Ligand-gated mechanisms leading to ictogenesis in focal epileptic disorders

We review here the neuronal mechanisms that cause seizures in focal epileptic disorders and, specifically, those involving limbic structures that are known to be implicated in human mesial temporal lobe epilepsy. In both epileptic patients and animal models, the initiation of focal seizures - which are most often characterized by a low-voltage fast onset EEG pattern - is presumably dependent on the synchronous firing of GABA-releasing interneurons that, by activating post-synaptic GABA_A receptors, cause large increases in extracellular [K⁺] through the activation of the co-transporter KCC2. A similar mechanism may contribute to seizure maintenance; accordingly, inhibiting KCC2 activity transforms seizure activity into a continuous pattern of short-lasting epileptiform discharges. It has also been found that interactions between different areas of the limbic system modulate seizure occurrence by controlling extracellular [K⁺] homeostasis. In line with this view, low-frequency electrical or optogenetic activation of limbic networks restrain seizure generation, an effect that may also involve the activation of GABA_B receptors and activity-dependent changes in epileptiform synchronization. Overall, these findings highlight the paradoxical role of GABA_A signaling in both focal seizure generation and maintenance, emphasize the efficacy of low-frequency activation in abating seizures, and provide experimental evidence explaining the poor efficacy of antiepileptic drugs designed to augment GABAergic function in controlling seizures in focal epileptic disorders.

GABAB Receptors: are they Missing in Action in Focal Epilepsy Research?

GABA, the key inhibitory neurotransmitter in the adult forebrain, activates pre- and postsynaptic receptors that have been categorized as GABAA, which directly open ligand-gated (or receptor-operated) ion-channels, and GABA_B, which are metabotropic since they operate through second messengers. Over the last three decades, several studies have addressed the role of GABA_B receptors in the pathophysiology of generalized and focal epileptic disorders. Here, we will address their involvement in focal epileptic disorders by mainly reviewing in vitro studies that have shown: (i) how either enhancing or decreasing GABA_B receptor function can favour epileptiform synchronization and thus ictogenesis, although with different features; (ii) the surprising ability of GABA_B receptor antagonism to disclose ictal-like activity when the excitatory ionotropic transmission is abolished; and (iii) their contribution to controlling seizure-like discharges during repetitive electrical stimuli delivered in limbic structures. In spite of this evidence, the role of GABA_B receptor function in focal epileptic disorders has been attracting less interest when compared to the numerous studies that have addressed GABA_A receptor signaling. Therefore, the main aim of our mini-review is to revive interest in the function of GABA_B receptors in focal epilepsy research.

Electrical stimulation of the endopiriform nucleus attenuates epilepsy in rats by network modulation

OBJECTIVE

Neuromodulatory anterior thalamic deep brain stimulation (DBS) is an effective therapy for intractable epilepsy, but few patients achieve complete seizure control with thalamic DBS. Other stimulation sites may be considered for anti-seizure DBS. We investigated bilateral low-frequency stimulation of the endopiriform nuclei (LFS-EPN) to control seizures induced by intracortically implanted cobalt wire in rats.

METHODS

Chronic epilepsy was induced by cobalt wire implantation in the motor cortex unilaterally. Bipolar-stimulating electrodes were implanted into the EPN bilaterally. Continuous electroencephalography (EEG) was recorded using electrodes placed into bilateral motor cortex and hippocampus CA1 areas. Spontaneous seizures were monitored by long-term video-EEG, and behavioral seizures were classified based on the Racine scale. Continuous 1-Hz LFS-EPN began on the third day after electrode implantation and was controlled by a multi-channel stimulator. Stimulation continued until the rats had no seizures for three consecutive days.

RESULTS

Compared with the control and sham stimulation groups, the LFS-EPN group experienced significantly fewer seizures per day and the mean Racine score of seizures was lower due to fewer generalized seizures. Ictal discharges at the epileptogenic site had significantly reduced theta band power in the LFS-EPN group compared to the other groups.

INTERPRETATION

Bilateral LFS-EPN attenuates cobalt wire-induced seizures in rats by modulating epileptic networks. Reduced ictal theta power of the EEG broadband spectrum at the lesion site may be associated with the anti-epileptogenic mechanism of LFS-EPN. Bilateral EPN DBS may have therapeutic applications in human partial epilepsies.

Comparison of fiber tract low frequency stimulation to focal and ANT stimulation in an acute rat model of focal cortical seizures

BACKGROUND

Current implementations of direct brain stimulation for epilepsy in patients involve high-frequency (HFS) electrical current and targeting of grey matter. Studies have shown that low-frequency (LFS) fiber-tract stimulation may also prove effective. To compare the efficacy of high-frequency grey matter stimulation to the low-frequency fiber tract stimulation technique a well-controlled set of experiments using a single animal model of epilepsy is needed.

OBJECTIVE

The goal of this study was to determine the relative efficacy of different direct brain stimulation techniques for suppressing seizures using an acute rat model of focal cortical seizures.

METHODS

4-AP was injected into the S1 region of cortex in rodents over 3 h. LFPs were recorded from the seizure focus and mirror focus to monitor seizure frequency during the experiments. CC-LFS, HFS-ANT, Focal-HFS, or a transection of the CC was applied.

RESULTS

Stimulation of the CC yielded a 65% ±14% (p = 0.0014) reduction of seizures in the focus and a 97% ±15% (p = 0.0026) reduction in the mirror focus (n = 7). By comparison transection of the CC produced a 65% ±18% reduction in the focus and a non-statistically significant reduction of 57% ±18% (p = 0.1381) in the mirror focus (n = 5). All other methods of stimulation failed to have a statistically significant effect on seizure suppression.

CONCLUSIONS

LFS of the CC is the only method of stimulation to significantly reduce seizure frequency in this model of focal cortical seizures. These results support the hypothesis that LFSof fiber tracts has significant potential for seizure control.

Corpus callosum low-frequency stimulation suppresses seizures in an acute rat model of focal cortical seizures

OBJECTIVE

Low-frequency fiber-tract stimulation has been shown to be effective in treating mesial temporal lobe epilepsies through activation of the hippocampal commissure in rodents and human patients. The corpus callosum is a major pathway connecting the two hemispheres of the brain; however, few experiments have documented corpus callosum stimulation. The objective is to determine the efficacy of corpus callosum stimulation at low frequencies to suppress cortical seizures.

METHODS

4-Aminopyridine was injected in the primary motor cortex of 24 rats under anesthesia. Recording electrodes were placed in the contralateral motor cortex and hippocampus. Three pairs of stimulating electrodes were inserted into the corpus callosum along its longitudinal axis. Local field potentials were recorded 1 hour before, during, and after stimulation to determine the effect of stimulation on seizure duration. Stimulation was delivered from each pair of electrodes independently in separate experiments. Furthermore, electrical stimulation was applied to the region of the corpus callosum with the highest degree of innervation of the seizure focus to compare the efficacy of different stimulation frequencies (1-30 Hz) on seizure suppression.

RESULTS

Corpus callosum stimulation was effective at suppressing seizures at 10 Hz by 76% (P < 0.05, n = 5) and at 20 Hz by 95% (P < 0.0001, n = 14). Stimulation at frequencies of 1 and 30 Hz did not have a significant effect on reducing the total time spent seizing (P > 0.9999, n = 5). Furthermore, stimulation was only effective at suppressing seizures when the pair of electrodes was placed within the section of corpus callosum containing fibers innervating the seizure focus. Secondarily generalized seizures in the hippocampus were eliminated when seizures in the cortical focus were suppressed.

SIGNIFICANCE

Low-frequency fiber-tract stimulation of the corpus callosum suppresses both cortical and cortically induced hippocampal seizures in an acute model of focal cortical seizures. The stimulation paradigm is selective, as it is only effective when targeted to specific regions of the corpus callosum that project maximally to cortical regions generating the seizure activity. Selective placement of stimulation electrodes along the corpus callosum could be used as a patient-specific treatment for cortical epilepsies.

The epileptic amygdala: Toward the development of a neural prosthesis by temporally coded electrical stimulation

Many patients with epilepsy do not obtain proper control of their seizures through conventional treatment. We review aspects of the pathophysiology underlying epileptic phenomena, with a special interest in the role of the amygdala, stressing the importance of hypersynchronism in both ictogenesis and epileptogenesis. We then review experimental studies on electrical stimulation of mesiotemporal epileptogenic areas, the amygdala included, as a means to treat medically refractory epilepsy. Regular high-frequency stimulation (HFS) commonly has anticonvulsant effects and sparse antiepileptogenic properties. On the other hand, HFS is related to acute and long-term increases in excitability related to direct neuronal activation, long-term potentiation, and kindling, raising concerns regarding its safety and jeopardizing in-depth understanding of its mechanisms. In turn, the safer regular low-frequency stimulation (LFS) has a robust antiepileptogenic effect, but its pro- or anticonvulsant effect seems to vary at random among studies. As an alternative, studies by our group on the development and investigation of temporally unstructured electrical stimulation applied to the amygdala have shown that nonperiodic stimulation (NPS), which is a nonstandard form of LFS, is capable of suppressing both acute and chronic spontaneous seizures. We hypothesize two noncompetitive mechanisms for the therapeutic role of amygdala in NPS, 1) a direct desynchronization of epileptic circuitry in the forebrain and brainstem and 2) an indirect desynchronization/inhibition through nucleus accumbens activation. We conclude by reintroducing the idea that hypersynchronism, rather than hyperexcitability, may be the key for epileptic phenomena and epilepsy treatment.

Seizure reduction through interneuron-mediated entrainment using low frequency optical stimulation

Low frequency electrical stimulation (LFS) can reduce neural excitability and suppress seizures in animals and patients with epilepsy. However the therapeutic outcome could benefit from the determination of the cell types involved in seizure suppression. We used optogenetic techniques to investigate the role of interneurons in LFS (1Hz) in the epileptogenic hippocampus. Optical low frequency stimulation (oLFS) was first used to activate the cation channel channelrhodopsin-2 (ChR2) in the Thy1-ChR2 transgenic mouse that expresses ChR2 in both excitatory and inhibitory neurons. We found that oLFS could effectively reduce epileptiform activity in the hippocampus through the activation of GAD-expressing hippocampal interneurons. This was confirmed using the VGAT-ChR2 transgenic mouse, allowing for selective optical activation of only GABA interneurons. Activating hippocampal interneurons through oLFS was found to cause entrainment of neural activity similar to electrical stimulation, but through a GABAA-mediated mechanism. These results confirm the robustness of the LFS paradigm and indicate that GABA interneurons play an unexpected role of shaping inter-ictal activity to decrease neural excitability in the hippocampus.

Reliability of unstable periodic orbit based control strategies in biological systems

Presence of recurrent and statistically significant unstable periodic orbits (UPOs) in time series obtained from biological systems is now routinely used as evidence for low dimensional chaos. Extracting accurate dynamical information from the detected UPO trajectories is vital for successful control strategies that either aim to stabilize the system near the fixed point or steer the system away from the periodic orbits. A hybrid UPO detection method from return maps that combines topological recurrence criterion, matrix fit algorithm, and stringent criterion for fixed point location gives accurate and statistically significant UPOs even in the presence of significant noise. Geometry of the return map, frequency of UPOs visiting the same trajectory, length of the data set, strength of the noise, and degree of nonstationarity affect the efficacy of the proposed method. Results suggest that establishing determinism from unambiguous UPO detection is often possible in short data sets with significant noise, but derived dynamical properties are rarely accurate and adequate for controlling the dynamics around these UPOs. A repeat chaos control experiment on epileptic hippocampal slices through more stringent control strategy and adaptive UPO tracking is reinterpreted in this context through simulation of similar control experiments on an analogous but stochastic computer model of epileptic brain slices. Reproduction of equivalent results suggests that far more stringent criteria are needed for linking apparent success of control in such experiments with possible determinism in the underlying dynamics.

Suppression of acute seizures by theta burst electrical stimulation of the hippocampal commissure using a closed-loop system

This study investigated the effects of electrical stimulation with theta burst stimulation (eTBS) on seizure suppression. Optimal parameters of eTBS were determined through open-loop stimulation experiments and then implemented in a close-loop seizure control system. For the experiments, 4-aminopyridine (4-AP) was injected into the right hippocampus of Sprague-Dawley rats to induce an acute seizure. eTBS was applied on the ventral hippocampal commissure and the effects of eTBS with different combinations of burst frequency and number of pulses per burst were analyzed in terms of seizure suppression. A closed-loop seizure control system was then implemented based on optimal eTBS parameters. The efficiency of the closed-loop eTBS was evaluated and compared to that of high frequency stimulation. The results show that eTBS induced global suppression in the hippocampus and this was sustained even after the application of eTBS. The optimal parameter of eTBS in the open-loop stimulation experiments was a burst frequency at 100Hz with nine pulses in a burst. The eTBS integrated with the on-off control law yielded less actions and cumulative delivered charge, but induced longer after-effects of seizure suppression compared to continuous high frequency stimulation (cHFS). To conclude, eTBS has suppressive effects on 4-AP induced seizure. A closed-loop eTBS system provides a more effective way of suppressing seizure and requires less effort compared to cHFS. eTBS may be a novel stimulation protocol for effective seizure control.

A Wavelet-Statistical Features Approach for Nonconvulsive Seizure Detection

The detection of nonconvulsive seizures (NCSz) is a challenge because of the lack of physical symptoms, which may delay the diagnosis of the disease. Many researchers have reported automatic detection of seizures. However, few investigators have concentrated on detection of NCSz. This article proposes a method for reliable detection of NCSz. The electroencephalography (EEG) signal is usually contaminated by various nonstationary noises. Signal denoising is an important preprocessing step in the analysis of such signals. In this study, a new wavelet-based denoising approach using cubical thresholding has been proposed to reduce noise from the EEG signal prior to analysis. Three statistical features were extracted from wavelet frequency bands, encompassing the frequency range of 0 to 8, 8 to 16, 16 to 32, and 0 to 32 Hz. Extracted features were used to train linear classifier to discriminate between normal and seizure EEGs. The performance of the method was tested on a database of nine patients with 24 seizures in 80 hours of EEG recording. All the seizures were successfully detected, and false positive rate was found to be 0.7 per hour.

MULTIPLE OSCILLATORY STATES IN MODELS OF COLLECTIVE NEURONAL DYNAMICS

In our previous studies, we showed that the both realistic and analytical computational models of neural dynamics can display multiple sustained states (attractors) for the same values of model parameters. Some of these states can represent normal activity while other, of oscillatory nature, may represent epileptic types of activity. We also showed that a simplified, analytical model can mimic this type of behavior and can be used instead of the realistic model for large scale simulations. The primary objective of the present work is to further explore the phenomenon of multiple stable states, co-existing in the same operational model, or phase space, in systems consisting of large number of interconnected basic units. As a second goal, we aim to specify the optimal method for state control of the system based on inducing state transitions using appropriate external stimulus. We use here interconnected model units that represent the behavior of neuronal populations as an effective dynamic system. The model unit is an analytical model (S. Kalitzin et al., Epilepsy Behav. 22 (2011) S102–S109) and does not correspond directly to realistic neuronal processes (excitatory–inhibitory synaptic interactions, action potential generation). For certain parameter choices however it displays bistable dynamics imitating the behavior of realistic neural mass models. To analyze the collective behavior of the system we applied phase synchronization analysis (PSA), principal component analysis (PCA) and stability analysis using Lyapunov exponent (LE) estimation. We obtained a large variety of stable states with different dynamic characteristics, oscillatory modes and phase relations between the units. These states can be initiated by appropriate initial conditions; transitions between them can be induced stochastically by fluctuating variables (noise) or by specific inputs. We propose a method for optimal reactive control, allowing forced transitions from one state (attractor) into another.

THE EFFECT OF HIGH AND LOW FREQUENCY CORTICAL STIMULATION WITH A FIXED OR A POISSON DISTRIBUTED INTERPULSE INTERVAL ON CORTICAL EXCITABILITY IN RATS

Neurostimulation is a promising treatment for refractory epilepsy. We studied the effect of cortical stimulation with different parameters in the rat motor cortex stimulation model. High intensity simulation (threshold for motor response - 100 μA), high frequency (130 Hz) stimulation during 1 h decreased cortical excitability, irrespective of the interpulse interval used (fixed or Poisson distributed). Low intensity (10 μA) and/or low frequency (5 Hz) stimulation had no effect. Cortical stimulation appears promising for the treatment of neocortical epilepsy if frequency and intensity are high enough.

Computational modeling of transcranial direct current stimulation in the child brain: implications for the treatment of refractory childhood focal epilepsy

Transcranial direct current stimulation (tDCS) was recently proposed for the treatment of epilepsy. However, the electrode arrangement for this case is debated. This paper analyzes the influence of the position of the anodal electrode on the electric field in the brain. The simulation shows that moving the anode from scalp to shoulder does influence the electric field not only in the cortex, but also in deeper brain regions. The electric field decreases dramatically in the brain area without epileptiform activity.

Aggregation of sparse linear discriminant analyses for event-related potential classification in brain-computer interface

Two main issues for event-related potential (ERP) classification in brain-computer interface (BCI) application are curse-of-dimensionality and bias-variance tradeoff, which may deteriorate classification performance, especially with insufficient training samples resulted from limited calibration time. This study introduces an aggregation of sparse linear discriminant analyses (ASLDA) to overcome these problems. In the ASLDA, multiple sparse discriminant vectors are learned from differently l1-regularized least-squares regressions by exploiting the equivalence between LDA and least-squares regression, and are subsequently aggregated to form an ensemble classifier, which could not only implement automatic feature selection for dimensionality reduction to alleviate curse-of-dimensionality, but also decrease the variance to improve generalization capacity for new test samples. Extensive investigation and comparison are carried out among the ASLDA, the ordinary LDA and other competing ERP classification algorithms, based on different three ERP datasets. Experimental results indicate that the ASLDA yields better overall performance for single-trial ERP classification when insufficient training samples are available. This suggests the proposed ASLDA is promising for ERP classification in small sample size scenario to improve the practicability of BCI.

Mechanism of highly synchronized bilateral hippocampal activity

In vivo studies of epileptiform discharges in the hippocampi of rodents have shown that bilateral seizure activity can sometimes be synchronized with very small delays (<2 ms). This observed small time delay of epileptiform activity between the left and right CA3 regions is unexpected given the physiological propagation time across the hemispheres (>6 ms). The goal of this study is to determine the mechanisms of this tight synchronization with in-vitro electrophysiology techniques and computer simulations. The hypothesis of a common source was first eliminated by using an in-vitro preparation containing both hippocampi with a functional ventral hippocampal commissure (VHC) and no other tissue. Next, the hypothesis that a noisy baseline could mask the underlying synchronous activity between the two hemispheres was ruled out by low noise in-vivo recordings and computer simulation of the noisy environment. Then we built a novel bilateral CA3 model to test the hypothesis that the phenomenon of very small left-to-right propagation delay of seizure activity is a product of epileptic cell network dynamics. We found that the commissural tract connectivity could decrease the delay between seizure events recorded from two sides while the activity propagated longitudinally along the CA3 layer thereby yielding delays much smaller than the propagation time between the two sides. The modeling results indicate that both recurrent and feedforward inhibition were required for shortening the bilateral propagation delay and depended critically on the length of the commissural fiber tract as well as the number of cells involved in seizure generation. These combined modeling/experimental studies indicate that it is possible to explain near perfect synchronization between the two hemispheres by taking into account the structure of the hippocampal network.

Long-lasting hyperpolarization underlies seizure reduction by low frequency deep brain electrical stimulation

Mesial temporal lobe epilepsy (MTLE) is a common medically refractory neurological disease. Deep brain electrical stimulation (DBS) of grey matter has been used for MTLE with limited success. However, stimulation of a white matter tract connecting the hippocampi, the ventral hippocampal commissure (VHC), with low frequencies that simulate interictal discharges has shown promising results, with seizure reduction greater than 98% in bilateral hippocampi during stimulation and greater than 50% seizure reduction in bilateral hippocampi after treatment. A major hurdle to the implementation and optimization of this treatment is that the mechanisms of seizure reduction by low frequency electrical stimulation (LFS) are not known. The goal of this study is to understand how commissural fibre tract stimulation reduces bilateral hippocampal epileptic activity in an in vitro slice preparation containing bilateral hippocampi connected by the VHC. It is our hypothesis that electrical stimuli induce hyperpolarization lasting hundreds of milliseconds following each pulse which reduces spontaneous epileptic activity during each inter-stimulus interval (ISI). Stimulus-induced long-lasting-hyperpolarization (LLH) can be mediated by GABA(B) inhibitory post-synaptic potentials (IPSPs) or slow after-hyperpolarization (sAHP). To test the role of LLH in effective bilateral seizure reduction by fibre tract stimulation, we measured stimulus-induced hyperpolarization during LFS of the VHC using electrophysiology techniques. Antagonism of the GABA(B) IPSP and/or sAHP diminished stimulus-induced hyperpolarization concurrently with LFS efficacy (greater than 50% reduction). Blocking both the GABA(B) IPSP and sAHP simultaneously eliminated the effect of electrical stimulation on seizure reduction entirely. These data show that LFS of the VHC is an effective protocol for bilateral hippocampal seizure reduction and that its efficacy relies on the induction of long-lasting hyperpolarization mediated through GABA(B) IPSPs and sAHP. Based on this study, optimization of the timing of LFS and LFS-induced-LLH may lead to improved outcomes from DBS treatments for human epilepsy.

Application of intrinsic time-scale decomposition (ITD) to EEG signals for automated seizure prediction

Intrinsic time-scale decomposition (ITD) is a new nonlinear method of time-frequency representation which can decipher the minute changes in the nonlinear EEG signals. In this work, we have automatically classified normal, interictal and ictal EEG signals using the features derived from the ITD representation. The energy, fractal dimension and sample entropy features computed on ITD representation coupled with decision tree classifier has yielded an average classification accuracy of 95.67%, sensitivity and specificity of 99% and 99.5%, respectively using 10-fold cross validation scheme. With application of the nonlinear ITD representation, along with conceptual advancement and improvement of the accuracy, the developed system is clinically ready for mass screening in resource constrained and emerging economy scenarios.

EFFICIENT AUTOMATIC SELECTION AND COMBINATION OF EEG FEATURES IN LEAST SQUARES CLASSIFIERS FOR MOTOR IMAGERY BRAIN–COMPUTER INTERFACES

Discriminative features have to be properly extracted and selected from the electroencephalographic (EEG) signals of each specific subject in order to achieve an adaptive brain–computer interface (BCI) system. This work presents an efficient wrapper-based methodology for feature selection and least squares discrimination of high-dimensional EEG data with low computational complexity. Features are computed in different time segments using three widely used methods for motor imagery tasks and, then, they are concatenated or averaged in order to take into account the time course variability of the EEG signals. Once EEG features have been extracted, proposed framework comprises two stages. The first stage entails feature ranking and, in this work, two different procedures have been considered, the least angle regression (LARS) and the Wilcoxon rank sum test, to compare the performance of each one. The second stage selects the most relevant features using an efficient leave-one-out (LOO) estimation based on the Allen's PRESS statistic. Experimental comparisons with the state-of-the-art BCI methods shows that this approach gives better results than current state-of-the-art approaches in terms of recognition rates and computational requirements and, also with respect to the first ranking stage, it is confirmed that the LARS algorithm provides better results than the Wilcoxon rank sum test for these experiments.

PHASE SYNCHRONIZATION OF NEURONAL NOISE IN MOUSE HIPPOCAMPAL EPILEPTIFORM DYNAMICS

Organized brain activity is the result of dynamical, segregated neuronal signals that may be used to investigate synchronization effects using sophisticated neuroengineering techniques. Phase synchrony analysis, in particular, has emerged as a promising methodology to study transient and frequency-specific coupling effects across multi-site signals. In this study, we investigated phase synchronization in intracellular recordings of interictal and ictal epileptiform events recorded from pairs of cells in the whole (intact) mouse hippocampus. In particular, we focused our analysis on the background noise-like activity (NLA), previously reported to exhibit complex neurodynamical properties. Our results show evidence for increased linear and nonlinear phase coupling in NLA across three frequency bands [theta (4–10 Hz), beta (12–30 Hz) and gamma (30–80 Hz)] in the ictal compared to interictal state dynamics. We also present qualitative and statistical evidence for increased phase synchronization in the theta, beta and gamma frequency bands from paired recordings of ictal NLA. Overall, our results validate the use of background NLA in the neurodynamical study of epileptiform transitions and suggest that what is considered "neuronal noise" is amenable to synchronization effects in the spatiotemporal domain.

Fiber tract stimulation can reduce epileptiform activity in an in-vitro bilateral hippocampal slice preparation

Mesial temporal lobe epilepsy (MTLE) is a common medically refractory neurological disease that has been treated with electrical stimulation of gray matter with limited success. However, stimulation of a white matter tract connecting the hippocampi could maximize treatment efficacy and extent. We tested low-frequency stimulation (LFS) of a novel target that enables simultaneous targeting of bilateral hippocampi: the ventral hippocampal commissure (VHC) with a novel in-vitro slice preparation containing bilateral hippocampi connected by the VHC. The goal of this study is to understand the role of hippocampal interplay in seizure propagation and reduction by commissural fiber tract stimulation. LFS is applied to the VHC as extracellular and intracellular recording techniques are combined with signal processing to estimate several metrics of epilepsy including: (1) total time occupied by seizure activity (%); (2) seizure duration (s); (3) seizures per minute (#); and (4) power in the ictal (V(2)Hz(-1)); as well as (5) interictal spectra (V(2)Hz(-1)). Bilateral epileptiform activity in this preparation is highly correlated between hippocampi. Application of LFS to the VHC reduces all metrics of epilepsy during treatment in an amplitude and frequency dependent manner. This study lends several insights into the mechanisms of bilateral seizure reduction by LFS of the VHC, including that depolarization blocking, LTD/LTP and GABA(A) are not involved. Importantly, enhanced post-stimulation 1-Hz spiking correlates with long-lasting seizure reduction and both are heightened by targeting bilateral hippocampi via the VHC. Therefore, stimulating bilateral hippocampi via a single electrode in the VHC may provide an effective MTLE treatment.