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Excitatory GABAergic signalling is associated with acquired benzodiazepine resistance in status epilepticus
Status epilepticus (SE) is defined as a state of unrelenting seizure activity. Generalised convulsive SE is associated with a rapidly rising mortality rate, and thus constitutes a medical emergency. Benzodiazepines, which act as positive modulators of chloride (Cl - ) permeable GABA A receptors, are indicated as first-line treatment, but this is ineffective in many cases. We found that 48% of children presenting with SE were unresponsive to benzodiazepine treatment, and critically, that the duration of SE at the time of treatment is an important predictor of non-responsiveness. We therefore investigated the cellular mechanisms that underlie acquired benzodiazepine resistance, using rodent organotypic and acute brain slices. Removing Mg 2+ ions leads to an evolving pattern of epileptiform activity, and eventually to a persistent state of repetitive discharges that strongly resembles clinical EEG recordings of SE. We found that diazepam loses its antiseizure efficacy and conversely exacerbates epileptiform activity during this stage of SE-like activity. Interestingly, a low concentration of the barbiturate phenobarbital had a similar exacerbating effect on SE-like activity, whilst a high concentration of phenobarbital was effective at reducing or preventing epileptiform discharges. We then show that the persistent SE-like activity is associated with a reduction in GABA A receptor conductance and Cl - extrusion capability. We explored the effect on intraneuronal Cl - using both gramicidin, perforated-patch clamp recordings and Cl - imaging. This showed that during SE-like activity, reduced Cl - extrusion capacity was further exacerbated by activity-dependent Cl - loading, resulting in a persistently high intraneuronal Cl - . Consistent with these results, we found that optogenetic stimulation of GABAergic interneurons in the SE-like state, actually enhanced epileptiform activity in a GABA A R dependent manner. Together our findings describe a novel potential mechanism underlying benzodiazepine-resistant SE, with relevance to how this life-threatening condition should be managed in the clinic.
Disrupting Epileptiform Activity by Preventing Parvalbumin Interneuron Depolarization Block.
Inhibitory synaptic mechanisms oppose epileptic network activity in the brain. The breakdown in this inhibitory restraint and propagation of seizure activity has been linked to the overwhelming of feedforward inhibition, which is provided in large part by parvalbumin-expressing (PV) interneurons in the cortex. The underlying cellular processes therefore represent potential targets for understanding and preventing the propagation of seizure activity. Here we use an optogenetic strategy to test the hypothesis that depolarization block in PV interneurons is a significant factor during the loss of inhibitory restraint. Depolarization block results from the inactivation of voltage-gated sodium channels and leads to impaired action potential firing. We used focal NMDA stimulation to elicit reproducible epileptiform discharges in hippocampal organotypic brain slices from male and female mice and combined this with targeted recordings from defined neuronal populations. Simultaneous patch-clamp recordings from PV interneurons and pyramidal neurons revealed epileptiform activity that was associated with an overwhelming of inhibitory synaptic mechanisms and the emergence of a partial, and then complete, depolarization block in PV interneurons. To counteract this depolarization block, we developed protocols for eliciting pulsed membrane hyperpolarization via the inhibitory opsin, archaerhodopsin. This optical approach was effective in counteracting cumulative inactivation of voltage-gated channels, maintaining PV interneuron action potential firing properties during the inhibitory restraint period, and reducing the probability of initiating epileptiform activity. These experiments support the idea that depolarization block is a point of weakness in feedforward inhibitory synaptic mechanisms and represents a target for preventing the initiation and spread of seizure activity.SIGNIFICANCE STATEMENT GABAA receptor-mediated synaptic transmission opposes seizure activity by establishing an inhibitory restraint against spreading excitation. Parvalbumin-expressing (PV) interneurons contribute significantly to this inhibitory restraint, but it has been suggested that these cells are overwhelmed as they enter a state of "depolarization block." Here we test the importance of this process by devising an optogenetic strategy to selectively relieve depolarization block in PV interneurons. By inducing brief membrane hyperpolarization, we show that it is possible to reduce depolarization block in PV interneurons, maintain their action potential firing in the face of strong excitation, and disrupt epileptiform activity in an in vitro model. This represents a proof of principle that targeting rate-limiting processes can strengthen the inhibitory restraint of epileptiform activity.
The transition to status epilepticus: how the brain meets the demands of perpetual seizure activity.
The pathophysiology leading to the development of status epilepticus (SE) remains a topic of significant scientific interest and clinical relevance. The use of multiple experimental and computational models has shown that SE relies on a complex interaction between mechanisms that operate at both a cellular and network level. In this narrative review, we will summarise the current knowledge on the factors that play a key role in allowing SE to develop and persist. These include pathological adaptations to changing ion dynamics, neuroenergetics, receptor expression and neurotransmission, which enable the brain to meet the extensive demands required to maintain ongoing synchronous hyperexcitability. We will examine how these processes converge to enable synapses to support seizure perpetuation. Lastly, we will use the concept of a perpetuating network to highlight how connections between brain regions can provide positive feedback loops that can serve to propagate seizure activity. We hope this review will collate the findings of previous research and help fuel further studies into the mechanisms that underlie how the brain can make the transition to SE.
Chloride dynamics alter the input-output properties of neurons.
Fast synaptic inhibition is a critical determinant of neuronal output, with subcellular targeting of synaptic inhibition able to exert different transformations of the neuronal input-output function. At the receptor level, synaptic inhibition is primarily mediated by chloride-permeable Type A GABA receptors. Consequently, dynamics in the neuronal chloride concentration can alter the functional properties of inhibitory synapses. How differences in the spatial targeting of inhibitory synapses interact with intracellular chloride dynamics to modulate the input-output function of neurons is not well understood. To address this, we developed computational models of multi-compartment neurons that incorporate experimentally parametrised mechanisms to account for neuronal chloride influx, diffusion, and extrusion. We found that synaptic input (either excitatory, inhibitory, or both) can lead to subcellular variations in chloride concentration, despite a uniform distribution of chloride extrusion mechanisms. Accounting for chloride changes resulted in substantial alterations in the neuronal input-output function. This was particularly the case for peripherally targeted dendritic inhibition where dynamic chloride compromised the ability of inhibition to offset neuronal input-output curves. Our simulations revealed that progressive changes in chloride concentration mean that the neuronal input-output function is not static but varies significantly as a function of the duration of synaptic drive. Finally, we found that the observed effects of dynamic chloride on neuronal output were mediated by changes in the dendritic reversal potential for GABA. Our findings provide a framework for understanding the computational effects of chloride dynamics on dendritically targeted synaptic inhibition.
Backpropagation and the brain.
During learning, the brain modifies synapses to improve behaviour. In the cortex, synapses are embedded within multilayered networks, making it difficult to determine the effect of an individual synaptic modification on the behaviour of the system. The backpropagation algorithm solves this problem in deep artificial neural networks, but historically it has been viewed as biologically problematic. Nonetheless, recent developments in neuroscience and the successes of artificial neural networks have reinvigorated interest in whether backpropagation offers insights for understanding learning in the cortex. The backpropagation algorithm learns quickly by computing synaptic updates using feedback connections to deliver error signals. Although feedback connections are ubiquitous in the cortex, it is difficult to see how they could deliver the error signals required by strict formulations of backpropagation. Here we build on past and recent developments to argue that feedback connections may instead induce neural activities whose differences can be used to locally approximate these signals and hence drive effective learning in deep networks in the brain.
Chemogenetic Recruitment of Specific Interneurons Suppresses Seizure Activity.
Current anti-epileptic medications that boost synaptic inhibition are effective in reducing several types of epileptic seizure activity. Nevertheless, these drugs can generate significant side-effects and even paradoxical responses due to the broad nature of their action. Recently developed chemogenetic techniques provide the opportunity to pharmacologically recruit endogenous inhibitory mechanisms in a selective and circuit-specific manner. Here, we use chemogenetics to assess the potential of suppressing epileptiform activity by enhancing the synaptic output from three major interneuron populations in the rodent hippocampus: parvalbumin (PV), somatostatin (SST), and vasoactive intestinal peptide (VIP) expressing interneurons. To target different neuronal populations, promoter-specific cre-recombinase mice were combined with viral-mediated delivery of chemogenetic constructs. Targeted electrophysiological recordings were then conducted in an in vitro model of chronic, drug-resistant epilepsy. In addition, behavioral video-scoring was performed in an in vivo model of acutely triggered seizure activity. Pre-synaptic and post-synaptic whole cell recordings in brain slices revealed that each of the three interneuron types increase their firing rate and synaptic output following chemogenetic activation. However, the interneuron populations exhibited different effects on epileptiform discharges. Recruiting VIP interneurons did not change the total duration of epileptiform discharges. In contrast, recruiting SST or PV interneurons produced robust suppression of epileptiform synchronization. PV interneurons exhibited the strongest effect per cell, eliciting at least a fivefold greater reduction in epileptiform activity than the other cell types. Consistent with this, we found that in vivo chemogenetic recruitment of PV interneurons suppressed convulsive behaviors by more than 80%. Our findings support the idea that selective chemogenetic enhancement of inhibitory synaptic pathways offers potential as an anti-seizure strategy.
Chemicogenetic recruitment of specific interneurons suppresses seizure activity
Enhancing the brain’s endogenous inhibitory mechanisms represents an important strategy for suppressing epileptic discharges. Indeed, drugs that boost synaptic inhibition can disrupt epileptic seizure activity, although these drugs generate complex effects due to the broad nature of their action. Recently developed chemicogenetic techniques provide the opportunity to pharmacologically enhance endogenous inhibitory mechanisms in a more selective manner. Here we use chemicogenetics to assess the anti-epileptic potential of enhancing the synaptic output from three major interneuron populations in the hippocampus: parvalbumin (PV), somatostatin (SST) and vasoactive intestinal peptide (VIP) expressing interneurons. Targeted pre- and post-synaptic whole cell recordings in an in vitro hippocampal mouse model revealed that all three interneuron types increase their firing rate and synaptic output following chemicogenetic activation. However, the interneuron populations exhibited different anti-epileptic effects. Recruiting VIP interneurons resulted in a mixture of pro-epileptic and anti-epileptic effects. In contrast, recruiting SST or PV interneurons produced robust suppression of epileptiform activity. PV interneurons exhibited the strongest effect per cell, eliciting at least a five-fold greater reduction in epileptiform activity than the other cell types. Consistent with this, we found that chemicogenetic recruitment of PV interneurons was effective in an in vivo mouse model of hippocampal seizures. Following efficient delivery of the chemicogenetic tool, pharmacological enhancement of the PV interneuron population suppressed a range of seizure-related behaviours and prevented generalized seizures. Our findings therefore support the idea that selective chemicogenetic enhancement of synaptic inhibitory pathways offers potential as an anti-epileptic strategy. Significance statement Drugs that enhance synaptic inhibition can be effective anticonvulsants but often cause complex effects due to their widespread action. Here we examined the anti-epileptic potential of recently developed chemicogenetic techniques, which offer a way to selectively enhance the synaptic output of distinct types of inhibitory neurons. A combination of in vitro and in vivo experimental models were used to investigate seizure activity in the mouse hippocampus. We find that chemicogenetically recruiting the parvalbumin-expressing population of inhibitory neurons produces the strongest anti-epileptic effect per cell, and that recruiting this cell population can suppress a range of epileptic behaviours in vivo. The data therefore support the idea that targeted chemicogenetic enhancement of synaptic inhibition offers promise for developing new treatments.
Biophysical models reveal the relative importance of transporter proteins and impermeant anions in chloride homeostasis.
Fast synaptic inhibition in the nervous system depends on the transmembrane flux of Cl- ions based on the neuronal Cl- driving force. Established theories regarding the determinants of Cl- driving force have recently been questioned. Here, we present biophysical models of Cl- homeostasis using the pump-leak model. Using numerical and novel analytic solutions, we demonstrate that the Na+/K+-ATPase, ion conductances, impermeant anions, electrodiffusion, water fluxes and cation-chloride cotransporters (CCCs) play roles in setting the Cl- driving force. Our models, together with experimental validation, show that while impermeant anions can contribute to setting [Cl-]i in neurons, they have a negligible effect on the driving force for Cl- locally and cell-wide. In contrast, we demonstrate that CCCs are well-suited for modulating Cl- driving force and hence inhibitory signaling in neurons. Our findings reconcile recent experimental findings and provide a framework for understanding the interplay of different chloride regulatory processes in neurons.
Reproducibility of Molecular Phenotypes after Long-Term Differentiation to Human iPSC-Derived Neurons: A Multi-Site Omics Study.
Reproducibility in molecular and cellular studies is fundamental to scientific discovery. To establish the reproducibility of a well-defined long-term neuronal differentiation protocol, we repeated the cellular and molecular comparison of the same two iPSC lines across five distinct laboratories. Despite uncovering acceptable variability within individual laboratories, we detect poor cross-site reproducibility of the differential gene expression signature between these two lines. Factor analysis identifies the laboratory as the largest source of variation along with several variation-inflating confounders such as passaging effects and progenitor storage. Single-cell transcriptomics shows substantial cellular heterogeneity underlying inter-laboratory variability and being responsible for biases in differential gene expression inference. Factor analysis-based normalization of the combined dataset can remove the nuisance technical effects, enabling the execution of robust hypothesis-generating studies. Our study shows that multi-center collaborations can expose systematic biases and identify critical factors to be standardized when publishing novel protocols, contributing to increased cross-site reproducibility.
Why won't it stop? The dynamics of benzodiazepine resistance in status epilepticus.
Status epilepticus is a life-threatening neurological emergency that affects both adults and children. Approximately 36% of episodes of status epilepticus do not respond to the current preferred first-line treatment, benzodiazepines. The proportion of episodes that are refractory to benzodiazepines is higher in low-income and middle-income countries (LMICs) than in high-income countries (HICs). Evidence suggests that longer episodes of status epilepticus alter brain physiology, thereby contributing to the emergence of benzodiazepine resistance. Such changes include alterations in GABAA receptor function and in the transmembrane gradient for chloride, both of which erode the ability of benzodiazepines to enhance inhibitory synaptic signalling. Often, current management guidelines for status epilepticus do not account for these duration-related changes in pathophysiology, which might differentially impact individuals in LMICs, where the average time taken to reach medical attention is longer than in HICs. In this Perspective article, we aim to combine clinical insights and the latest evidence from basic science to inspire a new, context-specific approach to efficiently managing status epilepticus.
Somnotate: A probabilistic sleep stage classifier for studying vigilance state transitions
Electrophysiological recordings from freely behaving animals are a widespread and powerful mode of investigation in sleep research. These recordings generate large amounts of data that require sleep stage annotation (polysomnography), in which the data is parcellated according to three vigilance states: awake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep. Manual and computational annotation methods currently ignore intermediate states because the classification features become ambiguous. However, these intermediate states contain important information regarding vigilance state dynamics. Here, we present a new classifier, “Somnotate”, which produces automated annotation accuracies that exceed human expert performance on mouse electrophysiological data, is robust to errors in the training data, compatible with different recording configurations, and maintains high performance during experimental interventions. Somnotate is a probabilistic classifier based on a combination of linear discriminant analysis (LDA) with a hidden Markov model (HMM). A unique feature of Somnotate is that it quantifies and reports the certainty of its annotations, enabling the experimenter to identify ambiguous recording periods in a principled manner. We leverage this feature to identify epochs that exhibit intermediate vigilance states, revealing that many of these cluster around state transitions, whereas others correspond to failed attempts to transition. We show that the success rates of different transitions can be experimentally manipulated and explain previously observed sleep patterns. Somnotate can thus facilitate the study of sleep stage transitions and offers new insight into the mechanisms underlying sleep-wake dynamics. Author summary Typically, the three different vigilance states – awake, REM sleep, and non-REM sleep – exhibit distinct features that are readily recognised in electrophysiological recordings. However, particularly around vigilance state transitions, epochs often exhibit features from more than one state. These intermediate vigilance states pose challenges for existing manual and automated classification methods, and are hence often ignored. Here, we present ‘Somnotate’ - an open-source, highly accurate and robust sleep stage classifier, which supports research into intermediate states and sleep stage dynamics. Somnotate quantifies and reports the certainty of its annotations, enabling the experimenter to identify abnormal epochs in a principled manner. We use this feature to identify intermediate states and to detect unsuccessful attempts to switch between vigilance states. This provides new insights into the mechanisms of vigilance state transitions in mice, and creates new opportunities for future experiments.
Optogenetic silencing strategies differ in their effects on inhibitory synaptic transmission.
Optogenetic silencing using light-driven ion fluxes permits rapid and effective inhibition of neural activity. Using rodent hippocampal neurons, we found that silencing activity with a chloride pump can increase the probability of synaptically evoked spiking after photoactivation; this did not occur with a proton pump. This effect can be accounted for by changes to the GABA(A) receptor reversal potential and demonstrates an important difference between silencing strategies.
Excitatory effects of parvalbumin-expressing interneurons maintain hippocampal epileptiform activity via synchronous afterdischarges.
Epileptic seizures are characterized by periods of hypersynchronous, hyperexcitability within brain networks. Most seizures involve two stages: an initial tonic phase, followed by a longer clonic phase that is characterized by rhythmic bouts of synchronized network activity called afterdischarges (ADs). Here we investigate the cellular and network mechanisms underlying hippocampal ADs in an effort to understand how they maintain seizure activity. Using in vitro hippocampal slice models from rats and mice, we performed electrophysiological recordings from CA3 pyramidal neurons to monitor network activity and changes in GABAergic signaling during epileptiform activity. First, we show that the highest synchrony occurs during clonic ADs, consistent with the idea that specific circuit dynamics underlie this phase of the epileptiform activity. We then show that ADs require intact GABAergic synaptic transmission, which becomes excitatory as a result of a transient collapse in the chloride (Cl(-)) reversal potential. The depolarizing effects of GABA are strongest at the soma of pyramidal neurons, which implicates somatic-targeting interneurons in AD activity. To test this, we used optogenetic techniques to selectively control the activity of somatic-targeting parvalbumin-expressing (PV(+)) interneurons. Channelrhodopsin-2-mediated activation of PV(+) interneurons during the clonic phase generated excitatory GABAergic responses in pyramidal neurons, which were sufficient to elicit and entrain synchronous AD activity across the network. Finally, archaerhodopsin-mediated selective silencing of PV(+) interneurons reduced the occurrence of ADs during the clonic phase. Therefore, we propose that activity-dependent Cl(-) accumulation subverts the actions of PV(+) interneurons to perpetuate rather than terminate pathological network hyperexcitability during the clonic phase of seizures.
Tight Coupling of Astrocyte pH Dynamics to Epileptiform Activity Revealed by Genetically Encoded pH Sensors.
UNLABELLED: Astrocytes can both sense and shape the evolution of neuronal network activity and are known to possess unique ion regulatory mechanisms. Here we explore the relationship between astrocytic intracellular pH dynamics and the synchronous network activity that occurs during seizure-like activity. By combining confocal and two-photon imaging of genetically encoded pH reporters with simultaneous electrophysiological recordings, we perform pH measurements in defined cell populations and relate these to ongoing network activity. This approach reveals marked differences in the intracellular pH dynamics between hippocampal astrocytes and neighboring pyramidal neurons in rodent in vitro models of epilepsy. With three different genetically encoded pH reporters, astrocytes are observed to alkalinize during epileptiform activity, whereas neurons are observed to acidify. In addition to the direction of pH change, the kinetics of epileptiform-associated intracellular pH transients are found to differ between the two cell types, with astrocytes displaying significantly more rapid changes in pH. The astrocytic alkalinization is shown to be highly correlated with astrocytic membrane potential changes during seizure-like events and mediated by an electrogenic Na(+)/HCO3 (-) cotransporter. Finally, comparisons across different cell-pair combinations reveal that astrocytic pH dynamics are more closely related to network activity than are neuronal pH dynamics. This work demonstrates that astrocytes exhibit distinct pH dynamics during periods of epileptiform activity, which has relevance to multiple processes including neurometabolic coupling and the control of network excitability. SIGNIFICANCE STATEMENT: Dynamic changes in intracellular ion concentrations are central to the initiation and progression of epileptic seizures. However, it is not known how changes in intracellular H(+) concentration (ie, pH) differ between different cell types during seizures. Using recently developed pH-sensitive proteins, we demonstrate that astrocytes undergo rapid alkalinization during periods of seizure-like activity, which is in stark contrast to the acidification that occurs in neighboring neurons. Rapid astrocytic pH changes are highly temporally correlated with seizure activity, are mediated by an electrogenic Na(+)/HCO3- cotransporter, and are more tightly coupled to network activity than are neuronal pH changes. As pH has profound effects on signaling in the nervous system, this work has implications for our understanding of seizure dynamics.
Ion dynamics during seizures.
Changes in membrane voltage brought about by ion fluxes through voltage and transmitter-gated channels represent the basis of neural activity. As such, electrochemical gradients across the membrane determine the direction and driving force for the flow of ions and are therefore crucial in setting the properties of synaptic transmission and signal propagation. Ion concentration gradients are established by a variety of mechanisms, including specialized transporter proteins. However, transmembrane gradients can be affected by ionic fluxes through channels during periods of elevated neural activity, which in turn are predicted to influence the properties of on-going synaptic transmission. Such activity-induced changes to ion concentration gradients are a feature of both physiological and pathological neural processes. An epileptic seizure is an example of severely perturbed neural activity, which is accompanied by pronounced changes in intracellular and extracellular ion concentrations. Appreciating the factors that contribute to these ion dynamics is critical if we are to understand how a seizure event evolves and is sustained and terminated by neural tissue. Indeed, this issue is of significant clinical importance as status epilepticus-a type of seizure that does not stop of its own accord-is a life-threatening medical emergency. In this review we explore how the transmembrane concentration gradient of the six major ions (K(+), Na(+), Cl(-), Ca(2+), H(+)and [Formula: see text]) is altered during an epileptic seizure. We will first examine each ion individually, before describing how multiple interacting mechanisms between ions might contribute to concentration changes and whether these act to prolong or terminate epileptic activity. In doing so, we will consider how the availability of experimental techniques has both advanced and restricted our ability to study these phenomena.