Neuroscience Research

Long-term, automated tracking of group-housed social animals using RFID (radio frequency identification) is a promising approach in ethological neuroscience. However, low-frequency (LF) RFID, while long-established in the field, is constrained by its inherent low data rates, which lead to two critical limitations: (1) compromised spatiotemporal resolution, and (2) the inability to identify multiple tags (animals) simultaneously. To address these limitations, we developed eeeHive, a high-frequency (HF) RFID-based animal tracking system with a fully custom hardware architecture that enables high-speed, multiplexed antenna polling and concurrent multi-tag reading. The polling time per antenna in eeeHive was 5.9 ms, with an additional 8.2 ms read time per tag. We applied the system to track 24 mice for one week, and six common marmosets for seven weeks. The system successfully tracked individuals even within dense clusters, revealing complex behavioral traits characterized by spatial utilization, temporal dynamics, behavioral regularity, and inter-individual relationships. Additional tests with Japanese fire-bellied newts and Nile tilapia juveniles demonstrated comparable tracking performance in aquatic environments. Taken together, eeeHive overcomes the inherent limitations of conventional LF RFID, establishing a powerful HF RFID-based platform for fine-scale behavioral tracking of group-housed animals across terrestrial and aquatic species.

The transcription factor FOXP2 is the most well-known language-related gene in humans, yet its role in primate vocalization remains poorly understood. Here we report that knockdown of FOXP2 in the striatum markedly disrupts vocalization stability in the marmoset monkey, a valuable non-human primate model for studying vocal behavior. FOXP2 exhibited high expression in the marmoset striatum, especially during early development. Using the CRISPR-Cas12 system, we achieved specific in vivo editing of the FOXP2 gene and effective knockdown of FOXP2 protein expression in the marmoset striatum. Two neonatal marmosets received bilateral striatal injections of the gene-editing and control virus, respectively, and were raised together in the same family. In three such marmoset pairs, analysis of vocalizations recorded during 6-15 weeks post-injection revealed that striatal FOXP2 knockdown significantly altered vocal features and increased intra-individual variability in phee syllables--the most common marmoset vocalization, often produced repetitively as multi-syllable phee calls. Notably, in FOXP2-edited marmosets, acoustic alterations were minimal in the first syllable of phee calls but became progressively more pronounced in subsequent syllables, which exhibited a marked upward shift in the frequency spectrum over time with progressively steeper slopes. These temporal dynamics in vocal features reflect a reduction in the stability of continuous vocal production. In line with the known striatal functions in motor control, our findings provide the first evidence of FOXP2 in controlling vocalization in non-human primates, thereby opening new avenues for investigating the neural mechanisms underlying FOXP2 function.

The Drosophila adult central brain contains 240 circadian neurons, of which there are more than 25 different neuron subtypes based on connectomic data. Recent single cell RNA-seq (scRNAseq) characterization of these neurons "around the clock" also indicates a similar number of molecular subtypes of circadian neurons, but other conclusions from these transcriptomic studies warranted verifying and extending with other approaches. To this end: 1) We used a genetic multiplexing strategy to profile the transcriptomes of circadian neurons from multiple time points in a single experiment, reducing confounding technical variation between timepoints; 2) Large numbers of single nuclei were sequenced (snRNA-seq), which was enabled because the new method EL-INTACT purifies nuclei from frozen heads; 3) We assayed 12 time points under both light-dark (LD) and constant darkness (DD) conditions. These approaches showed dramatic transcriptional differences between time points in many circadian neuron types and enhanced time-of-day gene expression analysis. The data indicate that most of this regulation is transcriptional and circadian. There were however a small number of light-dependent transcripts, including a few that correspond to mammalian immediate-early genes. They probably play a role in the light-regulation of gene expression and behavior in specific neurons, perhaps circadian entrainment or phase-shifting. The results taken together provide a more comprehensive picture of gene expression heterogeneity within adult Drosophila circadian neurons including how intrinsic clock mechanisms and light cues are integrated across circadian neuron subtypes.

The primary objective of system neuroscience is to understand the functional mapping and its causation in the dynamics of the brain network. Some experimental and methodological studies suggest that functional modularity and its hierarchical information processing in the brain network are crucial to understanding the functional role of task-specific or state-specific information flow in the brain. However, because most of the established techniques for detecting effective network structures in the neuroscience research field are strongly based on the "Granger causality" perspective, existing causal discovery methods specified for brain network analysis cannot identify the causal hierarchy in the modular network in the brain due to spurious correlation issues and indistinguishability of causal direction under the Gaussianity of observational noise in a linear system. To address the issues, we developed a causal discovery method for synchronous neural dynamics, called the Jacobian-informed linear non-Gaussian acyclic model, "j-VAR-LiNGAM", by incorporating the information of the Jacobian matrix determined from a phase-coupled oscillator model estimated from observed neural data into the VAR-LiNGAM algorithms. The method was validated by showing that it could extract causal ordering in both synthetic data and empirical neural observed data. Moreover, by analyzing the observed neural oscillatory signals obtained from mice and humans, we confirmed that our method identified causally hierarchical structures in the brain, which aligned with the neurophysiological interpretations. These findings suggested that our proposed method can reveal the neural basis of hierarchical information processing in the brain network.

The axon initial segment (AIS) undergoes structural plasticity and refines neuronal excitability, yet the underlying mechanisms remain unclear. We here developed an in vivo CRISPR/Cas9 knockout platform using an all-in-one triple-guide RNA vector introduced via electroporation and employed this approach to seek molecules that regulate the developmental shortening of AIS in the chicken nucleus magnocellularis. We have targeted fourteen molecules associated with microtubules and found that knockouts of glycogen synthase kinase 3{beta} (GSK3{beta}) and Tau disabled the AIS shortening. Conversely, overexpression of constitutively active form of GSK3{beta} facilitated the AIS shortening in vivo. This extensive shortening was replicated in slice cultures, which was occluded by stabilization of microtubules. These results suggested that microtubule remodeling by GSK3{beta} activity contributed to the AIS shortening. This study thus provides a genetic approach suitable for genetic screening that allows identifying regulators of the AIS plasticity in the chicken brain.

Lack of social interaction results in various behavioral abnormalities in rodents, including increased anxiety levels, altered sociability, and impaired cognitive ability. Epigenetic factors regulate gene expression, however, how they contribute to juvenile social isolation (jSI)-induced behavioral alterations remains largely unknown. Here, we focused on the nucleus accumbens (NAc), a critical brain region of the reward system that regulates motivation-related behaviors. We first performed RNA-seq on neuronal nuclei and found alterations in genes related to neuronal function, as well as in transcriptional and epigenetic regulation. Protein-protein interaction (PPI) analysis of differentially expressed genes (DEGs) showed that top key nodes among down-regulated genes include membrane receptors (Ntrk2, Grin3a, and Grik1) and an apoptosis regulator (Bcl2). To further investigate whether jSI-induced gene expression alterations are mediated by histone modifications, we next performed CUT&Tag for four histone modifications (H3K4me1, H3K4me3, H3K27ac, and H3K27me3), and the results implied that epigenetic alterations may also play a role in neuronal function as well as transcriptional regulation. Reanalysis of previously published RNA-seq data on the manipulation of histone modification-associated factors (including Kdm6b, Brd4, and Setd1a) suggested that these enzymes were probably involved in jSI-induced gene expression alterations. Taken together, our comprehensive analysis implies the involvement of histone modification regulation in jSI-related alterations of gene expression in NAc.

Electrophysiological data, which serve as a biological signal that bridges neural activity and behavioral tasks, provide an innovative approach to neuroscience research. In this study, we constructed a dataset that contains over 2000 neurons across 117 days recorded in 20 mice containing 28,573 trials. Data for 5 mice were collected from the Secondary Motor Cortex (M2) region 8 mice was derived from the Ventrolateral Striatum (VLS) and 7 mice were from Substantia Nigra pars Reticulata (SNR). We induced licking behavior in head-fixed mice by periodically delivering water through a spout while simultaneously recording spiking activity from three brain regions and behavior related electrical signals. This dataset ensures precise temporal alignment between neural activity and behavioral events, offering a robust foundation for investigating neural encoding mechanisms and simulation of neural activities. This dataset establishes a precise spike-to-event mapping, which enables high decoding accuracy using Multilayer Perceptron (MLP) and Support Vector Machine (SVM). It can serve as a high-quality benchmark for developing encoding and decoding algorithms in neural networks, particularly Spiking Neural Networks (SNNs).

MicroRNAs (miRNAs) play essential roles in the posttranscriptional regulation of gene expression in organisms. In the process of synthesizing mature miRNAs from miRNA precursors, the miRNA precursors are cleaved via Dicer at their loop structure, after which the miRNA precursors become mature and regulate transcription. However, the consequences of altering the loop sequence are not fully understood. The silkworm Bombyx mori is a lepidopteran insect with many genetic strains. We identified a mutant of the miRNA miR-3260 whose the part of the loop structure was lacking in a silkworm strain with translucent larval skin. Here, we aimed to analyze the role of wild-type miR-3260 and the influence of the mutation of the loop structure in B. mori. First, we identified the genomic region responsible for the translucent larval skin phenotype and determined that the mutated miR-3260 nucleotide sequences. Then, we predicted the binding partners of wild-type miR-3260 using the RNA hybrid tool and found two juvenile hormone (JH)-related genes as targets of wild-type miR-3260. Next, we assessed the relationships between miR-3260 and JH and found that miR-3260 was highly expressed in the Corpora allata and its expression responded to JH treatment. Meanwhile, miR-3260 mimic and inhibitor did not induce the typical phenotypes associated with JH in B. mori. Then, we compared the dicing products from wild-type and mutant miR-3260 precursors and observed that neither form underwent Dicer-mediated cleavage when the loop structure was altered. These results suggest that loop mutations in the miR-3260 precursor may not influence dicing activity, consistent with the lack of observable phenotypic effects.

The brain is believed to process information efficiently in a different manner from deep learning-based artificial intelligence (AI). Brain-like next-generation AI is gaining attention owing to its potential to perform human-like, highly adaptive, robust, and power-efficient computation. To realize such AI, one crucial approach is the bottom-up implementation of the neuronal systems, capturing their electrophysiological characteristics in electronic circuits. However, this neuromorphic approach generally focuses on simplified neuronal models that do not refer to many biological findings. Developing closer-to-brain models is a natural direction that serve as a fundamental computing model for next-generation AI. One of the constraints of neuromorphic circuits is the bit resolution of synaptic efficacy memory, as the memory footprint scales with it precision. Although low-resolution synaptic efficacy is essential for minimizing memory circuit footprint and energy consumption, it generally leads to performance degradation in many tasks such as the spatio-temporal spike pattern detection. This study proposed a closer-to-brain learning rule that incorporates heterosynaptic plasticity (HP) induced by glutamate spillover. It is demonstrated that our model mitigates the performance degradation associated with low-bit resolution synaptic efficacy, achieving the pattern detection success rate with 3-bit resolution synaptic efficacy, which is comparable to 64-bit floating-point precision. Furthermore, the findings of the study indicate that HP based model accelerates the convergence of the synaptic effcacy and effectively potentiates the synapses relevant to the pattern detection while suppressing irrelevant ones, thereby promoting a bimodal distribution of synaptic efficacies. These findings may provide a basic framework for constructing an energy-efficient, brain-like next-generation AI that maintains high performance under hardware constraints.

Octopamine is involved in a variety of different physiological and behavioral mecha-nisms in Drosophila melanogaster. Throughout the life cycle of the fruit fly, from the larva to the adult, octopaminergic neurons in both the central and the peripheral nerv-ous system target a multitude of neurons and even non-neuronal tissues, making it challenging to analyze individual mechanisms of octopamine function. One approach to deconstructing this complex system is to examine the postsynaptic components of signal transmission. In Drosophila, octopamine interacts with six distinct G-protein-coupled receptors. For some of these receptors, expression maps and functional im-plications have been described. In contrast, other receptors have been neglected, partly due to the lack of suitable genetic tools. Here, for the first time, we compiled a complete set of mutant lines of all known octopamine receptors, all generated using the same genetic tool, the recently established Trojan Exon system. It integrates the Gal4/UAS binary expression strategy while simultaneously impairing receptor func-tion. This enabled us to generate a comprehensive anatomical map of receptor ex-pression in the larva and, at the same time, analyze the function of individual octopa-mine receptors during larval development, chemosensory perception and locomotion. All octopamine receptors (Oamb, Oct2R, Oct{beta}1R, Oct{beta}2R, Oct{beta}3R, and Oct-TyrR) showed extensive signal in the central nervous system. The same was found for the peripheral nervous system, with the exception of Oct{beta}2R, which showed pronounced expression in the somatic muscles. We also observed a previously undescribed role of Oct{beta}1R, Oct{beta}3R, and Oct-TyrR in larval hatching and in the survival of larvae and pupae. Molecular evaluation of the Trojan Exon octopamine lines supports our analy-sis. In addition, we combined the experimental results with gene expression data from the different development stages of Drosophila melanogaster and from different tis-sues and cell populations throughout the body. Overall, we compiled, analyzed and validated a complete set of octopamine lines which, together with gene expression analysis, provides a basis for further functional studies on the larval octopaminergic system.

Homeostatic plasticity of intrinsic excitability (IE) in the visual system has been essentially shown at the cortical level but whether thalamic nuclei also express homeostatic plasticity of IE is unknown. We show here that 4 days of monocular deprivation (MD) at eye opening induces a homeostatic change in IE in dorsal lateral geniculate nucleus (dLGN) neurons. Neurons recorded in the dLGN region activated by the deprived eye are more excitable than neurons recorded in the dLGN region activated by the open eye. No significant changes were observed following 7 days of MD, however. Enhanced excitability in neurons from the deprived side after 4 days of MD was associated with a reduced Kv1-dependent LTP-IE, a smaller voltage ramp, and a reduced inter-spike interval, suggesting that Kv1 channels are down-regulated in deprived dLGN neurons. Furthermore, the ankyrin G signal of the axon initial segment was larger in deprived dLGN neurons compared with open ones, indicating that Nav1 channel number also undergoes homeostatic regulation, and Kv1.1 channel signals were lower in deprived neurons compared to open ones. In addition, electrical coupling was found to be strengthened in neurons displaying enhanced IE following either brief (4 days) or long (10 days) MD. These results suggest that homeostatic and Hebbian plasticity in the dLGN share common expression mechanisms involving the regulation of Kv1 channels, Nav1 channels and electrical coupling between relay neurons.

Recombinant Adeno-associated viruses (AAVs) are widely used for gene delivery in the central nervous system and have become central tools in both gene therapy and basic neuroscience research. However, although AAV serotypes have been extensively characterized in rodent models, their performance in human neurons, particularly those derived from induced pluripotent stem cells (iPSCs), remains poorly characterized. While human iPSC-derived neurons are increasingly used for disease modeling and drug screening, their susceptibility to viral transduction varies and remains difficult to predict. In this study, we systematically evaluated the transduction efficiency and toxicity profiles of 18 wild-type and engineered AAV serotypes across three distinct types of iPSC-derived neurons, relevant to disease modeling and drug discovery: cortical projection neurons, NGN2- induced forebrain-like neurons, and dopaminergic neurons and four doses (1E3, 1E4, 1E5 and 2E5 genome copies per cell). Using automated high-throughput confocal imaging and quantification of reporter gene expression, we identified several serotypes with robust and efficient transduction across all neuronal subtypes. Among these, three serotypes AAV6, AAV6.2 and AAV2.7m8 showed consistently high performance. To assess safety, we quantified cell number and neurite morphology, finding that while high transduction and gene expression correlate with toxicity, sensitivity varied across neuronal subtypes, with NGN2 neurons being most vulnerable and dopaminergic neurons most resilient. Finally, we validated our findings in a more complex 3D model by testing one of the best-performing serotypes, AAV2.7m8, in both whole and dissociated human cerebellar organoids. Together, our results establish a benchmark dataset for AAV performance in human iPSC- derived neurons and provide practical guidance for AAV based gene delivery in human in vitro neural models. This resource will be valuable for both basic research and preclinical applications aiming to manipulate gene expression in human neurons and understanding AAV tropism in disease-relevant cell types.

The cerebellar nuclei form the main output structures of the cerebellum and are composed of a deeply conserved set of cell types. Two excitatory cell classes, Class-A and -B, are present in each cerebellar nucleus and mediate all excitatory output of the cerebellum. To provide genetic access to these cell types, here we identified Acan as a marker gene for Class-B cells and generated a knock-in Acan-P2A-Cre mouse line. We demonstrate that this Acan-Cre line selectively labels Class-B neurons in the cerebellar nuclei and validate its use in viral projection tracing. This new mouse line provides a valuable genetic tool to study cerebellar nuclei organization and function.

Glutamatergic neuronal synapses in the mouse neocortex mature during the first two months after birth. A key event during synaptic maturation is a change in short-term synaptic plasticity (STP), i.e. a switch from strong synaptic depression to a weaker depression or even facilitation. Glutamatergic pyramidal neurons located in the cortical layers II/III, layer V, and layer VI project axons through the corpus callosum where they release glutamate along their shafts and form glutamatergic synapses with oligodendrocyte precursor cells (OPCs). Here, we used single-cell electrophysiological recordings in brain slices to investigate synaptic plasticity at neuron-OPC synapses along axonal shafts in the white matter, and applied computation approaches to pinpoint the mechanisms of this plasticity. We found that during postnatal development of mice, there is a switch from short-term synaptic depression to short-term synaptic facilitation at glutamatergic neuron-OPC synapses in the corpus callosum. Synaptic delay of phasic neuron-OPC excitatory postsynaptic current shortens, and the amount of asynchronous release at neuron-OPC synapses decrease as animals mature, indicating that glutamate release becomes more synchronized. Our computational modelling suggests that both pre- and postsynaptic changes may contribute to the functional development and changes of plasticity at neuron-OPC synapses in the white matter. Taking together, our findings indicate that synaptic release machineries located at different sites along the same axon (i.e. axonal shaft in the white matter vs synaptic boutons in the grey matter) mature in a very similar fashion, STP occurs at both synaptic sites, and STP dynamics represent an important event during brain maturation.

High and low tides occur twice a day (every [~]12.4 hours), with the largest tidal ranges during spring tides around new and full moons (every [~]14.765 days). While these lunar cycles are known to influence many animal phenotypes, particularly the reproduction of coastal animals, the genetic basis of lunar-related rhythms remains unclear. Since phenotypic variation is a valuable resource for elucidating such mechanisms, we examined geographic variation in the lunar-regulated mass spawning of the grass puffer (Takifugu alboplumbeus) along the Japanese coast. We found that western populations spawn during the first half of the spring tides, whereas eastern populations spawn during the second half. Furthermore, although spawning typically occurs a few hours before high tide, this timing is restricted to a specific time window that is earlier in the western populations than in the eastern ones. Behavioral analysis of larvae also revealed a shorter free-running circadian period ({tau}) in the western population than in the eastern ones. As differences in {tau} affect individual variation in the timing of physiological functions and behaviors, we hypothesized that differences in {tau} could account for the different time windows and consequently the observed difference in spawning days. Population genomics analysis identified proline-rich transmembrane protein 1-like (prrt1l) as a candidate gene. Expression of prrt1l was observed in the circadian pacemaker suprachiasmatic nucleus, and triple CRISPR F0 knockout of prrt1l shortened the free-running period in larvae. These findings suggest a potential mechanism underlying the geographic variation in lunar-synchronized spawning behavior. HighlightsO_LIThe geographic variation exists in the lunar-regulated spawning of the grass puffer, with differences in spawning dates and times between western and eastern Japan. C_LIO_LIThe free-running period of western populations is shorter than that of eastern populations, which is consistent with their earlier spawning timing. C_LIO_LIPopulation genomics analysis identified prrt1l as a candidate gene harboring population-specific missense mutations, the knockout of which shortens the free-running period. C_LI

CaMKII promoter is widely used to label and manipulate hippocampal pyramidal neurons via transgenic mouse lines or viral approaches. While it targets most excitatory neurons, a small subset remains unlabeled and often overlooked. We present an AAV-based strategy combined with CaMKII-driven Cre expression to access and study this remaining population. Furthermore, we provide a detailed protocol for in-house AAV production, targeted stereotaxic delivery, and functional validation of targeted neurons through slice electrophysiology and behavior. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=194 HEIGHT=200 SRC="FIGDIR/small/723440v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@3a31ccorg.highwire.dtl.DTLVardef@9b7e90org.highwire.dtl.DTLVardef@92297borg.highwire.dtl.DTLVardef@1e159eb_HPS_FORMAT_FIGEXP M_FIG C_FIG

The circadian system is an important regulator of reward-related neural function and behavior. Dopamine (DA) release in the nucleus accumbens is a key component of reward processing, yet how circadian timing shapes DA release in relation to reward behavior remains unclear. Here, we investigated circadian rhythms in DA release and reward behavior using long-term fiber photometry paired with an automated reward delivery and measurement system. We found two distinct circadian rhythms in DA release: spontaneous DA, reflecting ongoing DA release not associated with reward, and reward-evoked DA, reflecting transient DA response during reward. Spontaneous DA peaked during the early subjective day, whereas reward-evoked peak DA peaked near the day-to-night transition. Both rhythms were distinct from reward behavior, which peaked during the early subjective night. Linear modeling further showed that the relationship between reward-evoked DA and reward behavior depended on circadian time, with greater DA responses occurring between late subjective day and early subjective night. Spontaneous baseline and reward-evoked DA were also negatively correlated, and this relationship was likewise modulated across circadian time. Together, these findings support a model in which circadian modulation of baseline DA may alter the gain of reward-evoked signaling, amplifying DA responses across behaviorally relevant times of day.

Apuschkin et al. (2024) proposed a GPCR-based transcriptomic atlas for midbrain dopamine (DA) neuron subpopulations, including candidates such as Nmur1, Cckar, and Ffar4. To guide genetic targeting, these markers must reflect functional expression in adult DA neurons. Using in situ hybridization, Cre-dependent reporter lines, and both intracranial and systemic viral approaches, we find no evidence of adult Nmur1-mediated recombination in DA neurons, while Cckar-driven recombination is consistent with developmental expression only. Notably, Ffar4 expression overlaps extensively with Ntsr1 midbrain populations, indicating that it does not define a distinct DA neuron class. Furthermore, analysis of independent spatial transcriptomic datasets together with our MERFISH data shows that many proposed GPCR markers are not detectably expressed in adult DA neurons. These findings demonstrate that transcriptomic enrichment does not always yield reliable adult markers and highlight the need for functional validation prior to use in circuit targeting.

We present a free and open-source, semi-automated, topologically robust pipeline for fitting cable models to 3D surface mesh morphology data of neuronal membranes, particularly suited to structures with complex shapes and topological holes. The motivation for this work is the discovery of morphologically complex neural spines on the auditory space-specific neurons of the barn owl (Tyto alba, Tyto furcata), dubbed "toric spines", notable for their high curvature, branching density, and holes/loops. Multicompartmental simulation software requires morphology to be represented as cable models (e.g., SWC format), yet existing software tools for fitting cable models to complex 3D surface meshes have not produced satisfactory results for toric spines, and loops are generally unsupported. We present the Mesh and Skeleton Cable Fitting (MASCAF) pipeline and software, which fits a cable model (e.g., SWC format) to a surface mesh using mean-curvature flow skeletonization. In this paper, we demonstrate how MASCAF is applied to fit cable models, how loops can be reconstructed in simulations with the Arbor and NEURON simulation software, and how the results can be validated using geometry and simulator-based methods. While non-tree morphologies such as toric spines are neuroanatomically special, our software pipeline provides a cable-model fitting approach for surface mesh data that is topologically robust, deterministic, open-source, and applicable to general morphologies, thereby closing a crucial gap between neuronal imaging and high-resolution simulation.

Voltage-gated sodium channels (VGSCs) are conventionally described as heterotrimers composed of one alpha and two beta subunits. However, the patterns of co-expression of alpha- and beta-subunits in neurons remain unclear. In the present study, we report that alpha- (Nav1.1, Nav1.2, and Nav1.6) and beta- (beta-1 and beta-2) subunits are densely expressed in axon initial segments (AISs) of neurons in the neocortex, hippocampus and cerebellum at postnatal days 14-15 (P14-15) and 8-9 weeks (8-9W). These distributions are largely unique and partially overlapping among brain regions. Notably, in the neocortex and hippocampus, AISs of presumptive parvalbumin-positive inhibitory neurons are positive for Nav1.1 and beta-1, whereas those of excitatory ones are positive for Nav1.2 and beta-2. Similarly, AISs of cerebellar basket cells, which are inhibitory neurons, are positive for Nav1.1 and beta-1, whereas those of granule cells, which are excitatory neurons, are positive for Nav1.2 and beta-2. Nav1.6 is expressed in many of these neurons. Some subunits exhibited distinct distribution patterns at the two postnatal stages analyzed, possibly because of their developmental changes of subcellular localizations. Taken together, these results indicate that combinations of VGSC subunits are largely unique among different neuronal subpopulations. These findings provide a useful reference for understanding the distribution and interactions of VGSC subunits in the brain.