Biology subjects

Yamane, Y.

Publications and source records attributed to Yamane, Y..

5 recordsLinked to original sources

bioRxiv2026

Pan-cortical area sensorimotor network coordination during motor learning of forelimb-reaching task in the marmoset

Motor learning alters activities in multiple brain areas. While learning-induced activity change in these areas has been investigated, how the information flow changes in the network across those areas remains to be thoroughly examined. We analysed wide-field calcium imaging data spanning from the premotor cortex to the parietal cortex of marmosets while they learned a two-target forelimb-reaching task. We applied non-negative matrix factorization (NMF) to the activity data and extracted about 30 localized activity components. Encoding model analysis indicated that learning was associated with a decrease in activity components related to hand movements, and an increase in those related to external and reward signals. Causality analysis by embedding entropy (EE) revealed increases in causal links across activity components in different areas and stabilization of the network structure with behavioural improvements. These results indicate that motor learning entails both a redistribution of task-related activity and a reorganization of large-scale cortical network interactions.

neuroscience↗

bioRxiv2025

Graph topology reframes the coherence of cell-state manifold inference under heterogeneous single-cell observations

Manifold-based single-cell omics analyses assume that high-dimensional observations can fall into a low-dimensional space encoding biological constraints. In practice, per-cell observation is highly heterogeneous: shallowly- and deeply-observed cells coexist. In an empirical scRNA-seq dataset, shallowly-observed cells cluster together to generate spurious hubs that can give rise to illusory loops in low-dimensional manifold skeletons in graph abstraction. Several imputation methods leave these artifacts largely intact, whereas graph abstraction restricted to homogeneously-observed cells alone recovers tree-like structures locally representing constrained cell state transitions. Simulations further demonstrate that realistic heterogeneous observation can create spurious subclusters and false branching. Grounded by these observations, we propose topological stability descriptors of low-dimensional manifold skeletons to delineate a regime in which manifold-based inference is trustworthy despite realistic heterogeneous observations. Our findings underscore that the heterogeneity of observations is not merely noise but a source of systemic distortion in manifold-based inference that must be addressed.

bioinformatics↗

bioRxiv2024

Optical Neuroimage Studio (OptiNiSt): intuitive, scalable, extendable framework for optical neuroimage data analysis

Advancements in calcium indicators and optical techniques have made optical neural recording a common tool in neuroscience. As the volume of optical neural recording data grows, streamlining the data analysis pipelines for image preprocessing, signal extraction, and subsequent neural activity analyses becomes essential. There are a number of challenges in optical neural data analysis. 1) The quality of original and processed data needs to be carefully examined at each step. 2) As there are numerous image preprocessing, cell extraction, and activity analysis algorithms, each with pros and cons, experimenters need to implement or install them to compare and select optimal methods and parameters for each step of processing. 3) To ensure the reproducibility of the research, each analysis step needs to be recorded in a systematic way. 4) For data sharing and meta-analyses, adoption of standard data formats and processing protocols is required. To address these challenges, we developed Optical Neuroimage Studio (OptiNiSt) (https://github.com/oist/optinist), a framework for intuitively creating calcium data analysis pipelines that are scalable, extendable, and reproducible. OptiNiSt includes the following features. 1) Researchers can easily create analysis pipelines by selecting multiple processing modules, tuning their parameters, and visualizing the results at each step through a graphic user interface in a web browser. 2) In addition to common analytical tools that are pre-installed, new analysis algorithms in Python can be easily added. 3) Once a processing pipeline is designed, the entire workflow with its modules and parameters are stored in a YAML file, which makes the pipeline reproducible and deployable on high-performance computing clusters. 4) OptiNiSt can read image data in a variety of file formats and store the analysis results in NWB (Neurodata Without Borders), a standard data format for data sharing. We expect that this framework will be helpful in standardizing optical neural data analysis protocols.

neuroscience↗

bioRxiv2024

Characterization of a Unique Spontaneous Calcifying Cell Line (CJ): a Novel Tool for the Study of Ectopic Calcification

PurposeDue to the lack of an appropriate in vitro evaluation system, there is no effective prevention or treatment for ectopic calcification diseases (ECD). We obtained canine renal adenocarcinoma cells (CJ cells) that spontaneously form large amounts of calcified precipitates (CaP-ppt) and examined whether they could serve as a model for the early stages of ectopic calcification (EC). MethodsDispersed cells obtained by collagenase-DNase digestion were cultured in 10% FBS, antibiotic-containing DMEM-high glucose medium (standard medium). CaP-ppt was stained with Alizarin Red (AR) and colorimetrically quantified after acid extraction. Cell volume was determined by Crystal violet (CV) staining followed by extraction and colorimetric quantification. Calcium (Ca) and phosphate (PO4) were determined with a commercial kit to obtain the Ca/P ratio. Screening of anti-CaP-ppt compounds was performed in the same 96-well plate in the order of cell culture {Rightarrow} CaP-ppt quantification {Rightarrow} cell quantification and evaluated by IC50 value. ResultsCJ cells produced large amounts of CaP-ppt on standard medium alone without external phosphate addition; CaP-ppt formation was not accompanied by cell death, but on the contrary, CaP-ppt increased at physiological pH values around pH 7.4 due to active cell metabolism. The Ca2+ and PO43- partitioning kinetics to CaP-ppt were found, and the Ca/P ratio of CaP-ppt was stable at 1.35. The anti-Cap-ppt effects of bisphosphonates and all-trans retinoic acid (ATRA) were also confirmed in this CJ cell CaP-ppt system. DiscussionThere was doubt about the vascular calcifying cell model with the addition of high concentrations of phosphoric acid, but there were no suitable alternative cells. Spontaneously calcifying CJ cells provide a fundamental solution to this problem. Anti-CaP-ppt screening also eliminates the need for medium exchange, thus saving labor and cost. The Ca/P ratio of CaP-ppt in CJ cells is 1.35, the same as that of amorphous Ca phosphate (ACP), corresponding to the early (reversible) stage of EC. Therefore, it has favorable conditions as an evaluation system for drug discovery. ConclusionCJ cells, which calcify at physiological phosphate concentrations (0.9 mM) in standard media, are useful and novel research material for basic and preventive studies of ECD and for drug development studies.

cell biology↗

bioRxiv2016

Neurons in the inferior temporal cortex of macaque monkeys are sensitive to multiple surface features from natural objects

Object surfaces contain a variety of visual features that help us to recognize them. To understand how this information is represented and processed in the brain, we prepared a set of images from natural object surfaces that maintained surface features but lacked contours. We examined spiking responses of neurons in the inferior temporal (IT) cortex of monkeys, which is a crucial structure needed for visual object recognition. About half of IT neurons responded to surface images with sharp selectivity, indicating that a significant fraction of these neurons contribute to object surface representation in a sparse manner. Responses of IT neurons were susceptible to image manipulations, including color removal, removal of luminance contrasts, and spatial structure degradation. This shows that multiple features are required for IT responses to surface images. Comparing neuronal response properties among IT, visual area 4 (V4), and primary visual cortex (V1) revealed properties of IT neurons that differed from those in the other visual processing regions. Additionally, some neuronal response properties were similar between IT and V4, but differed from those in V1, indicating that responses of IT neurons to surface images are constructed by hierarchical processing throughout the ventral visual pathway.

neuroscience↗