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Sleep-wake regulation is thought to be governed by interactions among several nuclei in midbrain, pons, and hypothalamic regions. Determination of the causal role of these nuclei in state transitions requires simultaneous measurements from the nuclei with sufficient spatial and temporal resolution. We obtained long-term experimental single- and multi-unit measurements simultaneously from multiple nuclei of the putative hypothalamic and brainstem sleep-wake regulatory network in freely behaving rats. Cortical and hippocampal activity, along with head acceleration were also acquired to assess behavioral state. Here, we confirm that the general activity profile of the recorded sleep-wake regulatory nuclei is similar to the patterns presented previously in brief recordings of individual nuclei in head-fixed animals. However, we found that these activity profiles when studied with respect to cortical and behavioral signs of state transitions differ significantly from previous reports. Our findings pose fundamental questions about the neural mechanisms that maintain specific states and the neural interactions that lead to the emergence of sleep-wake states.

Spreading depression is characterized by slow, propagating wave of cellular depolarization (SD) and is wildly associated with migraine, stroke, and traumatic brain injury. Seizures and spreading depression (or spreading depolarization, SD) have long been reported to coincide in acute seizure induction experiments. However, SD has not been observed associated with spotaneous seizures in animal or clinical recordings. Recently, advances in acquisition systems for neurointensive care units have made routine observations of SD possible. In clinical epilepsy, SD has been suggested as a candidate mechanism for migraine/headache like events following seizures as well as for post-ictal generalized suppression. In animal models of epilepsy, seizure-induced brainstem SD has also been demonstrated as a mechanism of sudden unexplained death in epilepsy (SUDEP). The interplay between seizures and SD has also been suggested in computational models, where the two are components of the repetoir of neuronal activity.However, the spatiotemporal dynamics of SD with respect to spontaneous seizures in chronically epileptic brain remains ambigous. We analyzed continuous long-term DC sensitive EEG measurements from two fundamentally different animal models of chronic epilepsy. We found that SD was associated with approximately one-third of all spontaneous seizures in each model. Additionally, SDs participated in the organization of seizure clusters. These findings demonstrate that the underlying dynamic of epileptic events is broader than seizures alone.Significance StatementSpreading depression is characterized by slow, propagating wave of cellular spreading depolarization (SD) and is wildly associated with migraine, stroke, and traumatic brain injury. Although recently the linkage between SD and induced seizures has been recognized, the mechanistic relationship between SD and spontaneous seizures remains poorly understood. Here, we utilized long-term, stable, near-DC measurements of the brain activity in two fundamentally different animal models of epilepsy to investigate the SD-seizure interplay. We found that SD is a frequent phenomenon in the epileptic brain, in these models is associated with more than a third of all seizures, and appears to connect seizures in seizure clusters. Although in one model SD stereotypically propagates out from a single focus in the hippocampus, depression of the field-potentials is observed synchronously across much of the hippocampus. These observations highlight the value of stable DC measurements for accurate understanding of SD and its propagation. We found that spontaneous ictal events that include both seizures and SD are frequent in animal models of epilepsy. These findings suggest that SD could be a valuable target for treatment and control of epilepsy.

Postinjury epilepsy is an potentially preventable sequela in as many as 20% of patients with brain insults. For these cases biomarkers of epileptogenesis are critical to facilitate identification of patients at high-risk of developing epilepsy and to introduce effective anti-epileptogenic interventions. Here, we demonstrate that delayed brain–heart coincidences serve as a reliable biomarker. In a murine model of post-infection acquired epilepsy, we used long-term simultaneous measurements of the brain activity via electroencephalography and autonomic cardiac activity via electrocardiography, in male mice, to quantitatively track brain–heart interactions during epileptogenesis. We find that abnormal cortical discharges precede abnormal fluctuations in the cardiac rhythm at the resolution of single beat-to-beat intervals. The delayed brain–heart coincidence is detectable as early as the onset of chronic measurements, 2–14 weeks before the first seizure, only in animals that become epileptic, and increases during epileptogenesis. Therefore, delayed brain–heart coincidence serves as a biomarker of epileptogenesis and could be used for phenotyping, diagnostic, and therapeutic purposes.SIGNIFICANCE STATEMENTNo biomarker that readily predicts and tracks epileptogenesis currently exists for the wide range of human acquired epilepsies. Here, we used long-term measurements of brain and heart activity in a mouse model of post-infection acquired epilepsy to investigate the potential of brain–heart interaction as a biomarker of epileptogenesis. We found that delayed coincidences from brain to heart can clearly separate the mice that became epileptic from those that did not weeks before development of epilepsy. Our findings allow for phenotyping and tracking of epileptogenesis in this and likely other models of acquired epilepsy. Such capability is critical for efficient adjunctive treatment development and for tracking the efficacy of such treatments.

Electrical stimulation offers the potential to develop novel strategies for the treatment of refractory medial temporal lobe epilepsy. In particular, direct electrical stimulation of the hippocampus presents the opportunity to modulate pathological dynamics at the ictal focus, although the neuroanatomical substrate of this region renders it susceptible to altering cognition and affective processing as a side effect. We investigated the effects of three electrical stimulation paradigms on separate groups of freely moving rats (sham, 8-Hz and 40-Hz sine-wave stimulation of the ventral/intermediate hippocampus, where 8- and 40-Hz stimulation were chosen to mimic naturally occurring hippocampal oscillations). Animals exhibited attenuated locomotor and exploratory activity upon stimulation at 40 Hz, but not at sham or 8-Hz stimulation. Such behavioral modifications were characterized by a significant reduction in rearing frequency, together with increased freezing behavior. Logistic regression analysis linked the observed changes in animal locomotion to 40-Hz electrical stimulation independently of time-related variables occurring during testing. Spectral analysis, conducted to monitor the electrophysiological profile in the CA1 area of the dorsal hippocampus, showed a significant reduction in peak theta frequency, together with reduced theta power in the 40-Hz vs. the sham stimulation animal group, independent of locomotion speed (theta range: 4–12 Hz). These findings contribute to the development of novel and safe medical protocols by indicating a strategy to constrain or optimize parameters in direct hippocampal electrical stimulation.

Improved understanding of the interaction between state of vigilance (SOV) and seizure onset has therapeutic potential. Six rats received injections of tetanus toxin (TeTX) in the ventral hippocampus that resulted in chronic spontaneous seizures. The distribution of SOV before 486 seizures was analyzed for a total of 19 d of recording. Rapid eye movement sleep (REM) and exploratory wake, both of which express prominent hippocampal theta rhythm, preceded 47 and 34%, for a total of 81%, of all seizures. Nonrapid eye movement sleep (NREM) and nonexploratory wake, neither of which expresses prominent theta, preceded 6.8 and 13% of seizures. We demonstrate that identification of SOV yields significant differentiation of seizure susceptibilities, with the instantaneous seizure rate during REM nearly 10 times higher than baseline and the rate for NREM less than half of baseline. Survival analysis indicated a shorter duration of preseizure REM bouts, with a maximum transition to seizure at ∼90 s after the onset of REM. This study provides the first analysis of a correlation between SOV and seizure onset in the TeTX model of temporal lobe epilepsy, as well as the first demonstration that hippocampal theta rhythms associated with natural behavioral states can serve a seizure-promoting role. Our findings are in contrast with previous studies suggesting that the correlations between SOV and seizures are primarily governed by circadian oscillations and the notion that hippocampal theta rhythms inhibit seizures. The documentation of significant SOV-dependent seizure susceptibilities indicates the potential utility of SOV and its time course in seizure prediction and control.

Sleep is important for normal brain function, and sleep disruption is comorbid with many neurological diseases. There is a growing mechanistic understanding of the neurological basis for sleep regulation that is beginning to lead to mechanistic mathematically described models. It is our objective to validate the predictive capacity of such models using data assimilation (DA) methods. If such methods are successful, and the models accurately describe enough of the mechanistic functions of the physical system, then they can be used as sophisticated observation systems to reveal both system changes and sources of dysfunction with neurological diseases and identify routes to intervene. Here we report on extensions to our initial efforts [1] at applying unscented Kalman Filter (UKF) to models of sleep regulation on three fronts: tools for multi-parameter fitting; a sophisticated observation model to apply the UKF for observations of behavioral state; and comparison with data recorded from brainstem cell groups thought to regulate sleep.

Theta (4---12 Hz) and gamma (30---80 Hz) rhythms are considered important for cortical and hippocampal function. Although several neuron types are implicated in rhythmogenesis, the exact cellular mechanisms remain unknown. Subthreshold electric fields provide a flexible, area-specific tool to modulate neural activity and directly test functional hypotheses. Here we present experimental and computational evidence of the interplay among hippocampal synaptic circuitry, neuronal morphology, external electric fields, and network activity. Electrophysiological data are used to constrain and validate an anatomically and biophysically realistic model of area CA1 containing pyramidal cells and two interneuron types: dendritic- and perisomatic-targeting. We report two lines of results: addressing the network structure capable of generating theta-modulated gamma rhythms, and demonstrating electric field effects on those rhythms. First, theta-modulated gamma rhythms require specific inhibitory connectivity. In one configuration, GABAergic axo-dendritic feedback on pyramidal cells is only effective in proximal but not distal layers. An alternative configuration requires two distinct perisomatic interneuron classes, one exclusively receiving excitatory contacts, the other additionally targeted by inhibition. These observations suggest novel roles for particular classes of oriens and basket cells. The second major finding is that subthreshold electric fields robustly alter the balance between different rhythms. Independent of network configuration, positive electric fields decrease, while negative fields increase the theta/gamma ratio. Moreover, electric fields differentially affect average theta frequency depending on specific synaptic connectivity. These results support the testable prediction that subthreshold electric fields can alter hippocampal rhythms, suggesting new approaches to explore their cognitive functions and underlying circuitry.

Cortical oscillations arise during behavioral and mental tasks, and all temporal oscillations have particular spatial patterns. Studying the mechanisms that generate and modulate the spatiotemporal characteristics of oscillations is important for understanding neural information processing and the signs and symptoms of dynamical diseases of the brain. Nevertheless, it remains unclear how GABAergic inhibition modulates these oscillation dynamics. Using voltage-sensitive dye imaging, pharmacological methods, and tangentially cut occipital neocortical brain slices (including layers 3–5) of Sprague-Dawley rat, we found that GABAa disinhibition with bicuculline can progressively simplify oscillation dynamics in the presence of carbachol in a concentration-dependent manner. Additionally, GABAb disinhibition can further simplify oscillation dynamics after GABAa receptors are blocked. Both GABAa and GABAb disinhibition increase the synchronization of the neural network. Theta frequency (5–15-Hz) oscillations are reliably generated by using a combination of GABAa and GABAb antagonists alone. These theta oscillations have basic spatiotemporal patterns similar to those generated by carbachol ⁄bicuculline. These results are illustrative of how GABAergic inhibition increases the complexity of patterns of activity and contributes to the regulation of the cortex.

Electrical stimulation is emerging as a viable alternative for patients with epilepsy whose seizures are not alleviated by drugs or surgery. Its attractions are temporal and spatial specificity of action, flexibility of waveform parameters and timing, and the perception that its effects are reversible unlike resective surgery. However, despite significant advances in our understanding of mechanisms of neural electrical stimulation, clinical electrotherapy for seizures relies heavily on empirical tuning of parameters and protocols. We highlight concurrent treatment goals with potentially conflicting design constraints that must be resolved when formulating rational strategies for epilepsy electrotherapy, namely, seizure reduction versus cognitive impairment, stimulation efficacy versus tissue safety, and mechanistic insight versus clinical pragmatism. First, treatment markers, objectives, and metrics relevant to electrical stimulation for epilepsy are discussed from a clinical perspective. Then the experimental perspective is presented, with the biophysical mechanisms and modalities of open-loop electrical stimulation, and the potential benefits of closed-loop control for epilepsy.

Summary: Purpose: Electric field stimulation can interact with brain activity in a subthreshold manner. Electric fields have been previously adaptively applied to control seizures in vitro. We report the first results from establishing suitable electrode geometries and trajectories, as well as stimulation and recording electronics, to apply this technology in vivo. Methods: Electric field stimulation was performed in a rat kainic acid injection seizure model. Radial electric fields were generated unilaterally in hippocampus from an axial depth electrode. Both sinusoidal and multiphasic stimuli were applied. Hippocampal activity was recorded bilaterally from tungsten microelectrode pairs. Histologic examination was performed to establish electrode trajectory and characterize lesioning. Results: Electric field modulation of epileptiform neural activity in phase with the stimulus was observed in five of six sinusoidal and six of six multiphasic waveform experiments. Both excitatory and suppressive modulation were observed in the two experiments with stimulation electrodes most centrally placed within the hippocampus. Distinctive modulation was observed in the period preceding seizure-onset detection in two of six experiments. Short-term histologic tissue damage was observed in one of six experiments associated with high unbalanced charge delivery. Conclusions: We demonstrated in vivo electric field modulation of epileptiform hippocampal activity, suggesting that electric field control of in vivo seizures may be technically feasible. The response to stimulation before seizure could be useful for triggering control systems, and may be a novel approach to define a preseizure state. Key Words: Electric field—Neural prosthesis—Seizure—Hippocampus— Preseizure state—Epilepsy. Although control system technology has made extraordinary advances during the past century, our efforts to apply sophisticated control strategies to epilepsy have been limited. Such limitations arise both from the lack of a flexible control parameter that would permit us to increase or decrease activity in the brain rapidly and reversibly, and the lack of stimulation and recording amplifiers designed for simultaneous monitoring of neuronal activity during control stimulation. Uninterrupted monitoring would allow a control system to use ongoing information about the dynamics to prescribe the control perturbations as continuous feedback. The application of continuous feedback would allow a controller to modify spe

Motivated by the observation that applied electric fields modulate hippocampal seizures, and that seizures may be asynchronous, we modeled synaptically coupled two-compartment hippocampal pyramidal neurons embedded within an electrically resistive lattice in order to examine network synchronization properties under the influence of externally applied electric fields. Excitatory electric fields were shown to synchronize or desynchronize the network depending on the natural frequency mismatch between the neurons. Such frequency mismatch was found to decrease as a function of increasing electric field amplitude. These findings provide testable hypotheses for future seizure control experiments.

We describe a novel method of adaptively controlling epileptic seizure-like events in hippocampal brain slices using electric fields. Extracellular neuronal activity is continuously recorded during field application through differential extracellular recording techniques, and the applied electric field strength is continuously updated using a computer-controlled proportional feedback algorithm. This approach appears capable of sustained amelioration of seizure events in this preparation when used with negative feedback. Seizures can be induced or enhanced by using fields of opposite polarity through positive feedback. In negative feedback mode, such findings may offer a novel technology for seizure control. In positive feedback mode, adaptively applied electric fields may offer a more physiological means of neural modulation for prosthetic purposes than previously possible.

Epilepsy is a dynamical disease - symptoms are produced by aberrant dynamics of neuronal networks. Although numerous attempts have been made to suppress epileptic seizures in human patients by stimulating sites remote from the epileptic focus, the efficacy of doing this without taking the dynamics of the seizures into account have been unimpressive.

Neural activity can be modulated by applying a polarizing low-frequency (100 Hz) electric field (PLEF). Unlike conventional pulsed stimulation, PLEF stimulation has a graded, modulatory effect on neuronal excitability, and permits the simultaneous recording of neuronal activity during stimulation suitable for continuous feedback control. We tested a prototype system that allows for simultaneous PLEF stimulation with minimal recording artifact in a chronic tetanus toxin animal model (rat) of hippocampal epilepsy with spontaneous seizures. Depth electrode local field potentials recorded during seizures revealed a characteristic pattern of field postsynaptic potentials (fPSPs). Sinusoidal voltage-controlled PLEF stimulation (0.5–25 Hz) was applied in open-loop cycles radially across the CA3 of ventral hippocampus. For stimulated seizures, fPSPs were transiently entrained with the PLEF waveform. Statistical significance of entrainment was assessed with Thomson's harmonic F-test, with 45/132 stimulated seizures in four animals individually demonstrating significant entrainment (p < 0.04). Significant entrainment for multiple presentations at the same frequency (p < 0.01) was observed in three of four animals in 42/64 stimulated seizures. This is the first demonstration in chronically implanted freely behaving animals of PLEF modulation of neural activity with simultaneous recording.

Low Frequency (≪100Hz) applied electric fields have been shown to modulate neuronal activity both In Vitro and in acute whole animal studies [1–3]. We have been working to apply this technology for seizure control in chronically implanted animals. We have developed electronics for simultaneously recording neural activity while stimulating with low frequency fields. We have observed transient entrainment of spike and wave activity during spontaneous seizures with open loop sinusoidal stimulation with frequencies between 9–15 Hz. This is the first demonstration of low frequency field modulation of neural activity in chronically implanted mammalian brain.

Earlier work [1] applied chaos control algorithms to modulate the timing of neuronal population burst events with the idea that changing such interictal dynamic could be used to prevent seizures. This work utilized classical neurophysiological stimulation techniques, specifically pulse‐like current injections, which were limited to exciting new burst events. Building on this work, we have shown that a broadly applied electric field can be used as a more versatile control parameter for interacting with neuronal neurons, able to proportionately excite or suppress average neuronal excitability of large groups of neurons. I’ll discuss both the physics underlying the electric field interaction with neurons, and our recent work [2] interacting with and controlling seizure activity in live neuronal networks.

Stochastic resonance, a nonlinear phenomenon in which random noise optimizes a system’s response to a signal, has been postulated to provide a role for noise in information processing in the brain. In these experiments, a time varying electric field was used to deliver both signal and noise directly to a network of neurons from mammalian brain. As the magnitude of the stochastic component of the field was increased, resonance was observed in the response of the neuronal network to a weak periodic signal. This is the first demonstration of stochastic resonance in neuronal networks from the brain. [S0031-9007(96)01583-9]