Biology subjects

Nakae, K.

Publications and source records attributed to Nakae, K..

10 recordsLinked to original sources

bioRxiv2026

A multimodal dataset for reconstructing common marmoset body-environment interactions in a 3D digital-twin framework

The common marmoset (Callithrix jacchus) is an important non-human primate model in neuroscience and biomedical research. However, existing 3D resources for this species have mainly focused on brain atlases or keypoint-based pose estimation, and reusable data resources that jointly describe the body surface, fur, articulated structure, and experimental environment remain limited. Here, we present a multimodal dataset designed to reconstruct body- environment interactions of common marmosets in three dimensions. The dataset includes a whole-body surface mesh derived from computed tomography (CT) images, fur representations based on photographic references, a rigged 3D model for pose-driven animation, synchronized behavioral videos from three individuals recorded for approximately 90 hours from eight view-points, 2D and 3D keypoint estimation data, 3D models of the experimental environment constructed from blueprint information, and rendered pseudo-egocentric views generated by integrating pose estimation results with the 3D body and environment models. Technical validation assessed the geometric agreement between the CT-derived mesh and the surface model, the accuracy of 2D and 3D keypoint estimation, the dimensional accuracy of the environment model, and the structural similarity between real and rendered images. This dataset provides a foundation for treating marmoset natural behavior not only as point trajectories but also as a three-dimensional phenomenon involving body shape and its spatial relationship with the environment, thereby enabling applications in behavioral analysis, visualization, synthetic-data generation, and future digital-twin studies.

animal behavior and cognition↗

bioRxiv2025

The Brain/MINDS 3D Digital Marmoset Brain Atlas Version 2.0: Population-based Cortical Region Parcellations with Multi-Modal Standard Templates

We present our new Brain/MINDS 3D digital marmoset brain atlas version 2.0 (BMA2.0), a population-based 3D digital brain atlas of the common marmoset (Callithrix jacchus), designed to overcome the limitations of previous single subject atlases that are prone to structural biases arising from individual variation. Here, manually delineated cortical regions from 10 myelin-stained brains were used to create a generalized cortical parcellation. Newly refined subcortical regions from a previous atlas and a completely new cerebellum parcellation were also incorporated, resulting in a comprehensive whole brain parcellation for both hemispheres. To facilitate multimodal data analysis, the atlas package includes co-registered average templates for myelin and Nissl staining from the same individuals, ex vivo MRI T2 (91 individuals), and in vivo MRI T2 (446 individuals). Cortical flat maps and pial, cortical mid-thickness, and white matter surfaces are also provided. BMA2.0 provides a central brain space for multimodal data integration, spatial analysis, and comparative neuroscience. Standard formats and transformations are provided for easy integration into existing workflows and interoperability with existing atlases.

neuroscience↗

bioRxiv2025

A multimodal dataset linking wide-field calcium imaging to behavior changes in mice during an operant lever-pull task

The BraiDyn-BC (Brain Dynamics underlying emergence of Behavioral Change) Database offers an extensive, multimodal dataset that links wide-field calcium imaging of the mouse neocortex to comprehensive behavioral measurements during a behavioral task. As one of the contents in this database, we newly provide a dataset that includes 15 sessions spanning two weeks of motor skill learning, in which 25 mice were trained to pull a lever to obtain water rewards. Simultaneous high-speed videography captures body, facial, and eye movements, and environmental parameters are monitored. The dataset also features resting-state cortical activity and sensory-evoked responses, enhancing its utility for both learning-related and sensory-driven neural dynamics studies. Data are formatted in accordance with the Neurodata Without Borders (NWB) standard, ensuring compatibility with existing analysis tools and adherence to the FAIR principles. This resource enables in-depth investigations into the neural mechanisms underlying behavior and learning. The platform encourages collaborative research, supporting the exploration of rapid within-session learning effects, long-term behavioral adaptations, and neural circuit dynamics.

neuroscience↗

bioRxiv2023

Epileptic responses in marmosets induced by knockdown of CREB Regulated Transcription Coactivator 1 (CRTC1)

Animal models have contributed greatly to the development of anticonvulsant drugs. However, 20-30% of epilepsy patients still do not achieve adequate seizure control. It is important to understand the biological mechanisms of epilepsy in order to develop treatments and novel anticonvulsant drugs. Here we report CRTC1 knockdown (KD) induced abnormal cFOS expression beyond the injection sites followed by epileptic response by three local injections of short hairpin RNA (shRNA) in marmoset V1. Longitudinal monitoring of cortical-wide neural activity revealed transient changes in high frequency oscillations by cortical electrocorticography throughout the cortex, and a lesion in the temporal lobe was observed by MRI and postmortem histology. shCRTC1 KD marmosets showed severe lesions surrounding the injection site several months after injection. Glial cell activation may occur simultaneously or prior to IEG induction after shCRTC1 injection. Thus, the epileptic process from seizure onset to remission can be studied in this animal model.

neuroscience↗

bioRxiv2022

Multi-modal brain magnetic resonance imaging database covering marmosets with a wide age range

Magnetic resonance imaging (MRI) is a noninvasive neuroimaging method beneficial for the identification of normal developmental and aging processes and data sharing. Marmosets have a relatively shorter life expectancy (approximately 10 years) than other primates, including, humans because they grow and age faster. Hence, the common marmoset model is effective in aging research. The current study investigated the aging process of the marmoset brain and provided an open MRI database on marmosets with a wide age range. The Brain/MINDS Marmoset Brain MRI Dataset contains brain MRI information on 216 marmosets aged between 1 and 10 years. During its release date, it is the largest public dataset worldwide. Further, it comprises multi contrast MRI images. In addition, 91 of 216 animals have corresponding ex vivo high-resolution MRI datasets. Our MRI database, which is available at the Brain/MINDS Data portal might help understand the effects of different factors, such as age, sex, body size, and fixation, on the brain. Moreover, it can contribute to and accelerate brain science studies worldwide.

neuroscience↗

bioRxiv2022

The Brain/MINDS Marmoset Connectivity Atlas: Exploring bidirectional tracing and tractography in the same stereotaxic space

We report on the implementation and features of the Brain/MINDS Marmoset Connectivity Atlas, BMCA, a new resource that provides access to anterograde neuronal tracer data in the prefrontal cortex of a marmoset brain. Neuronal tracers combined with fluorescence microscopy are a key technology for the systematic mapping of structural brain connectivity. We selected the prefrontal cortex for mapping due to its important role in higher brain functions. This work introduces the BMCA standard image preprocessing pipeline and tools for exploring and reviewing the data. We developed the BMCA-Explorer, which is an online image viewer designed for data exploration. Unlike other existing image explorers, it visualizes the data of different individuals in a common reference space at an unprecedented high resolution, facilitating comparative studies. To foster the integration with other marmoset brain image databases and cross-species comparisons, we added fiber tractography data from diffusion MRI, retrograde neural tracer data from the Marmoset Brain Connectivity Atlas project, and tools to map image data between marmoset and the human brain image space. This version of BMCA allows direct comparison between the results of 52 anterograde and 164 retrograde tracer injections in the cortex of the marmoset.

neuroscience↗

bioRxiv2022

Connectional architecture of the prefrontal cortex in the marmoset brain

Prefrontal cortex (PFC) has dramatically expanded in primates, but its organization and interactions with other brain regions are only partially understood. We performed high-resolution connectomic mapping of marmoset PFC and found two contrasting corticocortical and corticostriatal projection patterns: "patchy" projections that formed many columns of submillimeter scale in nearby and distant regions and "diffuse" projections that spread widely across the cortex and striatum. Parcellation-free analyses revealed representations of PFC gradients in these projections local and global distribution patterns. We also demonstrated column-scale precision of reciprocal cortico-cortical connectivity, suggesting that PFC contains a mosaic of discrete columns. Diffuse projections showed considerable diversity in the laminar patterns of axonal spread. In mice, columnar projections were much less conspicuous, underscoring the importance of the primate model. Altogether, these fine-grained analyses reveal important principles of local and long-distance PFC circuits in marmosets and provide insights into the functional organization of the primate brain.

neuroscience↗

bioRxiv2020

Model-based prediction of spatial gene expression via generative linear mapping

Decoding spatial transcriptomes from single-cell RNA sequencing (scRNA-seq) data has become a fundamental technique for understanding multicellular systems; however, existing computational methods lack both accuracy and biological interpretability due to their model-free frameworks. Here, we introduced Perler, a model-based method to integrate scRNA-seq data with reference in situ hybridization (ISH) data. To calibrate differences between these datasets, we developed a biologically interpretable model that uses generative linear mapping based on a Gaussian-mixture model using the Expectation-Maximization algorithm. Perler accurately predicted the spatial gene expression of Drosophila embryos, zebrafish embryos, mammalian liver, and mouse visual cortex from scRNA-seq data. Furthermore, the reconstructed transcriptomes did not over-fit the ISH data and preserved the timing information of the scRNA-seq data. These results demonstrated the generalizability of Perler for dataset integration, thereby providing a biologically interpretable framework for accurate reconstruction of spatial transcriptomes in any multicellular system.

genomics↗

bioRxiv2019

The NanoZoomer Connectomics Pipeline for Tracer Injection Studies of the Marmoset Brain

We describe our connectomics pipeline for processing tracer injection data for the brain of the common marmoset (Callithrix jacchus). Brain sections were imaged using a batch slide scanner (NanoZoomer 2.0-HT) and we used artificial intelligence to precisely segment the anterograde tracer signal from the background in the fluorescence images. The shape of each brain was reconstructed by reference to a block-face and all data was mapped into a common 3D brain space with atlas and 2D cortical flat map. To overcome the effect of using a single template atlas to specify cortical boundaries, each brain was cytoarchitectonically annotated and used for making an individual 3D atlas. Registration between the individual and common brain cortical boundaries in the flat map space was done to absorb the variation of each brain and precisely map all tracer injection data into one cortical brain space. We describe the methodology of our pipeline and analyze tracer segmentation and brain registration accuracy. Results show our pipeline can successfully process and normalize tracer injection experiments into a common space, making it suitable for large-scale connectomics studies with a focus on the cerebral cortex.

neuroscience↗

bioRxiv2018

System level analyses of motor-related neural activities in larval Drosophila

The way in which the central nervous system (CNS) governs animal movement is complex and difficult to solve solely by the analyses of muscle movement patterns. We tackle this problem by observing the activity of a large population of neurons in the CNS of larval Drosophila. We focused on two major behaviors of the larvae, forward and backward locomotion, and analyzed the neuronal activity related to these behaviors during fictive locomotion that spontaneously occurs in the isolated CNS. We expressed genetically-encoded calcium indicator, GCaMP, and a nuclear marker in all neurons and used digital scanned light-sheet microscopy to record neural activities in the entire ventral nerve cord at a fast frame rate. We developed image processing tools that automatically detect the cell position based on the nuclear staining and allocate the activity signals to each detected cell. We also applied a machine learning-based method that we developed recently to assign motor status in each time frame. Based on these methods, we find cells whose activity is biased to forward versus backward locomotion and vice versa. In particular, we identified a group of neurons near the boundary of subesophageal zone (SEZ) and thoracic neuromeres, which are strongly active during an early phase of backward but not forward fictive locomotion. Our experimental procedure and computational pipeline enable systematic identification of neurons to show characteristic motor activities in larval Drosophila.

neuroscience↗