BrainViewer: interacting with spatial connectome data at the mesoscale
Scientists construct connectomes, comprehensive descriptions of neuronal connections across a brain, in order to better understand and model brain function. Interactive visualizations of these pathways would enable exploratory analysis of such information flows. Current tools can be used to see individual tracing experiments which are used to build mesoscale connectomes of the mouse brain, but not the brain network itself. We present a connectivity visualization program called BrainViewer, which we use with a high-resolution mouse cortical connectome. This has the ability to display connectomes from other datasets when they become available and compare spatial connectivity across multiple brain structures. Our tool, optimized for speed and portability, presents a GUI visualization in 2-D top view and flatmap projections, allowing users to select and explore the connections of every source voxel to everywhere else in the cortex. Anatomists and other neuroscientists will find BrainViewer useful for building understanding beyond the known topography of cortical connectivity.
Code (1)
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Data-driven Mesoscale Weather Forecasting Combining Swin-Unet and Diffusion Models
Data-driven weather prediction models exhibit promising performance and advance continuously. In particular, diffusion models represent fine-scale details without spatial smoothing, which is crucial for mesoscale predict…
Weather ForecastingDiscovering mesoscopic descriptions of collective movement with neural stochastic modelling
Collective motion is an ubiquitous phenomenon in nature, inspiring engineers, physicists and mathematicians to develop mathematical models and bio-inspired designs. Collective motion at small to medium group sizes ($\sim…
Topology of the mesoscale connectome of the mouse brain
The wiring diagram of the mouse brain has recently been mapped at a mesoscopic scale in the Allen Mouse Brain Connectivity Atlas. Axonal projections from brain regions were traced using green fluoresent proteins. The res…
Navigable maps of structural brain networks across species
Connectomes are spatially embedded networks whose architecture has been shaped by physical constraints and communication needs throughout evolution. Using a decentralized navigation protocol, we investigate the relations…
AnatomyDisease Prediction based on Functional Connectomes using a Scalable and Spatially-Informed Support Vector Machine
Substantial evidence indicates that major psychiatric disorders are associated with distributed neural dysconnectivity, leading to strong interest in using neuroimaging methods to accurately predict disorder status. In t…
Data AugmentationDisease Predictionfeature selection