Nav1.1 haploinsufficiency in excitatory neurons ameliorates seizure-associated sudden death in a mouse model of Dravet syndrome

Dravet syndrome is a severe epileptic encephalopathy mainly caused by heterozygous mutations in the SCN1A gene encoding a voltage-gated sodium channel Nav1.1. We previously reported dense localization of Nav1.1 in parvalbumin (PV)-positive inhibitory interneurons in mice and abnormal firing of those neurons in Nav1.1-deficient mice. In the present study, we investigated the physiologic consequence of selective Nav1.1 deletion in mouse global inhibitory neurons, forebrain excitatory neurons or PV cells, using vesicular GABA transporter (VGAT)-Cre, empty spiracles homolog 1 (Emx1)-Cre or PV-Cre recombinase drivers. We show that selective Nav1.1 deletion using VGAT-Cre causes epileptic seizures and premature death that are unexpectedly more severe than those observed in constitutive Nav1.1-deficient mice. Nav1.1 deletion using Emx1-Cre does not cause any noticeable abnormalities in mice; however, the severe lethality observed with VGAT-Cre-driven Nav1.1 deletion is rescued by additional Nav1.1 deletion using Emx1-Cre. In addition to predominant expression in PV interneurons, we detected Nav1.1 in subpopulations of excitatory neurons, including entorhino-hippocampal projection neurons, a subpopulation of neocortical layer V excitatory neurons, and thalamo-cortical projection neurons. We further show that even minimal selective Nav1.1 deletion, using PV-Cre, is sufficient to cause spontaneous epileptic seizures and ataxia in mice. Overall, our results indicate that functional impairment of PV inhibitory neurons with Nav1.1 haploinsufficiency contributes to the epileptic pathology of Dravet syndrome, and show for the first time that Nav1.1 haploinsufficiency in excitatory neurons has an ameliorating effect on the pathology

Melting of excitonic insulator phase by an intense terahertz pulse in Ta2_2NiSe5_5

In this study, the optical response to a terahertz pulse was investigated in the transition metal chalcogenide Ta$_2$NiSe$_5$, a candidate excitonic insulator. First, by irradiating a terahertz pulse with a relatively weak electric field (0.3 MV/cm), the spectral changes in reflectivity near the absorption edge due to third-order optical nonlinearity were measured and the absorption peak characteristic of the excitonic phase just below the interband transition was identified. Next, by irradiating a strong terahertz pulse with a strong electric field of 1.65 MV/cm, the absorption of the excitonic phase was found to be reduced, and a Drude-like response appeared in the mid-infrared region. These responses can be interpreted as carrier generation by exciton dissociation induced by the electric field, resulting in the partial melting of the excitonic phase and metallization. The presence of a distinct threshold electric field for carrier generation indicates exciton dissociation via quantum-tunnelling processes. The spectral change due to metallization by the electric field is significantly different from that due to the strong optical excitation across the gap, which can be explained by the different melting mechanisms of the excitonic phase in the two types of excitations.Comment: 66 pages, 11 figures, 2 table

Development of a Scheme and Tools to Construct a Standard Moth Brain for Neural Network Simulations

Understanding the neural mechanisms for sensing environmental information and controlling behavior in natural environments is a principal aim in neuroscience. One approach towards this goal is rebuilding neural systems by simulation. Despite their relatively simple brains compared with those of mammals, insects are capable of processing various sensory signals and generating adaptive behavior. Nevertheless, our global understanding at network system level is limited by experimental constraints. Simulations are very effective for investigating neural mechanisms when integrating both experimental data and hypotheses. However, it is still very difficult to construct a computational model at the whole brain level owing to the enormous number and complexity of the neurons. We focus on a unique behavior of the silkmoth to investigate neural mechanisms of sensory processing and behavioral control. Standard brains are used to consolidate experimental results and generate new insights through integration. In this study, we constructed a silkmoth standard brain and brain image, in which we registered segmented neuropil regions and neurons. Our original software tools for segmentation of neurons from confocal images, KNEWRiTE, and the registration module for segmented data, NeuroRegister, are shown to be very effective in neuronal registration for computational neuroscience studies

Memory-specific correlated neuronal activity in higher-order auditory regions of a parrot.

Funder: Kayamori Foundation for Informational Science AdvancementFunder: the Netherlands Organization for Scientific ResearchFunder: Multi-Career Path Support Model for Female Researchers project of Japan’s Women UniversityFunder: Japan Society for the Promotion of Science (JSPS) Grant-in-AidFunder: ALW Open Competition and GW Horizon ProgrammeMale budgerigars (Melopsittacus undulatus) are open-ended learners that can learn to produce new vocalisations as adults. We investigated neuronal activation in male budgerigars using the expression of the protein products of the immediate early genes zenk and c-fos in response to exposure to conspecific contact calls (CCs: that of the mate or an unfamiliar female) in three subregions (CMM, dNCM and vNCM) of the caudomedial pallium, a higher order auditory region. Significant positive correlations of Zenk expression were found between these subregions after exposure to mate CCs. In contrast, exposure to CCs of unfamiliar females produced no such correlations. These results suggest the presence of a CC-specific association among the subregions involved in auditory memory. The caudomedial pallium of the male budgerigar may have functional subdivisions that cooperate in the neuronal representation of auditory memory