Hippocampal ripples coincide with "up-state" and spindles in retrosplenial cortex.

During NREM sleep, hippocampal sharp-wave ripple (SWR) events are thought to stabilize memory traces for long-term storage in downstream neocortical structures. Within the neocortex, a set of distributed networks organized around retrosplenial cortex (RS-network) interact preferentially with the hippocampus purportedly to consolidate those traces. Transient bouts of slow oscillations and sleep spindles in this RS-network are often observed around SWRs, suggesting that these two activities are related and that their interplay possibly contributes to memory consolidation. To investigate how SWRs interact with the RS-network and spindles, we combined cortical wide-field voltage imaging, Electrocorticography, and hippocampal LFP recordings in anesthetized and sleeping mice. Here, we show that, during SWR, "up-states" and spindles reliably co-occur in a cortical subnetwork centered around the retrosplenial cortex. Furthermore, retrosplenial transient activations and spindles predict slow gamma oscillations in CA1 during SWRs. Together, our results suggest that retrosplenial-hippocampal interaction may be a critical pathway of information exchange between the cortex and hippocampus.

Perturbed Information Processing Complexity in Experimental Epilepsy.

Comorbidities, such as cognitive deficits, which often accompany epilepsies, constitute a basal state, while seizures are rare and transient events. This suggests that neural dynamics, in particular those supporting cognitive function, are altered in a permanent manner in epilepsy. Here, we test the hypothesis that primitive processes of information processing at the core of cognitive function (i.e., storage and sharing of information) are altered in the hippocampus and the entorhinal cortex in experimental epilepsy in adult, male Wistar rats. We find that information storage and sharing are organized into substates across the stereotypic states of slow and theta oscillations in both epilepsy and control conditions. However, their internal composition and organization through time are disrupted in epilepsy, partially losing brain state selectivity compared with controls, and shifting toward a regimen of disorder. We propose that the alteration of information processing at this algorithmic level of computation, the theoretical intermediate level between structure and function, may be a mechanism behind the emergent and widespread comorbidities associated with epilepsy, and perhaps other disorders.SIGNIFICANCE STATEMENT Comorbidities, such as cognitive deficits, which often accompany epilepsies, constitute a basal state, while seizures are rare and transient events. This suggests that neural dynamics, in particular those supporting cognitive function, are altered in a permanent manner in epilepsy. Here, we show that basic processes of information processing at the core of cognitive function (i.e., storage and sharing of information) are altered in the hippocampus and the entorhinal cortex (two regions involved in memory processes) in experimental epilepsy. Such disruption of information processing at the algorithmic level itself could underlie the general performance impairments in epilepsy.

Impact of the day/night cycle on functional connectome in ageing male and female mice.

To elucidate how time of day, sex, and age affect functional connectivity (FC) in mice, we aimed to examine whether the mouse functional connectome varied with the day/night cycle and whether it depended on sex and age. We explored C57Bl6/J mice (6♀ and 6♂) at mature age (5 ± 1 months) and middle-age (14 ± 1 months). Each mouse underwent Blood Oxygen-Level-Dependent (BOLD) resting-state functional MRI (rs-fMRI) on a 7T scanner at four different times of the day, two under the light condition and two under the dark condition. Data processing consisted of group independent component analysis (ICA) and region-level analysis using resting-state networks (RSNs) derived from literature. Linear mixed-effect models (LMEM) were used to assess the effects of sex, lighting condition and their interactions for each RSN obtained with group-ICA (RSNs-GICA) and six bilateral RSNs adapted from literature (RSNs-LIT). Our study highlighted new RSNs in mice related to day/night alternation in addition to other networks already reported in the literature. In mature mice, we found sex-related differences in brain activation only in one RSNs-GICA comprising the cortical, hippocampal, midbrain and cerebellar regions of the right hemisphere. In males, brain activity was significantly higher in the left hippocampus, the retrosplenial cortex, the superior colliculus, and the cerebellum regardless of lighting condition; consistent with the role of these structures in memory formation and integration, sleep, and sex-differences in memory processing. Experimental constraints limited the analysis to the impact of light/dark cycle on the RSNs for middle-aged females. We detected significant activation in the pineal gland during the dark condition, a finding in line with the nocturnal activity of this gland. For the analysis of RSNs-LIT, new variables "sexage" (sex and age combined) and "edges" (pairs of RSNs) were introduced. FC was calculated as the Pearson correlation between two RSNs. LMEM revealed no effect of sexage or lighting condition. The FC depended on the edges, but there were no interaction effects between sexage, lighting condition and edges. Interaction effects were detected between i) sex and lighting condition, with higher FC in males under the dark condition, ii) sexage and edges with higher FC in male brain regions related to vision, memory, and motor action. We conclude that time of day and sex should be taken into account when designing, analyzing, and interpreting functional imaging studies in rodents.

Spatio-temporal heterogeneity in hippocampal metabolism in control and epilepsy conditions.

The hippocampus's dorsal and ventral parts are involved in different operative circuits, the functions of which vary in time during the night and day cycle. These functions are altered in epilepsy. Since energy production is tailored to function, we hypothesized that energy production would be space- and time-dependent in the hippocampus and that such an organizing principle would be modified in epilepsy. Using metabolic imaging and metabolite sensing ex vivo, we show that the ventral hippocampus favors aerobic glycolysis over oxidative phosphorylation as compared to the dorsal part in the morning in control mice. In the afternoon, aerobic glycolysis is decreased and oxidative phosphorylation increased. In the dorsal hippocampus, the metabolic activity varies less between these two times but is weaker than in the ventral. Thus, the energy metabolism is different along the dorsoventral axis and changes as a function of time in control mice. In an experimental model of epilepsy, we find a large alteration of such spatiotemporal organization. In addition to a general hypometabolic state, the dorsoventral difference disappears in the morning, when seizure probability is low. In the afternoon, when seizure probability is high, the aerobic glycolysis is enhanced in both parts, the increase being stronger in the ventral area. We suggest that energy metabolism is tailored to the functions performed by brain networks, which vary over time. In pathological conditions, the alterations of these general rules may contribute to network dysfunctions.

From phenomenological to biophysical models of seizures.

Epilepsy is a complex disease that requires various approaches for its study. This short review discusses the contribution of theoretical and computational models. The review presents theoretical frameworks that underlie the understanding of certain seizure properties and their classification based on their dynamical properties at the onset and offset of seizures. Dynamical system tools are valuable resources in the study of seizures. These tools can provide insights into seizure mechanisms and offer a framework for their classification, by analyzing the complex, dynamic behavior of seizures. Additionally, computational models have high potential for clinical applications, as they can be used to develop more accurate diagnostic and personalized medicine tools. We discuss various modeling approaches that span different scales and levels, while also questioning the neurocentric view, emphasizing the importance of considering glial cells. Finally, we explore the epistemic value provided by this type of approach.

Sleep, oscillations, and epilepsy.

Sleep and wake are defined through physiological and behavioral criteria and can be typically separated into non-rapid eye movement (NREM) sleep stages N1, N2, and N3, rapid eye movement (REM) sleep, and wake. Sleep and wake states are not homogenous in time. Their properties vary during the night and day cycle. Given that brain activity changes as a function of NREM, REM, and wake during the night and day cycle, are seizures more likely to occur during NREM, REM, or wake at a specific time? More generally, what is the relationship between sleep-wake cycles and epilepsy? We will review specific examples from clinical data and results from experimental models, focusing on the diversity and heterogeneity of these relationships. We will use a top-down approach, starting with the general architecture of sleep, followed by oscillatory activities, and ending with ionic correlates selected for illustrative purposes, with respect to seizures and interictal spikes. The picture that emerges is that of complexity; sleep disruption and pathological epileptic activities emerge from reorganized circuits. That different circuit alterations can occur across patients and models may explain why sleep alterations and the timing of seizures during the sleep-wake cycle are patient-specific.

Can in vitro studies aid in the development and use of antiseizure therapies? A report of the ILAE/AES Joint Translational Task Force.

In vitro preparations (defined here as cultured cells, brain slices, and isolated whole brains) offer a variety of approaches to modeling various aspects of seizures and epilepsy. Such models are particularly amenable to the application of anti-seizure compounds, and consequently are a valuable tool to screen the mechanisms of epileptiform activity, mode of action of known anti-seizure medications (ASMs), and the potential efficacy of putative new anti-seizure compounds. Despite these applications, all disease models are a simplification of reality and are therefore subject to limitations. In this review, we summarize the main types of in vitro models that can be used in epilepsy research, describing key methodologies as well as notable advantages and disadvantages of each. We argue that a well-designed battery of in vitro models can form an effective and potentially high-throughput screening platform to predict the clinical usefulness of ASMs, and that in vitro models are particularly useful for interrogating mechanisms of ASMs. To conclude, we offer several key recommendations that maximize the potential value of in vitro models in ASM screening. This includes the use of multiple in vitro tests that can complement each other, carefully combined with in vivo studies, the use of tissues from chronically epileptic (rather than naïve wild-type) animals, and the integration of human cell/tissue-derived preparations.

Personalized whole brain modeling of status epilepticus.

How status epilepticus (SE) is generated and propagates in the brain is not known. As for seizures, a patient-specific approach is necessary, and the analysis should be performed at the whole brain level. Personalized brain models can be used to study seizure genesis and propagation at the whole brain scale in The Virtual Brain (TVB), using the Epileptor mathematical construct. Building on the fact that SE is part of the repertoire of activities that the Epileptor can generate, we present the first attempt to model SE at the whole brain scale in TVB, using data from a patient who experienced SE during presurgical evaluation. Simulations reproduced the patterns found with SEEG recordings. We find that if, as expected, the pattern of SE propagation correlates with the properties of the patient's structural connectome, SE propagation also depends upon the global state of the network, i.e., that SE propagation is an emergent property. We conclude that individual brain virtualization can be used to study SE genesis and propagation. This type of theoretical approach may be used to design novel interventional approaches to stop SE. This paper was presented at the 8th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures held in September 2022.

A unified physiological framework of transitions between seizures, sustained ictal activity and depolarization block at the single neuron level.

The majority of seizures recorded in humans and experimental animal models can be described by a generic phenomenological mathematical model, the Epileptor. In this model, seizure-like events (SLEs) are driven by a slow variable and occur via saddle node (SN) and homoclinic bifurcations at seizure onset and offset, respectively. Here we investigated SLEs at the single cell level using a biophysically relevant neuron model including a slow/fast system of four equations. The two equations for the slow subsystem describe ion concentration variations and the two equations of the fast subsystem delineate the electrophysiological activities of the neuron. Using extracellular K+ as a slow variable, we report that SLEs with SN/homoclinic bifurcations can readily occur at the single cell level when extracellular K+ reaches a critical value. In patients and experimental models, seizures can also evolve into sustained ictal activity (SIA) and depolarization block (DB), activities which are also parts of the dynamic repertoire of the Epileptor. Increasing extracellular concentration of K+ in the model to values found during experimental status epilepticus and DB, we show that SIA and DB can also occur at the single cell level. Thus, seizures, SIA, and DB, which have been first identified as network events, can exist in a unified framework of a biophysical model at the single neuron level and exhibit similar dynamics as observed in the Epileptor.Author Summary: Epilepsy is a neurological disorder characterized by the occurrence of seizures. Seizures have been characterized in patients in experimental models at both macroscopic and microscopic scales using electrophysiological recordings. Experimental works allowed the establishment of a detailed taxonomy of seizures, which can be described by mathematical models. We can distinguish two main types of models. Phenomenological (generic) models have few parameters and variables and permit detailed dynamical studies often capturing a majority of activities observed in experimental conditions. But they also have abstract parameters, making biological interpretation difficult. Biophysical models, on the other hand, use a large number of variables and parameters due to the complexity of the biological systems they represent. Because of the multiplicity of solutions, it is difficult to extract general dynamical rules. In the present work, we integrate both approaches and reduce a detailed biophysical model to sufficiently low-dimensional equations, and thus maintaining the advantages of a generic model. We propose, at the single cell level, a unified framework of different pathological activities that are seizures, depolarization block, and sustained ictal activity.

Deficit in observational learning in experimental epilepsy.

Individuals use the observation of a conspecific to learn new behaviors and skills in many species. Whether observational learning is affected in epilepsy is not known. Using the pilocarpine rat model of epilepsy, we assessed learning by observation in a spatial task. The task involves a naive animal observing a demonstrator animal seeking a reward at a specific spatial location. After five observational sessions, the observer is allowed to explore the rewarded space and look for the reward. Although control observer rats succeed in finding the reward when allowed to explore the rewarded space, epileptic animals fail. However, epileptic animals are able to successfully learn the location of the reward through their own experience after several trial sessions. Thus, epileptic animals show a clear deficit in learning by observation. This result may be clinically relevant, in particular in children who strongly rely on observational learning.

Individual structural features constrain the mouse functional connectome.

Whole brain dynamics intuitively depend upon the internal wiring of the brain; but to which extent the individual structural connectome constrains the corresponding functional connectome is unknown, even though its importance is uncontested. After acquiring structural data from individual mice, we virtualized their brain networks and simulated in silico functional MRI data. Theoretical results were validated against empirical awake functional MRI data obtained from the same mice. We demonstrate that individual structural connectomes predict the functional organization of individual brains. Using a virtual mouse brain derived from the Allen Mouse Brain Connectivity Atlas, we further show that the dominant predictors of individual structure-function relations are the asymmetry and the weights of the structural links. Model predictions were validated experimentally using tracer injections, identifying which missing connections (not measurable with diffusion MRI) are important for whole brain dynamics in the mouse. Individual variations thus define a specific structural fingerprint with direct impact upon the functional organization of individual brains, a key feature for personalized medicine.

Spread Spectrum Modulation with Grassmannian Constellations for Mobile Multiple Access Underwater Acoustic Channels.

The objective of this study is to evaluate Grassmannian constellations combined with a spread spectrum multiple access scheme for underwater acoustic mobile multiple access communication systems. These communication systems enable the coordination of a fleet of Autonomous Underwater Vehicles (AUVs) from a surface or bottom control unit, e.g., a boat. Due to its robustness against phase rotation, the demodulator of Grassmannian constellations uses non-coherent detection, and the main advantage of such modulation lies in the spectrum efficiency gain with respect to conventional differential modulation. The communication system under study in this paper consists of (i), at the transmitter side, a Grassmannian modulation used in an orthogonal spread spectrum multiple access scheme called Multiuser Hyperbolic Frequency Modulation (MU-HFM) and (ii), at the receiver side, a non-coherent array decoder. The modulation and demodulation are presented as well as the considered spreading sequences. Finally, performances of the proposed transmission scheme are evaluated over replayed underwater acoustic channel responses collected at sea by a multi-sensor acoustic acquisition system.

Cell Assemblies in the Cortico-Hippocampal-Reuniens Network during Slow Oscillations.

The nucleus reuniens (NR) is an important anatomic and functional relay between the medial prefrontal cortex (mPFC) and the hippocampus (HPC). Whether the NR controls neuronal assemblies, a hallmark of information exchange between the HPC and mPFC for memory transfer/consolidation, is not known. Using simultaneous local field potential and unit recordings in NR, HPC, and mPFC in male rats during slow oscillations under anesthesia, we identified a reliable sequential activation of NR neurons at the beginning of UP states, which preceded mPFC ones. NR sequences were spatially organized, from dorsal to ventral NR. Chemical inactivation of the NR disrupted mPFC sequences at the onset of UP states as well as HPC sequences present during sharp-wave ripples. We conclude that the NR contributes to the coordination and stabilization of mPFC and HPC neuronal sequences during slow oscillations, possibly via the early activation of its own sequences.SIGNIFICANCE STATEMENT Neuronal assemblies are believed to be instrumental to code/encode/store information. They can be recorded in different brain regions, suggesting that widely distributed networks of networks are involved in such information processing. The medial prefrontal cortex, the hippocampus, and the thalamic nucleus reuniens constitute a typical example of a complex network involved in memory consolidation. In this study, we show that spatially organized cells assemblies are recruited in the nucleus reuniens at the UP state onset during slow oscillations. Nucleus reuniens activity appears to be necessary to the stability of medial prefrontal cortex and hippocampal cell assembly formation during slow oscillations. This result further highlights the role of the nucleus reuniens as a functional hub for exchanging and processing memories.

Circadian/multidien Molecular Oscillations and Rhythmicity of Epilepsy (MORE).

The occurrence of seizures at specific times of the day has been consistently observed for centuries in individuals with epilepsy. Electrophysiological recordings provide evidence that seizures have a higher probability of occurring at a given time during the night and day cycle in individuals with epilepsy here referred to as the seizure rush hour. Which mechanisms underlie such circadian rhythmicity of seizures? Why don't they occur every day at the same time? Which mechanisms may underlie their occurrence outside the rush hour? In this commentary, I present a hypothesis: MORE - Molecular Oscillations and Rhythmicity of Epilepsy, a conceptual framework to study and understand the mechanisms underlying the circadian rhythmicity of seizures and their probabilistic nature. The core of the hypothesis is the existence of ~24-hour oscillations of gene and protein expression throughout the body in different cells and organs. The orchestrated molecular oscillations control the rhythmicity of numerous body events, such as feeding and sleep. The concept developed here is that molecular oscillations may favor seizure genesis at preferred times, generating the condition for a seizure rush hour. However, the condition is not sufficient, as other factors are necessary for a seizure to occur. Studying these molecular oscillations may help us understand seizure genesis mechanisms and find new therapeutic targets and predictive biomarkers. The MORE hypothesis can be generalized to comorbidities and the slower multidien (week/month period) rhythmicity of seizures, a phenomenon addressed in another article in this issue of Epilepsia.

Antiseizure effects of Anacyclus pyrethrum in socially isolated rats with and without a positive handling strategy.

OBJECTIVE: Aqueous extract of Anacyclus pyrethrum (AEAPR) is used in traditional medicine to treat epilepsy, but whether it has antiseizure properties has not been established. Because extracts of the plant have antioxidant properties, we hypothesized that it may be particularly potent in conditions associated with oxidative stress, in particular social isolation. METHODS: We addressed these objectives in the pilocarpine experimental model of epilepsy using socially isolated rats maintaining contacts with (handled) and without (unhandled) positive handling strategy. Both groups were further divided into treated (AEAPR was added to the drinking water) and untreated groups. Continuous (24/7) electroencephalography (EEG) recordings started in the sixth week after status epilepticus (SE) with a predrug control period of 3 weeks, followed by 3 weeks of daily treatment with AEAPR or water, and finally a postdrug control period of 3 weeks. At the end of the experimental procedure, we measured lipid peroxidation, superoxide dismutase (SOD), glutathione peroxidase (GPx), and catalase activities in the hippocampus to assess oxidative stress. RESULTS: A. pyrethrum treatment significantly reduced seizure frequency by 51% and 57%, duration by 30% and 33%, and severity by 31% and 26% in isolated handled and unhandled rats, respectively. The beneficial effects on seizures were still present 3 weeks after the end of the treatment. The treatment reduced lipid peroxidation as well as SOD, GPx, and catalase activities. SIGNIFICANCE: We conclude that A. pyrethrum has antiseizure and antioxidant properties, even in social isolation conditions.

Assessment of the Use of Multi-Channel Organic Electrodes to Record ENG on Small Nerves: Application to Phrenic Nerve Burst Detection.

Effective closed-loop neuromodulation relies on the acquisition of appropriate physiological control variables and the delivery of an appropriate stimulation signal. In particular, electroneurogram (ENG) data acquired from a set of electrodes applied at the surface of the nerve may be used as a potential control variable in this field. Improved electrode technologies and data processing methods are clearly needed in this context. In this work, we evaluated a new electrode technology based on multichannel organic electrodes (OE) and applied a signal processing chain in order to detect respiratory-related bursts from the phrenic nerve. Phrenic ENG (pENG) were acquired from nine Long Evans rats in situ preparations. For each preparation, a 16-channel OE was applied around the phrenic nerve's surface and a suction electrode was applied to the cut end of the same nerve. The former electrode provided input multivariate pENG signals while the latter electrode provided the gold standard for data analysis. Correlations between OE signals and that from the gold standard were estimated. Signal to noise ratio (SNR) and ROC curves were built to quantify phrenic bursts detection performance. Correlation score showed the ability of the OE to record high-quality pENG. Our methods allowed good phrenic bursts detection. However, we failed to demonstrate a spatial selectivity from the multiple pENG recorded with our OE matrix. Altogether, our results suggest that highly flexible and biocompatible multi-channel electrode may represent an interesting alternative to metallic cuff electrodes to perform nerve bursts detection and/or closed-loop neuromodulation.

Fur-Dam Regulatory Interplay at an Internal Promoter of the Enteroaggregative Escherichia coli Type VI Secretion sci1 Gene Cluster.

The type VI secretion system (T6SS) is a weapon for delivering effectors into target cells that is widespread in Gram-negative bacteria. The T6SS is a highly versatile machine, as it can target both eukaryotic and prokaryotic cells, and it has been proposed that T6SSs are adapted to the specific needs of each bacterium. The expression of T6SS gene clusters and the activation of the secretion apparatus are therefore tightly controlled. In enteroaggregative Escherichia coli (EAEC), the sci1 T6SS gene cluster is subject to a complex regulation involving both the ferric uptake regulator (Fur) and DNA adenine methylase (Dam)-dependent DNA methylation. In this study, an additional, internal, promoter was identified within the sci1 gene cluster using +1 transcriptional mapping. Further analyses demonstrated that this internal promoter is controlled by a mechanism strictly identical to that of the main promoter. The Fur binding box overlaps the -10 transcriptional element and a Dam methylation site, GATC-32. Hence, the expression of the distal sci1 genes is repressed and the GATC-32 site is protected from methylation in iron-rich conditions. The Fur-dependent protection of GATC-32 was confirmed by an in vitro methylation assay. In addition, the methylation of GATC-32 negatively impacted Fur binding. The expression of the sci1 internal promoter is therefore controlled by iron availability through Fur regulation, whereas Dam-dependent methylation maintains a stable ON expression in iron-limited conditions.IMPORTANCE Bacteria use weapons to deliver effectors into target cells. One of these weapons, the type VI secretion system (T6SS), assembles a contractile tail acting as a spring to propel a toxin-loaded needle. Its expression and activation therefore need to be tightly regulated. Here, we identified an internal promoter within the sci1 T6SS gene cluster in enteroaggregative E. coli We show that this internal promoter is controlled by Fur and Dam-dependent methylation. We further demonstrate that Fur and Dam compete at the -10 transcriptional element to finely tune the expression of T6SS genes. We propose that this elegant regulatory mechanism allows the optimum production of the T6SS in conditions where enteroaggregative E. coli encounters competing species.

Multiuser Chirp Spread Spectrum Transmission in an Underwater Acoustic Channel Applied to an AUV Fleet.

The objective of this paper is to provide a multiuser transmission technique for underwater acoustic communication in the framework of an Autonomous Underwater Vehicle (AUV) fleet. By using a variant of a Hyperbolically Frequency-Modulated (HFM) signal, we describe a new family of transmission techniques called MultiUser Chirp Spread Spectrum (MU-CSS), which allows a very simple matched-filter-based decoding. These techniques are expected to provide good resilience against multiuser interference while keeping good robustness to Underwater Acoustic (UWA) channel impairments like Doppler shift. Their implementation for the UWA scenario is described, and the performance results over a simulated shallow-water UWA channel are analyzed and compared against conventional Code-Division Multiple Access (CDMA) and Time-Division Multiple Access (TDMA) transmission. Finally, the feasibility and robustness of the proposed methods are verified over the underWater AcousTic channEl Replay benchMARK (Watermark), fed by several channel responses from sounding experiments performed in a lake.

The Nucleus Reuniens Controls Long-Range Hippocampo-Prefrontal Gamma Synchronization during Slow Oscillations.

Gamma oscillations are involved in long-range coupling of distant regions that support various cognitive operations. Here we show in adult male rats that synchronized bursts of gamma oscillations bind the hippocampus (HPC) and prefrontal cortex (mPFC) during slow oscillations and slow-wave sleep, a brain state that is central for consolidation of memory traces. These gamma bursts entrained the firing of the local HPC and mPFC neuronal populations. Neurons of the nucleus reuniens (NR), which is a structural and functional hub between HPC and mPFC, demonstrated a specific increase in their firing before gamma burst onset, suggesting their involvement in HPC-mPFC binding. Chemical inactivation of NR disrupted the temporal pattern of gamma bursts and their synchronization, as well as mPFC neuronal firing. We propose that the NR drives long-range hippocampo-prefrontal coupling via gamma bursts providing temporal windows for information exchange between the HPC and mPFC during slow-wave sleep.SIGNIFICANCE STATEMENT Long-range coupling between hippocampus (HPC) and prefrontal cortex (mPFC) is believed to support numerous cognitive functions, including memory consolidation occurring during sleep. Gamma-band synchronization is a fundamental process in many neuronal operations and is instrumental in long-range coupling. Recent evidence highlights the role of nucleus reuniens (NR) in consolidation; however, how it influences hippocampo-prefrontal coupling is unknown. In this study, we show that HPC and mPFC are synchronized by gamma bursts during slow oscillations in anesthesia and natural sleep. By manipulating and recording the NR-HPC-mPFC network, we provide evidence that the NR actively promotes this long-range gamma coupling. This coupling provides the hippocampo-prefrontal circuit with a novel mechanism to exchange information during slow-wave sleep.

Antioxidant treatment after epileptogenesis onset prevents comorbidities in rats sensitized by a past stressful event.

OBJECTIVE: Unresolved past stressful events can induce a state of vulnerability to epilepsy and comorbidities. Using an experimental model of stress-induced vulnerability to depression, we tested whether an antioxidant treatment applied after the onset of epileptogenesis was disease modifying and could prevent the occurrence of comorbidities. METHODS: We used social defeat (SD) to trigger a state of vulnerability in half of the SD-exposed population of rats. One month after SD, we used repeated injections of kainic acid to trigger status epilepticus (SE). One subset of animals was treated after SE during 2 weeks with Tempol, a strong antioxidant. Supradural 24/7 recordings were used to assess the development of epilepsy. We assessed spatial and nonspatial memory as well as a depressionlike profile 6 weeks after SE. RESULTS: Serum brain-derived neurotrophic factor (BDNF) levels decreased after SD in all animals and recovered to pre-SD levels 1 month later in half of them (SDN group). The other half kept low serum BDNF levels (SDL group). At that stage, SDN and SDL animals do not present a depressionlike profile. The SDL group was more sensitive than the SDN group to epileptogenic conditions. Following SE, the SDL group displayed accelerated epileptogenesis, a depressionlike profile, and severe cognitive deficits as compared to SDN rats. Transient Tempol treatment was disease-modifying, reducing the number of seizures, and prevented the development of comorbidities in the SDL group. Tempol treatment normalized oxidative stress in the SDL group to SDN levels. SIGNIFICANCE: This study illustrates the disease-modifying effect of antioxidant treatment after the onset of epileptogenesis in a population rendered vulnerable by past stressful events. The transient treatment decreased seizure burden and had long-term effects, preventing the occurrence of a depressionlike profile and cognitive deficits. We propose that vulnerability to comorbidities can be reversed after the onset of epilepsy.