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Seizures have sleep–wake and circadian patterns in various epilepsies and, in turn, disrupt sleep and circadian rhythms. The resultant sleep deprivation (SD) is an exacerbating factor for seizures that sets up a vicious cycle that can potentially lead to disease progression and even to epilepsy-related mortality. A variety of cellular or network electrophysiological changes and changes in expression of clock-controlled genes or other transcription factors underlie sleep–wake and circadian distribution of seizures, as well as the disruptions seen in both. A broad understanding of these mechanisms may help in designing better treatments to prevent SD-induced seizure exacerbation, disrupt the vicious cycle of disease progression, and reduce epilepsy-related mortality.

Pattern separation is a central concept in current theories of episodic memory: this computation is thought to support our ability to avoid confusion between similar memories by transforming similar cortical input patterns of neural activity into dissimilar output patterns before their long-term storage in the hippocampus. Because there are many ways one can define patterns of neuronal activity and the similarity between them, pattern separation could in theory be achieved through multiple coding strategies. Using our recently developed assay that evaluates pattern separation in isolated tissue by controlling and recording the input and output spike trains of single hippocampal neurons, we explored neural codes through which pattern separation is performed by systematic testing of different similarity metrics and various time resolutions. We discovered that granule cells, the projection neurons of the dentate gyrus, can exhibit both pattern separation and its opposite computation, pattern convergence, depending on the neural code considered and the statistical structure of the input patterns. Pattern separation is favored when inputs are highly similar, and is achieved through spike time reorganization at short time scales (< 100 ms) as well as through variations in firing rate and burstiness at longer time scales. These multiplexed forms of pattern separation are network phenomena, notably controlled by GABAergic inhibition, that involve many celltypes with input-output transformations that participate in pattern separation to different extents and with complementary neural codes: a rate code for dentate fast-spiking interneurons, a burstiness code for hilar mossy cells and a synchrony code at long time scales for CA3 pyramidal cells. Therefore, the isolated hippocampal circuit itself is capable of performing temporal pattern separation using multiplexed coding strategies that might be essential to optimally disambiguate multimodal mnemonic representations., Author summary Pattern separation (the process of disambiguating incoming patterns of neuronal activity) is a central concept in all current theories of episodic memory, as it is hypothesized to support our ability to avoid confusion between similar memories. For the last thirty years, pattern separation has been attributed to the dentate gyrus of the hippocampus, but this has been hard to test experimentally. Moreover, because it is unclear how to define activity patterns in the brain, such a computation could be achieved in many different ways. Here, we demonstrate that pattern separation is performed by hippocampal networks (dentate gyrus and CA3) through a variety of neural codes. By systematically testing different definitions of what it means for spike trains to be similar (using a range of time scales and both standard and innovative metrics that assume different views of the neural code), we assessed how the input-output transformation of multiple hippocampal celltypes relate to pattern separation and found that different celltypes favor complementary coding strategies. This might help storing rich but concise and unambiguous representations of complex events. Finally, we provide the first experimental evidence of the importance of inhibitory signals in mediating pattern separation, and identify through which coding strategies.

Quantification of interictal spikes in EEG may provide insight on epilepsy disease burden, but manual quantification of spikes is time-consuming and subject to bias. We present a probability-based, automated method for the classification and quantification of interictal events, using EEG data from kainate- and saline-injected mice (C57BL/6J background) several weeks post-treatment. We first detected high-amplitude events, then projected event waveforms into Principal Components space and identified clusters of spike morphologies using a Gaussian Mixture Model. We calculated the odds-ratio of events from kainate-versus saline-treated mice within each cluster, converted these values to probability scores, P(kainate), and calculated an Hourly Epilepsy Index for each animal by summing the probabilities for events where the cluster P(kainate) > 0.5 and dividing the resultant sum by the record duration. This Index is predictive of whether an animal received an epileptogenic treatment (i.e., kainate), even if a seizure was never observed. We applied this method to an out-of-sample dataset to assess epileptiform spike morphologies in five kainate mice monitored for ~1 month. The magnitude of the Index increased over time in a subset of animals and revealed changes in the prevalence of epileptiform (P(kainate) > 0.5) spike morphologies. Importantly, in both data sets, animals that had electrographic seizures also had a high Index. This analysis is fast, unbiased, and provides information regarding the salience of spike morphologies for disease progression. Future refinement will allow a better understanding of the definition of interictal spikes in quantitative and unambiguous terms.

The gradual accumulation of amyloid-β (Aβ) is a neuropathologic hallmark of Alzheimer’s disease (AD); playing a key role in disease progression. Aβ is generated by the sequential cleavage of amyloid precursor protein (APP) by β- and γ-secretases, with BACE-1 (β-site APP cleaving enzyme-1) cleavage as the rate limiting step 1–3. CRISPR/Cas9 guided gene-editing is emerging as a promising tool to edit pathogenic mutations and hinder disease progression 4,5,6 However, few studies have applied this technology to neurologic diseases 7–9. Besides technical caveats such as low editing efficiency in brains and limited in vivo validation 7, the canonical approach of ‘mutation-correction’ would only be applicable to the small fraction of neurodegenerative cases that are inherited (i.e. < 10% of AD, Parkinson’s, ALS); with a new strategy needed for every gene. Moreover, feasibility of CRISPR/Cas9 as a therapeutic possibility in sporadic AD has not been explored. Here we introduce a strategy to edit endogenous APP at the extreme C-terminus and reciprocally manipulate the amyloid pathway – attenuating β-cleavage and Aβ, while up-regulating neuroprotective a-cleavage. APP N-terminus, as well as compensatory APP homologues remain intact, and key physiologic parameters remain unaffected. Robust APP-editing is seen in cell lines, cultured neurons, human embryonic stem cells/iPSC-neurons, and mouse brains. Our strategy works by limiting the physical association of APP and BACE-1, and we also delineate the mechanism that abrogates APP/BACE-1 interaction in this setting. Our work offers an innovative ‘cut and silence’ gene-editing strategy that could be a new therapeutic paradigm for AD.

Synchronous and bilateral spike-and-wave discharges accompany nonconvulsive behavioral and cognitive arrest during seizures associated with absence epilepsy. Previous investigation of multiple absence animal models suggests that the underlying cause of absence seizures is an increase in thalamic inhibitory tonic currents. In contrast, in this study we provide evidence that the level of cortical tonic inhibition also regulates absence seizure expression. Using continuous video-EEG recordings to monitor absence seizures and spike-and-wave discharge expression we show that pharmacological blockade of cortical tonic inhibition provokes absence seizures in wild-type mice. Furthermore, we show that pharmacological rescue of cortical tonic inhibition in an absence mouse (γ2R43Q) model, which lacks tonic inhibition, suppresses absence seizure and spike-and-wave discharge expression. Collectively, these results suggest an optimum level of tonic inhibition in the thalamocortical circuit is required for normal functioning and that a deviation from this optimum results in aberrant thalamocortical function, SWDs and absence seizures.

The γ2R43Q GABAA receptor mutation confers absence epilepsy in humans, and γ2R43Q knock-in mice (RQ) display absence seizures and generalized spike-and-wave discharges reminiscent of their human counterparts. Previous work on several rodent models led to the conclusion that elevated tonic inhibition in thalamic neurons is necessary and sufficient to produce typical absence epilepsy. In contrast, here we used patch-clamp electrophysiology in brain slices to show that RQ mice entirely lack tonic inhibition in principal cells of layer II/III somatosensory cortex and ventrobasal thalamus. Additionally, protein quantification and multielectrode electrophysiology show that the mutation interferes with trafficking of GABAA receptor subunits involved in generating tonic currents, leading to increased cortical firing and decreased thalamic bursting rates. Together with previous work, our results suggest that an optimum level of tonic inhibition is required for normal thalamocortical function, such that deviations in either direction away from this optimum enhance susceptibility to absence seizures.

The kinetics of GABAergic synaptic currents can vary by an order of magnitude depending on the cell type. The neurogliaform cell (NGFC) has recently been identified as a key generator of slow GABA(A) receptor-mediated volume transmission in the isocortex. However, the mechanisms underlying slow GABA(A) receptor-mediated IPSCs and their use-dependent plasticity remain unknown. Here, we provide experimental and modeling data showing that hippocampal NGFCs generate an unusually prolonged (tens of milliseconds) but low-concentration (micromolar range) GABA transient, which is responsible for the slow response kinetics and which leads to a robust desensitization of postsynaptic GABA(A) receptors. This strongly contributes to the use-dependent synaptic depression elicited by various patterns of NGFC activity including the one detected during theta network oscillations in vivo. Synaptic depression mediated by NGFCs is likely to play an important modulatory role in the feedforward inhibition of CA1 pyramidal cells provided by the entorhinal cortex.

Endocannabinoid signaling couples activity-dependent rises in postsynaptic Ca2+levels to decreased presynaptic GABA release. Here, we present evidence from paired recording experiments that cannabinoid-mediated inhibition of GABA release depends on the firing rates of the presynaptic interneurons. Low-frequency action potentials inpost hocidentified cholecystokinin-positive CA1 basket cells elicited IPSCs in the postsynaptic pyramidal cells that, as expected, were fully abolished by the exogenous application of the cannabinoid receptor agonist WIN55,212-2 [R-(+)-(2,3-dihydro-5-methyl-3-[(4-morpholinyl)methyl]pyrol[1,2,3-de]-1,4-benzoxazin-6-yl)(1-naphthalenyl) methanone monomethanesulfonate] at 5 μm. However, the presynaptic basket cells recovered from the cannabinoid agonist-induced inhibition of GABA release when the presynaptic firing rate was increased to ≥20 Hz. Pharmacological experiments showed that the recovered transmission was exclusively dependent on presynaptic N-type Ca2+channels. Furthermore, the increased presynaptic firing could also overcome even complete depolarization-induced suppression of inhibition, indicating that the magnitude of DSI markedly depends on the activity levels of basket cells. These results reveal a new locus of activity-dependent modulation for endocannabinoid signaling and suggest that endocannabinoid-mediated inhibition of GABA release may differ in distinct behavioral states.

GABAA receptors mediate synaptic and extrasynaptic inhibition. Native receptors consist of alpha and beta subunits, which are required for function, and another "modulatory" subunit, for example, gamma, delta, or epsilon. Of these, the epsilon subunit has the most restricted distribution, confers resistance to neurosteroid and anesthetic modulation, and causes spontaneous channel opening. Little is known, however, about how epsilon affects receptor kinetics, which in turn shape responses to both ambient and synaptic GABA exposure. Here, we expressed human alpha2beta1, alpha2beta1gamma2, or alpha2beta1epsilon subunit combinations in human embryonic kidney 293 cells and used rapid solution exchange to study receptor kinetics in outside-out patches. The epsilon subunit greatly slowed deactivation and recovery after brief GABA pulses. During long, saturating GABA pulses, the rate of desensitization was slower for alpha2beta1epsilon and alpha2beta1gamma2 than for alpha2beta1. However, in alpha2beta1epsilon, the final extent of desensitization was large compared with that of alpha2beta1gamma2. Responses in alpha2beta1epsilon, but not the others, were often followed by an "overshoot" above the baseline, suggesting that a fraction of channels are spontaneously open and are transiently silenced by receptor activation and subsequent desensitization. The baseline current and associated noise were reduced by picrotoxin, revealing that epsilon-containing channels are open approximately 4% of the time in the absence of GABA. These results suggest that, if epsilon-containing receptors are expressed at synapses, the synaptic currents would be long-lasting but may rundown quickly under high-frequency activation. In addition, silencing of spontaneous openings by desensitization raises the possibility that tonic inhibition mediated by epsilon-containing receptors may be regulated by phasic inhibition.