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 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.

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.

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.

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

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.

The brain is one of the most complex animal organs but the development of the many different neuron types remains enigmatic. A set of brain-specific transcription factors is known to be involved in brain patterning but their specific contributions remain to be elucidated in most cases, including foxQ2II. This transcription factor is known to be conserved in anterior neuroectodermal patterning of most animals while it has been lost from vertebrates. However, the contribution of foxQ2II-positive neurons to the adult brain has remained enigmatic. Here, we use an enhancer trap, immunostainings and our newly established beetle brainbow system to categorize Tc-foxQ2II-positive neurons into nine clusters with different projection patterns. All clusters contain neurons with the fast activating neurotransmitters acetylcholine and glutamate while no Tc-foxQ2II positive neuron is GABA-ergic or serotonin-positive. Interestingly, we found that many dopaminergic neurons were Tc-foxQ2II positive and we homologize them with dopaminergic neurons of the PPL2c, PPM1 and PPL1 cluster described in the Drosophila brain. Our results show that Tc-foxQ2II marks subsets of fast-acting interneurons contributing to the higher order brain centers mushroom bodies and central complex. Taken together, our work expands the known functional range of foxQ2 genes from sensory and neurosecretory cell specification to interneurons involved in the function of higher order brain centers.

Herbivore-induced plant volatiles (HIPVs) play a critical role in inducible plant defense as information-bearing airborne signals. Released from damaged tissues, HIPVs induce defense responses in undamaged parts of the plant, thereby reducing the risk of subsequent herbivore attack. Although both emission and perception are fundamental components of HIPV-mediated signaling, the co-evolutionary dynamics of these traits under herbivore-driven selection remain poorly understood. Here, we develop a mathematical model of within-plant signaling that explicitly incorporates both inducible signal emission and perception as evolving traits. Using the model, we derived the optimal level of HIPV signal emission and signal perception under successive herbivore attacks. Our results show that the strategy with both signal emission and signal perception, which underlies HIPV-mediated signaling, is favored only under intermediate levels of herbivory. Within this range, increasing herbivory frequency drives the joint evolution of reduced signal emission and enhanced sensitivity to released signal. Furthermore, extending the model to include perception-independent functions of HIPVs, such as the attraction of natural enemies and the deterrence of herbivores, expands the range of conditions under which HIPV-mediated signaling is favored. At the same time, it also allows the emergence of emission-only strategies lacking signal perception, suggesting the potential decoupling of the co-evolution of emission and responsiveness. These findings provide a theoretical framework for understanding how emission and perception jointly shape the evolution of volatile-mediated signaling systems in plants.

We find that multi-site temporal control of optogenetic photostimulation in peripheral nerves can enhance firing rates by overcoming the intrinsic limitation of opsin photophysics. The benefits of multi-site optogenetic stimulation were demonstrated with three approaches: (1) in silico modeling, (2) ex vivo in the sciatic nerve, and (3) in vivo in the vagus nerve. An in silico model of multi-site optogenetic stimulation was developed in two Hodgkin and Huxley type neuron models, that supported our hypothesis. The ex vivo sciatic nerve showed an increase in firing frequency that is physiologically relevant for functional control. The technique was then applied in vivo for optogenetic vagus nerve stimulation resulting in significant changes in heart rate compared with standard methods of single-site stimulation. Improving the control of optogenetically induced neural firing will have broad impacts for future developments in optical nerve interfaces and brain-machine interfaces.

Vestibular neurons are core elements of the pathways involved in vestibulo-motor functions, such as vestibulo-spinal and vestibulo-ocular reflexes. To meet behavioral needs, electrophysiological neuronal properties are adequately adapted to the sensory-motor computation sustaining these distinct vestibular reflexes. During frog metamorphosis, there is a complete reorganization of the posturo-locomotor system while the oculomotor system remains minimally changed, probably associated to so far unknown changes in vestibular neuronal properties. We used this unique model to investigate the central developmental mechanisms underlying such a reconfiguration of vestibular-associated behaviors. Central vestibular neurons exhibit two types of electrophysiological phenotypes: tonic neurons with a continuous discharge and phasic neurons with a transitory discharge mainly due to the activation of Kv1.1 channel. Electrophysiological recordings and Kv1.1 immunolabeling of vestibulospinal (VS) and vestibulo-ocular (VO) neurons at both larval and juvenile stages revealed that the majority of VS neurons exhibited a tonic discharge in larvae but a phasic discharge in juvenile, while VO neurons remained mainly tonic throughout development. Changes in phasic and tonic neurons proportions in VS population are partly explained by neurogenesis. But we provide evidences that an electrophysiological phenotype switch is a concomitant developmental mechanism participating in the maturation of these central vestibular neurons. All together our results showed that the maturation process in central vestibular neuronal groups is highly related to the metamorphosis-induced remodeling of vestibulo-motor functions they are involved in, with the ultimate purpose of ensuring an adequate adaptation of neuronal elements properties to the developmental changes of behavioral constrains.

Vocal communication involves a series of cognitive processes, which can be broadly categorized into three components: perceiving communicative signals; deciding whether and how to respond; and generating vocal motor output. These processes must work harmoniously, with integration and bridging between components being crucial for effective communication. Previous research on vocal communication has typically focused on specific brain regions or isolated cognitive functions, often lacking a holistic perspective of macro-scale, whole-cortical dynamics and their role in the complete communication process. Therefore, although the cortical areas associated with each cognitive component have been localized in humans, the macro-scale cortical dynamics underlying the integration of these cognitive processes remain unknown. Building on recent findings linking macro-scale cortical dynamics to behavioral performance, we hypothesized that traveling wave like cross-areal interactions play a role in integrating the three communicative components. To test this hypothesis, we recorded whole-cortical activity using epidural electrocorticography (ECoG) while subject marmosets vocally interacted with partners. We found theta-band activation in several cortical areas, including the parietal and auditory cortices, while listening to partners calls. This activity was further modulated depending on whether the subjects engaged in vocal interactions, potentially representing the transformation of sensory processing into decision-making and vocal motor preparation. Given the widespread nature of this modulation, we next characterized whole-brain activity patterns by employing a novel analytical method, Weakly Orthogonal Conjugate Contrast Analysis (WOCCA). This analysis revealed that cortical activity could be decomposed into two distinct traveling wave like propagation patterns, a rotational and a translational wave, and both waves discriminated communicative conditions consistent with localized activity. The rotational wave further represented vocal motor preparation through trigger-like temporal pattern. In addition, the magnitude of the translational wave immediately before subjects vocal production correlated with the vocal production-induced suppression of high-gamma-band activity, particularly in the prefrontal and auditory cortices. As vocalization-induced suppression is believed to reflect sensory prediction, the translational wave may propagate specific decision-related or acoustic information necessary for subsequent vocal production to local cortical areas. These findings suggest that the brain orchestrates the sequential cognitive processes underlying vocal communication through macro-scale traveling waves.

Adeno-associated viral (AAV) vectors are foundational tools for dissecting brain structure-function relationships, but AAV serotype tropism varies across brain regions and species, requiring empirical validation to inform experimental design. This need is especially important in non-model organisms, where molecular neuroscience tools remain underdeveloped and access to research subjects is often limited. The Arctic ground squirrel (AGS, Urocitellus parryii) is a valuable model for studying extreme physiology, including metabolic suppression during hibernation and resistance to cerebral ischemia/reperfusion, yet no studies have evaluated AAV performance in the AGS brain. Here, we investigated the ability of AAV serotypes 1, 8, 9, and DJ to transduce the AGS hypothalamus using the human synapsin (hSyn) promoter and directly compared cellular transduction rates in a region implicated in thermoregulation and hibernation. To maximize data collection from a limited experimental population, we used a within-animal, contralateral stereotaxic injection design. Recombinant AAV vectors expressing enhanced green fluorescent protein or mCherry were delivered bilaterally, and reporter expression was analyzed four weeks later. All tested serotypes produced clear and reproducible reporter expression, establishing AAV as a viable molecular tool in the AGS hypothalamus. AAV1 produced significantly greater cellular transduction rates than AAV-DJ (17.2% {+/-} 3.5% vs 8.4% {+/-} 2.9%, paired t-test, p = 0.032). AAV8 and AAV9 showed transduction rates of 22.8% {+/-} 0.6% and 20.1% {+/-} 1.5%, respectively; however, with only two biological replicates per serotype, formal statistical comparison was not performed. These findings provide the first direct characterization of AAV-mediated gene delivery in the AGS brain and establish a foundation for future molecular interrogation of hypothalamic circuits in this extreme mammalian hibernator.

The hippocampus and its projection targets constitute hippocampal output circuits that are essential for memory, navigation, and emotional regulation. Although cortical and subcortical regions receiving hippocampal projections have been well characterized, it remains unclear how hippocampal signals are processed within these projection target regions. To precisely understand information processing in hippocampal output circuits, it is therefore important to gain genetic access to neuronal subpopulations receiving direct hippocampal inputs for structural and functional analyses. Anterograde transsynaptic transduction using adeno-associated virus (AAV) serotype 1 has emerged as a powerful approach for targeting postsynaptic neurons, but its application is limited by unintended retrograde transport, which leads to false-positive labeling in reciprocally connected circuits. Here, we developed a direction-selective anterograde transsynaptic transduction by combining AAV vectors with distinct infection properties and an intersectional gene expression system. Using the hippocampal-entorhinal circuit, we identified an optimal viral combination that enables predominantly anterograde transsynaptic labeling. We further applied this method to map hippocampal projections to reciprocally connected regions, including the amygdala, providing a robust approach for dissecting complex hippocampal output circuits.

When three cyanobacterial proteins--KaiA, KaiB, and KaiC--are incubated with ATP in vitro, the phosphorylation level of KaiC exhibits stable circadian oscillations. Biochemical and structural analyses have shown that KaiCs ATPase activity is crucial for these oscillations, leading to the hypothesis that ATP-consuming dynamics function as a molecular clock, determining the oscillation period of individual molecules. Moreover, these molecular clocks synchronize with one another, resulting in collective oscillations at the ensemble level. In this study, we develop a theoretical model to test this molecular clockwork hypothesis. Our model clarifies the relationship between the oscillation period and ATPase activity, explaining the significant changes in the period induced by amino-acid substitutions near the CI-CII domain boundary of the KaiC hexamer. Furthermore, the model addresses the physical basis for temperature compensation concerning both the oscillation period and ATPase activity. Thus, the molecular clockwork perspective provides a framework for understanding the atomic design behind collective oscillations.

The phenomenon of splitting was originally observed in hamsters which, after prolonged exposure to constant light, exhibit two rest/wake cycles within a subjective day. Splitting is a consequence of the left and right suprachiasmatic nuclei (SCN) falling out of synchrony. While it is known that split activity is characterized by an antiphase relationship between the left and right SCN and between the core and shell within each hemisphere, the role of the commissural projections that connect the right and left SCN is not known. In the present study, we investigate the impact of the inter-hemispheric connections on the split and unsplit dynamics of a computational model of the bilateral SCN. Our model has 4 nodes corresponding to each right and left core and shell. We simulated our bilateral model under different lighting conditions and measured its period and the phase relationships among the 4 nodes. To further characterize the dynamics of the system, we performed a bifurcation analysis. We found that the bilateral model automatically splits unless entrained by bright light/dark cycles, or unless it has excitatory inter-hemispheric connections. This suggests that excitatory cross-connections may be important for freerunning behavior. We found that constant light of varying intensities transitions the model between split and unsplit activity only in very limited conditions, but the strength and polarity of the contralateral connections play a much greater role in this dynamical transition. These findings suggest that splitting may involve plasticity of the inter-hemispheric connections of the SCN.

The acquisition of sensorimotor skills critically depends on basal ganglia (BG)-thalamo-cortical circuits. Prevailing theories propose that the BG optimize motor output through reinforcement learning (RL), using internal performance evaluations to approximate stochastic gradient ascent. However, this framework struggles in non-convex performance landscapes, where local optima hinder efficient learning. Songbirds provide a compelling biological example of robust sensorimotor learning, mastering complex vocalizations through trial-and-error within a specialized BG-thalamo-cortical architecture. Here, we present a computational model constrained by the anatomy, physiology, and developmental trajectory of the zebra finch song system. The model combines a BG-driven RL pathway with a parallel cortical motor pathway that progressively consolidates successful motor patterns via Hebbian plasticity. In addition, we incorporate synaptic volatility within the BG pathway, introducing structured variability across learning. Through simulations of vocal learning using both a biophysical syrinx model and synthetic performance landscapes, we demonstrate that this dual-pathway architecture reliably converges to global optima and outperforms standard and noise-annealed RL approaches. The model reproduces key experimental features of song learning, including non-monotonic learning trajectories, a gradual reduction in motor variability, and the developmental transfer of motor control from subcortical to cortical circuits. Mechanistically, delayed maturation of the cortical pathway provides an implicit regulation of the exploration-exploitation trade-off, while synaptic volatility enables escape from local optima. These results highlight the importance of neural circuit architecture and dynamics in efficient learning, and suggest biologically inspired design principles for improving the robustness and sample efficiency of artificial RL systems in complex sensorimotor domains.