Clinical spectrum of STX1B-related epileptic disorders.

OBJECTIVE: The aim of this study was to expand the spectrum of epilepsy syndromes related to STX1B, encoding the presynaptic protein syntaxin-1B, and establish genotype-phenotype correlations by identifying further disease-related variants. METHODS: We used next-generation sequencing in the framework of research projects and diagnostic testing. Clinical data and EEGs were reviewed, including already published cases. To estimate the pathogenicity of the variants, we used established and newly developed in silico prediction tools. RESULTS: We describe 17 new variants in STX1B, which are distributed across the whole gene. We discerned 4 different phenotypic groups across the newly identified and previously published patients (49 patients in 23 families): (1) 6 sporadic patients or families (31 affected individuals) with febrile and afebrile seizures with a benign course, generally good drug response, normal development, and without permanent neurologic deficits; (2) 2 patients with genetic generalized epilepsy without febrile seizures and cognitive deficits; (3) 13 patients or families with intractable seizures, developmental regression after seizure onset and additional neuropsychiatric symptoms; (4) 2 patients with focal epilepsy. More often, we found loss-of-function mutations in benign syndromes, whereas missense variants in the SNARE motif of syntaxin-1B were associated with more severe phenotypes. CONCLUSION: These data expand the genetic and phenotypic spectrum of STX1B-related epilepsies to a diverse range of epilepsies that span the International League Against Epilepsy classification. Variants in STX1B are protean and contribute to many different epilepsy phenotypes, similar to SCN1A, the most important gene associated with fever-associated epilepsies.

A CREB2-targeting microRNA is required for long-term memory after single-trial learning.

Although single-trial induced long-term memories (LTM) have been of major interest in neuroscience, how LTM can form after a single episode of learning remains largely unknown. We hypothesized that the removal of molecular inhibitory constraints by microRNAs (miRNAs) plays an important role in this process. To test this hypothesis, first we constructed small non-coding RNA (sncRNA) cDNA libraries from the CNS of Lymnaea stagnalis subjected to a single conditioning trial. Then, by next generation sequencing of these libraries, we identified a specific pool of miRNAs regulated by training. Of these miRNAs, we focussed on Lym-miR-137 whose seed region shows perfect complementarity to a target sequence in the 3' UTR of the mRNA for CREB2, a well-known memory repressor. We found that Lym-miR-137 was transiently up-regulated 1 h after single-trial conditioning, preceding a down-regulation of Lym-CREB2 mRNA. Furthermore, we discovered that Lym-miR-137 is co-expressed with Lym-CREB2 mRNA in an identified neuron with an established role in LTM. Finally, using an in vivo loss-of-function approach we demonstrated that Lym-miR-137 is required for single-trial induced LTM.

Balanced plasticity and stability of the electrical properties of a molluscan modulatory interneuron after classical conditioning: a computational study.

The Cerebral Giant Cells (CGCs) are a pair of identified modulatory interneurons in the Central Nervous System of the pond snail Lymnaea stagnalis with an important role in the expression of both unconditioned and conditioned feeding behavior. Following single-trial food-reward classical conditioning, the membrane potential of the CGCs becomes persistently depolarized. This depolarization contributes to the conditioned response by facilitating sensory cell to command neuron synapses, which results in the activation of the feeding network by the conditioned stimulus. Despite the depolarization of the membrane potential, which enables the CGGs to play a key role in learning-induced network plasticity, there is no persistent change in the tonic firing rate or shape of the action potentials, allowing these neurons to retain their normal network function in feeding. In order to understand the ionic mechanisms of this novel combination of plasticity and stability of intrinsic electrical properties, we first constructed and validated a Hodgkin-Huxley-type model of the CGCs. We then used this model to elucidate how learning-induced changes in a somal persistent sodium and a delayed rectifier potassium current lead to a persistent depolarization of the CGCs whilst maintaining their firing rate. Including in the model an additional increase in the conductance of a high-voltage-activated calcium current allowed the spike amplitude and spike duration also to be maintained after conditioning. We conclude therefore that a balanced increase in three identified conductances is sufficient to explain the electrophysiological changes found in the CGCs after classical conditioning.

Persistent sodium current is a nonsynaptic substrate for long-term associative memory.

Although synaptic plasticity is widely regarded as the primary mechanism of memory [1], forms of nonsynaptic plasticity, such as increased somal or dendritic excitability or membrane potential depolarization, also have been implicated in learning in both vertebrate and invertebrate experimental systems [2-7]. Compared to synaptic plasticity, however, there is much less information available on the mechanisms of specific types of nonsynaptic plasticity involved in well-defined examples of behavioral memory. Recently, we have shown that learning-induced somal depolarization of an identified modulatory cell type (the cerebral giant cells, CGCs) of the snail Lymnaea stagnalis encodes information that enables the expression of long-term associative memory [8]. The Lymnaea CGCs therefore provide a highly suitable experimental system for investigating the ionic mechanisms of nonsynaptic plasticity that can be linked to behavioral learning. Based on a combined behavioral, electrophysiological, immunohistochemical, and computer simulation approach, here we show that an increase of a persistent sodium current of this neuron underlies its delayed and persistent depolarization after behavioral single-trial classical conditioning. Our findings provide new insights into how learning-induced membrane level changes are translated into a form of long-lasting neuronal plasticity already known to contribute to maintained adaptive modifications at the network and behavioral level [8].

Dynamic control of a central pattern generator circuit: a computational model of the snail feeding network.

Central pattern generators (CPGs) are networks underlying rhythmic motor behaviours and they are dynamically regulated by neuronal elements that are extrinsic or intrinsic to the rhythmogenic circuit. In the feeding system of the pond snail, Lymnaea stagnalis, the extrinsic slow oscillator (SO) interneuron controls the frequency of the feeding rhythm and the N3t (tonic) has a dual role; it is an intrinsic CPG interneuron, but it also suppresses CPG activity in the absence of food, acting as a decision-making element in the feeding circuit. The firing patterns of the SO and N3t neurons and their synaptic connections with the rest of the CPG are known, but how these regulate network function is not well understood. This was investigated by building a computer model of the feeding network based on a minimum number of cells (N1M, N2v and N3t) required to generate the three-phase motor rhythm together with the SO that was used to activate the system. The intrinsic properties of individual neurons were represented using two-compartment models containing currents of the Hodgkin-Huxley type. Manipulations of neuronal activity in the N3t and SO neurons in the model produced similar quantitative effects to food and electrical stimulation in the biological network indicating that the model is a useful tool for studying the dynamic properties of the feeding circuit. The model also predicted novel effects of electrical stimulation of two CPG interneurons (N1M and N2v). When tested experimentally, similar effects were found in the biological system providing further validation of our model.