Summary Disease-causing mutations in ion channels generally alter intrinsic gating properties such as activation, inactivation or voltage-dependence. We examined nine different mutations of the KCNT1 (Slack) Na+-activated K+ channel that give rise to three distinct forms of epilepsy. All produced many fold-increases in current amplitude over that of the wild type channel. This could not be accounted for by increases in the intrinsic open probability of individual channels. Rather, greatly increased opening was a consequence of cooperative interactions between multiple channels in a patch. The degree of cooperative gating was much greater for all of the mutant channels than for the wild type channel, and could explain increases in current even in a mutant with reduced unitary conductance. We also found that the same mutation gives rise to different forms of epilepsy in different individuals. Our findings indicate that a major consequence of the mutations is to alter channel-channel interactions.

Mutations in the KCNT1 (Slack, K Na 1.1) sodium-activated potassium channel produce severe epileptic encephalopathies. Expression in heterologous systems has shown that the disease-causing mutations give rise to channels that have increased current amplitude. It is not known, however, whether such gain of function occurs in human neurons, nor whether such increased K Na current is expected to suppress or increase the excitability of cortical neurons. Using genetically engineered human induced pluripotent stem cell (iPSC)-derived neurons, we have now found that sodium-dependent potassium currents are increased several-fold in neurons bearing a homozygous P924L mutation. In current-clamp recordings, the increased K Na current in neurons with the P924L mutation acts to shorten the duration of action potentials and to increase the amplitude of the afterhyperpolarization that follows each action potential. Strikingly, the number of action potentials that were evoked by depolarizing currents as well as maximal firing rates were increased in neurons expressing the mutant channel. In networks of spontaneously active neurons, the mean firing rate, the occurrence of rapid bursts of action potentials, and the intensity of firing during the burst were all increased in neurons with the P924L Slack mutation. The feasibility of an increased K Na current to increase firing rates independent of any compensatory changes was validated by numerical simulations. Our findings indicate that gain-of-function in Slack K Na channels causes hyperexcitability in both isolated neurons and in neural networks and occurs by a cell-autonomous mechanism that does not require network interactions.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. AbstractObjective: Brain-responsive neurostimulation (RNS System, NeuroPace) is used to treat medically refractory focal epilepsy and also provides long-term ambulatory neurophysiologic data. We sought to determine whether these data could predict the clinical response to antiseizure drugs (ASDs). Methods: First, newly added medications were identified in RNS System patients followed at a single epilepsy center. Daily detection rates including "episode starts" (predominantly interictal activity) and "long episodes" (often electrographic seizures) were compared before and after ASD initiation. Efficacy was determined from documentation of clinical improvement and medication retention. Next, the analysis was repeated on an independent sample of patients from a multicenter long-term treatment trial, using an efficacy measure of ≥50% reduction in diary-recorded seizure frequency after 3 months. Results: In the single center cohort, long episodes, but not episode starts, had a significantly greater reduction in the first week for clinically efficacious compared to inefficacious medications. In this cohort, having no long episodes in the first week was highly predictive of ASD efficacy. In the multicenter cohort, both long episodes and episode starts had a significantly greater reduction for effective medications starting in the first 1-2 weeks. In this larger dataset, a ≥50% decrease in episode starts was 90% specific for efficacy with a positive predictive value (PPV) of 67%, and a ≥84% decrease in long episodes was 80% specific with a PPV of 48%. Conversely, a <25% decrease in long episodes (including any increase) or a <20% decrease in episode starts had a predictive value for inefficacy of >80%. Significance: In RNS System patients with stable detection settings, when new ASDs are started, detection rates within the first 1-2 weeks may provide an early, objective indication of efficacy. These data could be used to identify responses to medication trials early to allow more rapid medication adjustments than conventionally possible.

We have generated a mouse model of this condition by replacing the wild type gene with one encoding Kcnt1 R455H , a cytoplasmic c-terminal mutation homologous to a human R474H variant that results in EIMFS. We compared behavior patterns and seizure activity in these mice with those of wild type mice and Kcnt1 −/− mice. Complete loss of Kcnt1 produced deficits in open field behavior and motor skill learning. Although their thresholds for electrically and chemically induced seizures were similar to those of wild type animals, Kcnt1 −/− mice were significantly protected from death after maximum electroshock-induced seizures. In contrast, homozygous Kcnt1 R455H/R455H mice were embryonic lethal. Video-EEG monitoring of heterozygous Kcnt1 +/R455H animals revealed persistent interictal spikes, spontaneous seizures and a substantially decreased threshold for pentylenetetrazoleinduced seizures. Surprisingly, Kcnt1 +/R455H mice were not impaired in tasks of exploratory behavior or procedural motor learning. These findings provide an animal model for EIMFS and suggest that Slack channels are required for the development of procedural learning and of pathways that link cortical seizures to other regions required for animal survival.Sodium influx into neurons through voltage-dependent sodium channels and through glutamate receptors during repetitive firing in neurons leads to the activation of Na + -activated K + currents, termed K Na currents 1 . Many K Na currents are mediated by two related potassium channel subunits 2 . Like many ion channels, these two subunits have had multiple names over time, and the names used here are Slack (also called K Na 1.1 or Slo2.2 and encoded by the KCNT1 gene) and Slick (K Na 1.2, Slo2.1, encoded by the KCNT2 gene) 3,4 . The Slack (Sequence Like A Calcium-activated K + Channel) subunit is widely expressed in the mammalian nervous system 5 . Rapid activation of K Na currents contributes to action potential repolarization and shapes synaptic potentials, while slower activation produces adaptation of firing rates during sustained neuronal stimulation and to afterhyperpolarizations that follow such stimulation 6 , K Na currents also regulate the temporal accuracy of action potentials in response to high-frequency stimulation 7 .Slack channels resemble K v channels in their transmembrane topology, with six hydrophobic transmembrane domains 8 . The large cytoplasmic C-terminal domain of the Slack subunit, however, shares similarities with the BK potassium channel 9 and contains two RCK (regulator of the conductance of K) domains. In addition to having a putative Na + sensing domain 10 , the C-terminus is required for the interactions between the Slack protein and cytoplasmic signaling molecules such as Phactr-1 and the Fragile X Mental Retardation Protein (FMRP) 11,12 .

The function of long-term memory is not just to reminisce about the past, but also to make predictions that help us behave appropriately and efficiently in the future. This predictive function of memory provides a new perspective on the classic question from memory research of why we remember some things but not others. If prediction is a key outcome of memory, then the extent to which an item generates a prediction signifies that this information already exists in memory and need not be encoded. We tested this principle using human intracranial EEG as a time-resolved method to quantify prediction in visual cortex during a statistical learning task and link the strength of these predictions to subsequent episodic memory behavior. Epilepsy patients of both sexes viewed rapid streams of scenes, some of which contained regularities that allowed the category of the next scene to be predicted. We verified that statistical learning occurred using neural frequency tagging and measured category prediction with multivariate pattern analysis. Although neural prediction was robust overall, this was driven entirely by predictive items that were subsequently forgotten. Such interference provides a mechanism by which prediction can regulate memory formation to prioritize encoding of information that could help learn new predictive relationships.SIGNIFICANCE STATEMENTWhen faced with a new experience, we are rarely at a loss for what to do. Rather, because many aspects of the world are stable over time, we rely on past experiences to generate expectations that guide behavior. Here we show that these expectations during a new experience come at the expense of memory for that experience. From intracranial recordings of visual cortex, we decoded what humans expected to see next in a series of photographs based on patterns of neural activity. Photographs that generated strong neural expectations were more likely to be forgotten in a later behavioral memory test. Prioritizing the storage of experiences that currently lead to weak expectations could help improve these expectations in future encounters.