, and parvalbumin restricted GEVI expression revealed distinct profiles for the excitatory and inhibitory cells in the spontaneous oscillations of the motor cortex. Resolving voltage fluctuations across space, time, and cell types with GEVIs represent a powerful approach to dissecting neuronal circuit activity.

Altered topological properties of brain functional networks in drug-resistant epilepsy patients with vagus nerve stimulators

PURPOSE

To explore abnormalities of topological properties in drug-resistant epilepsy (DRE) patients after vagus nerve stimulation (VNS) by analyzing brain functional networks using graph theory.

METHODS

Fifteen patients and eight healthy controls (HC) were scanned separately with resting-state functional magnetic resonance imaging (rs-fMRI). Graph theoretical analyses were chosen to compare the global (small-world parameters [γ, λ, σ, Cp, and Lp], and network efficiency [Eg and Eloc]), and nodal (BC, DC, and NE) properties in preoperative patients (EPpre), postoperative patients (EPpost) and HC.

RESULTS

HC, EPpre and EPpost all satisfied the criteria for small-world properties (σ > 1) within the sparsity range of 0.05-0.5. Compared with EPpre, EPpost performed higher in λ and Eloc but lower in γ, σ, and Cp. Compared with HC, EPpre exhibited decreased BC, DC or NE in the right inferior frontal gyrus, right superior temporal gyrus, bilateral cingulate gyri, right supplementary motor area, right superior occipital gyrus, right Heschl gyrus, and left calcarine fissure; increased BC in the left postcentral/precentral gyrus, right paracentral lobule, left rolandic operculum, and left supramarginal gyrus, and increased NE in the right caudate nucleus. Compared with EPpre, EPpost showed increased BC, DC or NE in the bilateral inferior frontal gyrus, right middle frontal gyrus, bilateral cingulate gyri, right superior temporal gyrus, and right Heschl gyrus and decreased BC in the left fusiform gyrus.

CONCLUSION

VNS downregulated small-world properties in DRE, and caused changes in some key nodes to reorganize the transmission ability of the large-scale network.

Spatiotemporal evolution of epileptic seizure based on mutual information and dynamic brain network

BACKGROUND

Epilepsy was defined as an abnormal brain network model disease in the latest definition. From a microscopic perspective, it is also particularly important to observe the Mutual Information (MI) of the whole brain network based on different lead positions.

METHODS

In this study, we selected EEG data from representative temporal lobe and frontal lobe epilepsy patients. Based on Phase Space Reconstruction and the calculation of MI indicator, we used Complex Network technology to construct a dynamic brain network function model of epilepsy seizure. At the same time, about the analysis of our network, we described the index changes and propagation paths of epilepsy discharge in different periods, and spatially monitors the seizure change process based on the analysis of the parameter characteristics of the complex network.

RESULTS

Our model portrayed the functional synergy between the various regions of the brain and the state transition during the seizure process. We also characterized the EEG synchronous propagation path and core nodes during seizures. The results shown the full node change path and the distribution of important indicators during the seizure process, which makes the state change of the seizure process more clearly.

CONCLUSION

In this study, we have demonstrated that synchronization-based brain networks change with time and space. The EEG synchronous propagation path and core nodes during epileptic seizures can provide a reference for finding the focus area.

Current Pharmacologic Strategies for Treatment of Intractable Epilepsy in Children

Epileptic encephalopathy (EE) is a devastating pediatric disease that features medically resistant seizures, which can contribute to global developmental delays. Despite technological advancements in genetics, the neurobiological mechanisms of EEs are not fully understood, leaving few therapeutic options for affected patients. In this review, we introduce the most common EEs in pediatrics (i.e., Ohtahara syndrome, Dravet syndrome, and Lennox-Gastaut syndrome) and their molecular mechanisms that cause excitation/inhibition imbalances. We then discuss some of the essential molecules that are frequently dysregulated in EEs. Specifically, we explore voltage-gated ion channels, synaptic transmission-related proteins, and ligand-gated ion channels in association with the pathophysiology of Ohtahara syndrome, Dravet syndrome, and Lennox-Gastaut syndrome. Finally, we review currently available antiepileptic drugs used to treat seizures in patients with EEs. Since these patients often fail to achieve seizure relief even with the combination therapy, further extensive research efforts to explore the involved molecular mechanisms will be required to develop new drugs for patients with intractable epilepsy.

Clinical characteristics of low-grade tumor-related epilepsy and its predictors for surgical outcome

Objectives

Low‐grade tumors are the most common neoplasms inducing focal epilepsy; however, the short‐ and medium‐term efficacy of surgery in epilepsy patients with low‐grade tumors remains underappreciated. This study aims to summarize the clinical characteristics of epilepsy patients with low‐grade tumors and to identify factors associated with postsurgical seizure‐free outcomes.

Methods

We retrospectively reviewed consecutive patients with low‐grade tumors who underwent subsequent epilepsy surgery in our epilepsy center, between 2012 and 2018 with a minimum follow‐up of 1 year. Using Engel’s classification and Kaplan–Meier survival analysis, we assessed postoperative seizure freedom over time. Demographical, electroclinical, and other presurgical evaluations were then evaluated for association with postoperative seizure outcome.

Results

The cohort included a total of 132 patients: 79 males and 53 females. Among them, 110 (83.33%) were seizure‐free through their last follow‐up. The Engel class I outcomes were 90.15%, 87.76%, 85.53%, 82.46%, and 73.17% at the end of the 1st, 2nd, 3rd, 4th, and 5th postoperative years, respectively. Multivariate logistic analysis revealed that longer epilepsy duration (p < 0.001, OR 1.091, 95% CI 1.040–1.144) and incomplete resection (p = 0.009, OR 3.673, 95% CI 1.393–9.684) were independently associated with seizure recurrence through the last follow‐up.

Conclusions

Surgical treatment for seizure control in patients with low‐grade tumors provides excellent short‐ and median‐term outcomes.

Characterizing the seizure onset zone and epileptic network using EEG-fMRI in a rat seizure model

Accurate epileptogenic zone (EZ) or seizure onset zone (SOZ) localization is crucial for epilepsy surgery optimization. Previous animal and human studies on epilepsy have reported that changes in blood oxygen level-dependent (BOLD) signals induced by epileptic events could be used as diagnostic markers for EZ or SOZ localization. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) recording is gaining interest as a non-invasive tool for preoperative epilepsy evaluation. However, EEG-fMRI studies have reported inconsistent and ambiguous findings. Therefore, it remains unclear whether BOLD responses can be used for accurate EZ or SOZ localization. In this study, we used simultaneous EEG-fMRI recording in a rat model of 4-aminopyridine-induced acute focal seizures to assess the spatial concordance between individual BOLD responses and the SOZ. This was to determine the optimal use of simultaneous EEG-fMRI recording in the SOZ localization. We observed a high spatial consistency between BOLD responses and the SOZ. Further, dynamic BOLD responses were consistent with the regions where the seizures were propagated. These results suggested that simultaneous EEG-fMRI recording could be used as a noninvasive clinical diagnostic technique for localizing the EZ or SOZ and could be an effective tool for mapping epileptic networks.

Rapidly spreading seizures arise from large-scale functional brain networks in focal epilepsy

It remains unclear whether epileptogenic networks in focal epilepsy develop on physiological networks. This work aimed to explore the association between the rapid spread of ictal fast activity (IFA), a proposed biomarker for epileptogenic networks, and the functional connectivity or networks of healthy subjects. We reviewed 45 patients with focal epilepsy who underwent electrocorticographic (ECoG) recordings to identify the patients showing the rapid spread of IFA. IFA power was quantified as normalized beta-gamma band power. Using published resting-state functional magnetic resonance imaging databases, we estimated resting-state functional connectivity of healthy subjects (RSFC-HS) and resting-state networks of healthy subjects (RSNs-HS) at the locations corresponding to the patients' electrodes. We predicted the IFA power of each electrode based on RSFC-HS between electrode locations (RSFC-HS-based prediction) using a recently developed method, termed activity flow mapping. RSNs-HS were identified using seed-based and atlas-based methods. We compared IFA power with RSFC-HS-based prediction or RSNs-HS using non-parametric correlation coefficients. RSFC and seed-based RSNs of each patient (RSFC-PT and seed-based RSNs-PT) were also estimated using interictal ECoG data and compared with IFA power in the same way as RSFC-HS and seed-based RSNs-HS. Spatial autocorrelation-preserving randomization tests were performed for significance testing. Nine patients met the inclusion criteria. None of the patients had reflex seizures. Six patients showed pathological evidence of a structural etiology. In total, we analyzed 49 seizures (2-13 seizures per patient). We observed significant correlations between IFA power and RSFC-HS-based prediction, seed-based RSNs-HS, or atlas-based RSNs-HS in 28 (57.1%), 21 (42.9%), and 28 (57.1%) seizures, respectively. Thirty-two (65.3%) seizures showed a significant correlation with either seed-based or atlas-based RSNs-HS, but this ratio varied across patients: 27 (93.1%) of 29 seizures in six patients correlated with either of them. Among atlas-based RSNs-HS, correlated RSNs-HS with IFA power included the default mode, control, dorsal attention, somatomotor, and temporal-parietal networks. We could not obtain RSFC-PT and RSNs-PT in one patient due to frequent interictal epileptiform discharges. In the remaining eight patients, most of the seizures showed significant correlations between IFA power and RSFC-PT-based prediction or seed-based RSNs-PT. Our study provides evidence that the rapid spread of IFA in focal epilepsy can arise from physiological RSNs. This finding suggests an overlap between epileptogenic and functional networks, which may explain why functional networks in patients with focal epilepsy frequently disrupt.

Astroglial Glutamine Synthetase and the Pathogenesis of Mesial Temporal Lobe Epilepsy

The enzyme glutamine synthetase (GS), also referred to as glutamate ammonia ligase, is abundant in astrocytes and catalyzes the conversion of ammonia and glutamate to glutamine. Deficiency or dysfunction of astrocytic GS in discrete brain regions have been associated with several types of epilepsy, including medically-intractable mesial temporal lobe epilepsy (MTLE), neocortical epilepsies, and glioblastoma-associated epilepsy. Moreover, experimental inhibition or deletion of GS in the entorhinal-hippocampal territory of laboratory animals causes an MTLE-like syndrome characterized by spontaneous, recurrent hippocampal-onset seizures, loss of hippocampal neurons, and in some cases comorbid depressive-like features. The goal of this review is to summarize and discuss the possible roles of astroglial GS in the pathogenesis of epilepsy.

Mechanism of seizure-induced retrograde amnesia

Seizures cause retrograde amnesia, but underlying mechanisms are poorly understood. We tested whether seizure activated neuronal circuits overlap with spatial memory engram and whether seizures saturate LTP in engram cells. A seizure caused retrograde amnesia for spatial memory task. Spatial learning and a seizure caused cFos expression and synaptic plasticity overlapping set of neurons in the CA1 of the hippocampus. Recordings from learning-labeled CA1 pyramidal neurons showed potentiated synapses. Seizure-tagged neurons were also more excitable with larger rectifying excitatory postsynaptic currents than surrounding unlabeled neurons. These neurons had enlarged dendritic spines and saturated LTP. A seizure immediately after learning, reset the memory engram. Seizures cause retrograde amnesia through shared ensembles and mechanisms.

Spontaneous Activity of Neuronal Ensembles in Mouse Motor Cortex: Changes after GABAergic Blockade

The mouse motor cortex exhibits spontaneous activity in the form of temporal sequences of neuronal ensembles in vitro without the need of tissue stimulation. These neuronal ensembles are defined as groups of neurons with a strong correlation between its firing patterns, generating what appears to be a predetermined neural conduction mode that needs study. Each ensemble is commonly accompanied by one or more parvalbumin expressing neurons (PV+) or fast spiking interneurons. Many of these interneurons have functional connections between them, helping to form a circuit configuration similar to a small-world network. However, rich club metrics show that most connected neurons are neurons not expressing parvalbumin, mainly pyramidal neurons (PV-) suggesting feed-forward propagation through pyramidal cells. Ensembles with PV+ neurons are connected to these hubs. When ligand-gated fast GABAergic transmission is blocked, temporal sequences of ensembles collapse into a unique synchronous and recurrent ensemble, showing the need of inhibition for coding cortical spontaneous activity. This new ensemble has a duration and electrophysiological characteristics of brief recurrent interictal epileptiform discharges (IEDs) composed by the coactivity of both PV- and PV+ neurons, demonstrating that GABA transmission impedes its occurrence. Synchronous ensembles are clearly divided into two clusters one of them lasting longer and mainly composed by PV+ neurons. Because an ictal-like event was not recorded after several minutes of IEDs recording, it is inferred that an external stimulus and/or fast GABA transmission are necessary for its appearance, making this preparation ideal to study both the neuronal machinery to encode cortical spontaneous activity and its transformation into brief non-ictal epileptiform discharges.

A systematic exploration of parameters affecting evoked intracranial potentials in patients with epilepsy

BACKGROUND

Brain activity is constrained by and evolves over a network of structural and functional connections. Corticocortical evoked potentials (CCEPs) have been used to measure this connectivity and to discern brain areas involved in both brain function and disease. However, how varying stimulation parameters influences the measured CCEP across brain areas has not been well characterized.

OBJECTIVE

To better understand the factors that influence the amplitude of the CCEPs as well as evoked gamma-band power (70-150 Hz) resulting from single-pulse stimulation via cortical surface and depth electrodes.

METHODS

CCEPs from 4370 stimulation-response channel pairs were recorded across a range of stimulation parameters and brain regions in 11 patients undergoing long-term monitoring for epilepsy. A generalized mixed-effects model was used to model cortical response amplitudes from 5 to 100 ms post-stimulation.

RESULTS

Stimulation levels <5.5 mA generated variable CCEPs with low amplitude and reduced spatial spread. Stimulation at ≥5.5 mA yielded a reliable and maximal CCEP across stimulation-response pairs over all regions. These findings were similar when examining the evoked gamma-band power. The amplitude of both measures was inversely correlated with distance. CCEPs and evoked gamma power were largest when measured in the hippocampus compared with other areas. Larger CCEP size and evoked gamma power were measured within the seizure onset zone compared with outside this zone.

CONCLUSION

These results will help guide future stimulation protocols directed at quantifying network connectivity across cognitive and disease states.

Burst suppression uncovers rapid widespread alterations in network excitability caused by an acute seizure focus

Burst suppression is an electroencephalogram pattern of globally symmetric alternating high amplitude activity and isoelectricity that can be induced by general anaesthetics. There is scattered evidence that burst suppression may become spatially non-uniform in the setting of underlying pathology. Here, we induced burst suppression with isoflurane in rodents and then created a neocortical acute seizure focus with injection of 4-aminopyridine (4-AP) in somatosensory cortex. Burst suppression events were recorded before and after creation of the focus using bihemispheric wide-field calcium imaging and multielectrode arrays. We find that the seizure focus elicits a rapid alteration in triggering, initiation, and propagation of burst suppression events. Compared with the non-seizing brain, bursts are triggered from the thalamus, initiate in regions uniquely outside the epileptic focus, elicit marked increases of multiunit activity and propagate towards the seizure focus. These findings support the rapid, widespread impact of focal epilepsy on the extended brain network.

Repurposed molecules for antiepileptogenesis: Missing an opportunity to prevent epilepsy?

Prevention of epilepsy is a great unmet need. Acute central nervous system (CNS) insults such as traumatic brain injury (TBI), cerebrovascular accidents (CVA), and CNS infections account for 15%-20% of all epilepsy. Following TBI and CVA, there is a latency of days to years before epilepsy develops. This allows treatment to prevent or modify postinjury epilepsy. No such treatment exists. In animal models of acquired epilepsy, a number of medications in clinical use for diverse indications have been shown to have antiepileptogenic or disease-modifying effects, including medications with excellent side effect profiles. These include atorvastatin, ceftriaxone, losartan, isoflurane, N-acetylcysteine, and the antiseizure medications levetiracetam, brivaracetam, topiramate, gabapentin, pregabalin, vigabatrin, and eslicarbazepine acetate. In addition, there are preclinical antiepileptogenic data for anakinra, rapamycin, fingolimod, and erythropoietin, although these medications have potential for more serious side effects. However, except for vigabatrin, there have been almost no translation studies to prevent or modify epilepsy using these potentially "repurposable" medications. We may be missing an opportunity to develop preventive treatment for epilepsy by not evaluating these medications clinically. One reason for the lack of translation studies is that the preclinical data for most of these medications are disparate in terms of types of injury, models within different injury type, dosing, injury-treatment initiation latencies, treatment duration, and epilepsy outcome evaluation mode and duration. This makes it difficult to compare the relative strength of antiepileptogenic evidence across the molecules, and difficult to determine which drug(s) would be the best to evaluate clinically. Furthermore, most preclinical antiepileptogenic studies lack information needed for translation, such as dose-blood level relationship, brain target engagement, and dose-response, and many use treatment parameters that cannot be applied clinically, for example, treatment initiation before or at the time of injury and dosing higher than tolerated human equivalent dosing. Here, we review animal and human antiepileptogenic evidence for these medications. We highlight the gaps in our knowledge for each molecule that need to be filled in order to consider clinical translation, and we suggest a platform of preclinical antiepileptogenesis evaluation of potentially repurposable molecules or their combinations going forward.

Astrocytes and Glutamine Synthetase in Epileptogenesis

The cellular, molecular, and metabolic mechanisms that underlie the development of mesial temporal lobe epilepsy are incompletely understood. Here we review the role of astrocytes in epilepsy development (a.k.a. epileptogenesis), particularly astrocyte pathologies related to: aquaporin 4, the inwardly rectifying potassium channel Kir4.1, monocarboxylate transporters MCT1 and MCT2, excitatory amino acid transporters EAAT1 and EAAT2, and glutamine synthetase. We propose that inhibition, dysfunction or loss of astrocytic glutamine synthetase is an important causative factor for some epilepsies, particularly mesial temporal lobe epilepsy and glioblastoma-associated epilepsy. We postulate that the regulatory mechanisms of glutamine synthetase as well as the downstream effects of glutamine synthetase dysfunction, represent attractive, new targets for antiepileptogenic interventions. Currently, no antiepileptogenic therapies are available for human use. The discovery of such interventions is important as it will fundamentally change the way we approach epilepsy by preventing the disease from ever becoming manifest after an epileptogenic insult to the brain.

fMRI functional connectivity as an indicator of interictal epileptic discharges

•

Functional connectivity to successful EEG/fMRI response indicates higher IED rates.

•

The results hold when correcting for distance to maximum EEG-fMRI and laterality.

•

Intracranial IED rates correlate with functional connectivity to EEG/fMRI maxima.

•

Results suggest it is feasible to non-invasively infer the brain regions with IEDs.

Objective

To explore the relationship between functional connectivity and presence of interictal epileptic discharges (IEDs) in different brain regions in intracranial EEG (iEEG).

Methods

We studied 38 focal epilepsy patients who underwent simultaneous EEG/fMRI scanning and subsequent intracerebral stereo-EEG investigation. In EEG/fMRI analysis, IEDs with different spatial distributions were considered independent studies and IED-related maximal BOLD responses were evaluated. Studies with iEEG electrodes inside the maximal responses were selected and divided into three groups: Studies with 1. distinct maximal BOLD highly concordant with seizure-onset-zone (SOZ); 2. Moderate maximal BOLD concordant with SOZ; 3. maximal BOLD discordant with SOZ. Using maximal BOLD as seed, its functionally connected zone (FCZ) was determined. IED rates in iEEG channels inside and outside the FCZ were compared in the three groups. The effect of laterality and distance between channels and maximal BOLD, and correlation between functional connectivity values and IED rates were analyzed.

Results

Thirty-six studies in 25 patients were included. IED rates of intracranial EEG channels inside the FCZ were significantly higher than outside in Group 1 (p = 2.6×10−6) and Group 2 (p = 1.2×10−3) and the inside-outside difference remained after regressing distance and laterality factors. In Group 1, connectivity values were significantly correlated with IED rates in channels inside the FCZ (p < 0.05).

Significance

Our results indicate a higher probability of finding intracranial IEDs in the FCZ of SOZ-concordant maximal BOLD responses than in other regions, regardless of distance and laterality. In studies with distinct maximal BOLD, connectivity values can partially predict IED rates in intracranial EEG. It is thus feasible to non-invasively delineate brain regions that are likely to have high IED rates.

Background EEG Connectivity Captures the Time-Course of Epileptogenesis in a Mouse Model of Epilepsy

Large-scale brain networks are increasingly recognized as important for the generation of seizures in epilepsy. However, how a network evolves from a healthy state through the process of epileptogenesis remains unclear. To address this question, here, we study longitudinal epicranial background EEG recordings (30 electrodes, EEG free from epileptiform activity) of a mouse model of mesial temporal lobe epilepsy. We analyze functional connectivity networks and observe that over the time course of epileptogenesis the networks become increasingly asymmetric. Furthermore, computational modelling reveals that a set of nodes, located outside of the region of initial insult, emerges as particularly important for the network dynamics. These findings are consistent with experimental observations, thus demonstrating that ictogenic mechanisms can be revealed on the EEG, that computational models can be used to monitor unfolding epileptogenesis and that both the primary focus and epileptic network play a role in epileptogenesis.

Role of inhibitory control in modulating focal seizure spread

Focal seizure propagation is classically thought to be spatially contiguous. However, distribution of seizures through a large-scale epileptic network has been theorized. Here, we used a multielectrode array, wide field calcium imaging, and two-photon calcium imaging to study focal seizure propagation pathways in an acute rodent neocortical 4-aminopyridine model. Although ictal neuronal bursts did not propagate beyond a 2-3-mm region, they were associated with hemisphere-wide field potential fluctuations and parvalbumin-positive interneuron activity outside the seizure focus. While bicuculline surface application enhanced contiguous seizure propagation, focal bicuculline microinjection at sites distant to the 4-aminopyridine focus resulted in epileptic network formation with maximal activity at the two foci. Our study suggests that both classical and epileptic network propagation can arise from localized inhibition defects, and that the network appearance can arise in the context of normal brain structure without requirement for pathological connectivity changes between sites.

Pharmacotherapy for Focal Seizures in Children and Adolescents

Focal-onset seizures are among the most common forms of seizures in children and adolescents and can be caused by a wide diversity of acquired or genetic etiologies. Despite the increasing array of antiseizure drugs available, treatment of focal-onset seizures in this population remains problematic, with as many as one-third of children having seizures refractory to medications. This review discusses contemporary concepts in focal seizure classification and pathophysiology and describes the antiseizure medications most commonly chosen for this age group. As antiseizure drug efficacy is comparable in children and adults, here we focus on pharmacokinetic aspects, drug-drug interactions, and side effect profiles. Finally, we provide some suggestions for choosing the optimal medication for the appropriate patient.

Resolving the Micro-Macro Disconnect to Address Core Features of Seizure Networks

Current drug treatments for epilepsy attempt to broadly restrict excitability to mask a symptom, seizures, with little regard for the heterogeneous mechanisms that underlie disease manifestation across individuals. Here, we discuss the need for a more complete view of epilepsy, outlining how key features at the cellular and microcircuit level can significantly impact disease mechanisms that are not captured by the most common methodology to study epilepsy, electroencephalography (EEG). We highlight how major advances in neuroscience tool development now enable multi-scale investigation of fundamental questions to resolve the currently controversial understanding of seizure networks. These findings will provide essential insight into what has emerged as a disconnect between the different levels of investigation and identify new targets and treatment options.

Network pharmacology for antiepileptogenesis: Tolerability and neuroprotective effects of novel multitargeted combination treatments in nonepileptic vs. post-status epilepticus mice

Network-based approaches in drug discovery comprise both development of novel drugs interacting with multiple targets and repositioning of drugs with known targets to form novel drug combinations that interact with cellular or molecular networks whose function is disturbed in a disease. Epilepsy is a complex network phenomenon that, as yet, cannot be prevented or cured. We recently proposed multitargeted, network-based approaches to prevent epileptogenesis by combinations of clinically available drugs chosen to impact diverse epileptogenic processes. In order to test this strategy preclinically, we developed a multiphase sequential study design for evaluating such drug combinations in rodents, derived from human clinical drug development phases. Because pharmacokinetics of such drugs are known, only the tolerability of novel drug combinations needs to be evaluated in Phase I in öhealthy" controls. In Phase IIa, tolerability is assessed following an epileptogenic brain insult, followed by antiepileptogenic efficacy testing in Phase IIb. Here, we report Phase I and Phase IIa evaluation of 7 new drug combinations in mice, using 10 drugs (levetiracetam, topiramate, gabapentin, deferoxamine, fingolimod, ceftriaxone, α-tocopherol, melatonin, celecoxib, atorvastatin) with diverse mechanisms thought to be important in epileptogenesis. Six of the 7 drug combinations were well tolerated in mice during prolonged treatment at the selected doses in both controls and during the latent phase following status epilepticus induced by intrahippocampal kainate. However, none of the combinations prevented hippocampal damage in response to kainate, most likely because treatment started only 16-18 h after kainate. This suggests that antiepileptogenic or disease-modifying treatment may need to start earlier after the brain insult. The present data provide a rich collection of tolerable, network-based combinatorial therapies as a basis for antiepileptogenic or disease-modifying efficacy testing.

Large-Scale 3-5 Hz Oscillation Constrains the Expression of Neocortical Fast Ripples in a Mouse Model of Mesial Temporal Lobe Epilepsy

Large-scale slow oscillations allow the integration of neuronal activity across brain regions during sensory or cognitive processing. However, evidence that this form of coding also holds for pathological networks, such as for distributed networks in epileptic disorders, does not yet exist. Here, we show in a mouse model of unilateral hippocampal epilepsy that epileptic fast ripples generated in the neocortex distant from the primary focus occur during transient trains of interictal epileptic discharges. During these epileptic paroxysms, local phase-locking of neuronal firing and a phase-amplitude coupling of the epileptic discharges over a slow oscillation at 3-5 Hz are detected. Furthermore, the buildup of the slow oscillation begins in the bihippocampal network that includes the focus, which synchronizes and drives the activity across the large-scale epileptic network into the frontal cortex. This study provides the first functional description of the emergence of neocortical fast ripples in hippocampal epilepsy and shows that cross-frequency coupling might be a fundamental mechanism underlying the spreading of epileptic activity.

Pediatric Epilepsy Mechanisms: Expanding the Paradigm of Excitation/Inhibition Imbalance

Mechanisms underlying seizures and epilepsy have traditionally been considered to involve abnormalities of ion channels or synaptic function. Those considerations gave rise to the excitation/inhibition (E/I) imbalance theory, whereby increased excitation, decreased inhibition, or both favor a hyperexcitable state and an increased propensity for seizure generation and epileptogenesis. Several recent findings warrant reconsideration and expansion of the E/I hypothesis: novel genetic mutations have been identified that do not overtly affect E/I balance; neurotransmitters may exert paradoxical effects, especially during development; anti-seizure medications do not necessarily work by decreasing excitation or increasing inhibition; and metabolic factors participate in the regulation of neuronal and network excitability. These novel conceptual and experimental advances mandate expansion of the E/I paradigm, with the expectation that new and exciting therapies will emerge from this broadened understanding of how seizures and epilepsy arise and progress.

Epileptic foci localization based on mapping the synchronization of dynamic brain network

BACKGROUND

Characterizing the synchronous changes of epileptic seizures in different stages between different regions is profound to understand the transmission pathways of epileptic brain network and epileptogenic foci. There is currently no adequate quantitative calculation method for describing the propagation pathways of electroencephalogram (EEG) signals in the brain network from the short and long term. The goal of this study is to explore the innovative method to locate epileptic foci, mapping synchronization in the brain networks based on EEG.

METHODS

Mutual information was used to analyze the short-term synchronization in the full electrodes; while nonlinear dynamics quantifies the statistical independencies in the long -term among all electrodes. Then graph theory based on the complex network was employed to construct a dynamic brain network for epilepsy patients when they were awake, asleep and in seizure, analyzing the changing topology indexes.

RESULTS

Epileptic network achieved a high degree of nonlinear synchronization compared to awake time. and the main path of epileptiform activity was revealed by searching core nodes. The core nodes of the brain network were in connection with the onset zone. Seizures always happened with a high degree of distribution.

CONCLUSIONS

This study indicated the path of EEG synchronous propagation in seizures, and core nodes could locate the epileptic foci accurately in some epileptic patients.

Seizure susceptibility and infraslow modulatory activity in the intracranial electroencephalogram

OBJECTIVE

Studies of infraslow amplitude modulations (<0.15 Hz) of band power time series suggest that these envelope correlations may form a basis for distant spatial coupling in the brain. In this study, we sought to determine how infraslow relationships are affected by antiepileptic drug (AED) taper, time of day, and seizure.

METHODS

We studied intracranial electroencephalographic (icEEG) data collected from 13 medically refractory adult epilepsy patients who underwent monitoring at Yale-New Haven Hospital. We estimated the magnitude-squared coherence (MSC) at <0.15 Hz of traditional EEG frequency band power time series for all electrode contact pairs to quantify infraslow envelope correlations between them. We studied, first, hour-long background icEEG epochs before and after AED taper to understand the effect of taper. Second, we analyzed the entire record for each patient to study the effect of time of day. Finally, for each patient, we reviewed the clinical record to find all seizures that were at least 6 hours removed from other seizures and analyzed infraslow envelope MSC before and after them.

RESULTS

Infraslow envelope MSC increased slightly, but significantly, after AED taper, and increased on average during the night and decreased during the day. It was also increased significantly in all frequency bands up to 3 hours preseizure and 1 hour postseizure as compared to background icEEG (61 seizures studied). These changes occurred for both daytime and nighttime seizures (28 daytime, 33 nighttime). Interestingly, there was significant spatial variability to these changes, with the seizure onset area peaking at 3 hours preseizure, then showing progressive desynchronization from 3 hours preseizure to 1 hour postseizure.

SIGNIFICANCE

Infraslow envelope analysis may be used to understand long-term changes over the course of icEEG monitoring, provide unique insight into interictal electrophysiological changes related to ictogenesis, and contribute to the development of novel seizure forecasting algorithms.

Expanding Brain-Computer Interfaces for Controlling Epilepsy Networks: Novel Thalamic Responsive Neurostimulation in Refractory Epilepsy

Seizures have traditionally been considered hypersynchronous excitatory events and epilepsy has been separated into focal and generalized epilepsy based largely on the spatial distribution of brain regions involved at seizure onset. Epilepsy, however, is increasingly recognized as a complex network disorder that may be distributed and dynamic. Responsive neurostimulation (RNS) is a recent technology that utilizes intracranial electroencephalography (EEG) to detect seizures and delivers stimulation to cortical and subcortical brain structures for seizure control. RNS has particular significance in the clinical treatment of medically refractory epilepsy and brain–computer interfaces in epilepsy. Closed loop RNS represents an important step forward to understand and target nodes in the seizure network. The thalamus is a central network node within several functional networks and regulates input to the cortex; clinically, several thalamic nuclei are safe and feasible targets. We highlight the network theory of epilepsy, potential targets for neuromodulation in epilepsy and the first reported use of RNS as a first generation brain–computer interface to detect and stimulate the centromedian intralaminar thalamic nucleus in a patient with bilateral cortical onset of seizures. We propose that advances in network analysis and neuromodulatory techniques using brain–computer interfaces will significantly improve outcomes in patients with epilepsy. There are numerous avenues of future direction in brain–computer interface devices including multi-modal sensors, flexible electrode arrays, multi-site targeting, and wireless communication.

Multivariate regression methods for estimating velocity of ictal discharges from human microelectrode recordings

OBJECTIVE

Epileptiform discharges, an electrophysiological hallmark of seizures, can propagate across cortical tissue in a manner similar to traveling waves. Recent work has focused attention on the origination and propagation patterns of these discharges, yielding important clues to their source location and mechanism of travel. However, systematic studies of methods for measuring propagation are lacking.

APPROACH

We analyzed epileptiform discharges in microelectrode array recordings of human seizures. The array records multiunit activity and local field potentials at 400 micron spatial resolution, from a small cortical site free of obstructions. We evaluated several computationally efficient statistical methods for calculating traveling wave velocity, benchmarking them to analyses of associated neuronal burst firing.

MAIN RESULTS

Over 90% of discharges met statistical criteria for propagation across the sampled cortical territory. Detection rate, direction and speed estimates derived from a multiunit estimator were compared to four field potential-based estimators: negative peak, maximum descent, high gamma power, and cross-correlation. Interestingly, the methods that were computationally simplest and most efficient (negative peak and maximal descent) offer non-inferior results in predicting neuronal traveling wave velocities compared to the other two, more complex methods. Moreover, the negative peak and maximal descent methods proved to be more robust against reduced spatial sampling challenges. Using least absolute deviation in place of least squares error minimized the impact of outliers, and reduced the discrepancies between local field potential-based and multiunit estimators.

SIGNIFICANCE

Our findings suggest that ictal epileptiform discharges typically take the form of exceptionally strong, rapidly traveling waves, with propagation detectable across millimeter distances. The sequential activation of neurons in space can be inferred from clinically-observable EEG data, with a variety of straightforward computation methods available. This opens possibilities for systematic assessments of ictal discharge propagation in clinical and research settings.

Interneuronal Network Activity at the Onset of Seizure-Like Events in Entorhinal Cortex Slices

The onset of focal seizures in humans and in different animal models of focal epilepsy correlates with reduction of neuronal firing and enhanced interneuronal network activity. Whether this phenomenon contributes to seizure generation is still unclear. We used the in vitro entorhinal cortex slices bathed in 4-aminopirydine (4-AP) as an experimental paradigm model to evaluate the correlation between interneuronal GABAergic network activity and seizure-like events. Epileptiform discharges were recorded in layer V-VI pyramidal neurons and fast-spiking interneurons in slices from male and female mice and in the isolated female guinea pig brain preparation during perfusion with 4-AP. We observed that 90% of seizure-like events recorded in principal cells were preceded by outward currents coupled with extracellular potassium shifts, abolished by pharmacological blockade of GABA_A receptors. Potassium elevations associated to GABA_A receptor-mediated population events were confirmed in the entorhinal cortex of the in vitro isolated whole guinea pig brain. Fast-rising and sustained extracellular potassium increases associated to interneuronal network activity consistently preceded the initiation of seizure-like events. We conclude that in the 4-AP seizure model, interneuronal network activity occurs before 4-AP-induced seizures and therefore supports a role of interneuron activity in focal seizure generation.SIGNIFICANCE STATEMENT The paper focuses on the mechanisms of ictogenesis, a topic that requires a step beyond the simplistic view that seizures, and epilepsy, are due to an increase of excitatory network activity. Focal temporal lobe seizures in humans and in several experimental epilepsies likely correlate with a prevalent activation of interneurons. The potassium channel blocker 4-aminopyridine reliably induces seizure-like events in temporal lobe structures. Herein, we show that a majority of seizures in the entorhinal cortex starts with interneuronal network activity accompanied by a fast and sustained increase in extracellular potassium. Our new findings reinforce and add a new piece of evidence to the proposal that limbic seizures can be supported by GABAergic hyperactivity.

Hierarchical disruption in the Bayesian brain: Focal epilepsy and brain networks

In this opinion paper, we describe a combined view of functional and effective brain connectivity along with the free-energy principle for investigating persistent disruptions in brain networks of patients with focal epilepsy. These changes are likely reflected in effective connectivity along the cortical hierarchy and construct the basis of increased local functional connectivity in focal epilepsy. We propose a testable framework based on dynamic causal modelling and functional connectivity analysis with the capacity of explaining commonly observed connectivity changes during interictal periods. We then hypothesise their possible relation with disrupted free-energy minimisation in the Bayesian brain. This may offer a new approach for neuroimaging to specifically develop and address hypotheses regarding the network pathomechanisms underlying epileptic phenotypes.