Collaborative Augmented Reconstruction for Scaled Production of 3D Neuron Morphology in Mouse and Human Brains DOI Creative Commons
Hanchuan Peng, Lingli Zhang, Lei Huang

et al.

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: Oct. 26, 2023

Abstract Digital reconstruction of the intricate 3D morphology individual neurons from microscopic images is widely recognized as a crucial challenge in both research laboratories and large-scale scientific projects focusing on cell types brain anatomy. This task often fails conventional manual state-of-the-art automatic algorithms, even many which are based artificial intelligence (AI). It also critical but challenging to organize multiple neuroanatomists produce cross-validate biologically relevant agreeable reconstructions scaled data production. Here we propose an approach collaborative human augmented by AI. Specifically, have developed Collaborative Augmented Reconstruction (CAR) platform for neuron at scale. allows immersive interaction efficient collaborative-editing anatomy using variety client devices, such desktop workstations, virtual reality headsets, mobile phones, enabling users contribute anytime anywhere take advantage several AI-based automation tools. We tested CAR’s applicability mouse towards faithful Our indicate that CAR suitable generating tens thousands neuronal used our companion studies.

Language: Английский

Developmental mouse brain common coordinate framework DOI Creative Commons

Fae N. Kronman,

Josephine K. Liwang, Rebecca Betty

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Oct. 21, 2024

Abstract 3D brain atlases are key resources to understand the brain’s spatial organization and promote interoperability across different studies. However, unlike adult mouse brain, lack of developing reference hinders advancements in understanding development. Here, we present a developmental common coordinate framework (DevCCF) spanning embryonic day (E)11.5, E13.5, E15.5, E18.5, postnatal (P)4, P14, P56, featuring undistorted morphologically averaged atlas templates created from magnetic resonance imaging co-registered high-resolution light sheet fluorescence microscopy templates. The DevCCF with anatomical segmentations can be downloaded or explored via an interactive web-visualizer. As use case, utilize unveil GABAergic neuron emergence brains. Moreover, map Allen CCFv3 transcriptome cell-type data our stereotaxic P56 atlas. In summary, is openly accessible resource for multi-study integration advance

Language: Английский

Citations

11
Non-homogenous axonal bouton distribution in whole-brain single-cell neuronal networks DOI Creative Commons

Penghao Qian,

Linus Manubens-Gil, Shengdian Jiang

et al.

Cell Reports, Journal Year: 2024, Volume and Issue: 43(3), P. 113871 - 113871

Published: March 1, 2024

We examined the distribution of pre-synaptic contacts in axons mouse neurons and constructed whole-brain single-cell neuronal networks using an extensive dataset 1,891 fully reconstructed neurons. found that bouton locations were not homogeneous throughout axon among brain regions. As our algorithm was able to generate connectivity matrices from full morphology reconstruction datasets, we further non-homogeneous have a significant impact on network wiring, including degree distribution, triad census, community structure. By perturbing morphology, explored link between anatomical details topology. In silico exploration, dendritic axonal tree span would greatest followed by synaptic contact deletion. Our results suggest neuroanatomical must be carefully addressed studies at level.

Language: Английский

Citations

4
Collaborative augmented reconstruction of 3D neuron morphology in mouse and human brains DOI Creative Commons
Lingli Zhang, Lei Huang, Zexin Yuan

et al.

Nature Methods, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 4, 2024

Language: Английский

Citations

2
Non-homogenous axonal bouton distribution in whole-brain single cell neuronal networks DOI Creative Commons

Penghao Qian,

Linus Manubens-Gil, Shengdian Jiang

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Aug. 8, 2023

Summary We examined the distribution of pre-synaptic contacts in axons mouse neurons and constructed whole-brain single-cell neuronal networks using an extensive dataset 1891 fully reconstructed neurons. found that bouton locations were not homogeneous throughout axon also among brain regions. As our algorithm was able to generate connectivity matrices from full morphology reconstruction datasets, we further non-homogeneous have a significant impact on network wiring, including degree distribution, triad census community structure. By perturbing morphology, explored link between anatomical details topology. In silico exploration, dendritic axonal tree span would greatest followed by synaptic contact deletion. Our results suggest neuroanatomical must be carefully addressed studies whole at single cell level.

Language: Английский

Citations

3
Collaborative Augmented Reconstruction for Scaled Production of 3D Neuron Morphology in Mouse and Human Brains DOI Open Access
Lingli Zhang, Lei Huang, Zexin Yuan

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Oct. 7, 2023

Abstract Digital reconstruction of the intricate 3D morphology individual neurons from microscopic images is widely recognized as a crucial challenge in both research laboratories and large-scale scientific projects focusing on cell types brain anatomy. This task often fails conventional manual state-of-the-art automatic algorithms, even many which are based artificial intelligence (AI). It also critical but challenging to organize multiple neuroanatomists produce cross-validate biologically relevant agreeable reconstructions scaled data production. Here we propose an approach collaborative human augmented by AI. Specifically, have developed Collaborative Augmented Reconstruction (CAR) platform for neuron at scale. allows immersive interaction efficient collaborative-editing anatomy using variety client devices, such desktop workstations, virtual reality headsets, mobile phones, enabling users contribute anytime anywhere take advantage several AI-based automation tools. We tested CAR’s applicability mouse towards faithful Our indicate that CAR suitable generating tens thousands neuronal used our companion studies.

Language: Английский

Citations

1
Gossamer: Scaling Image Processing and Reconstruction to Whole Brains DOI Creative Commons

Karl Marrett,

Keivan Moradi,

Chris Sin Park

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: April 9, 2024

Abstract Neuronal reconstruction–a process that transforms image volumes into 3D geometries and skeletons of cells– bottlenecks the study brain function, connectomics pathology. Domain scientists need exact complete segmentations to subtle topological differences. Existing methods are diskbound, dense-access, coupled, single-threaded, algorithmically unscalable require manual cropping small windows proofreading due low accuracy. Designing a data-intensive parallel solution suited neurons’ shape, topology far-ranging connectivity is particularly challenging I/O load-balance, yet by abstracting these vision tasks strategically ordered specializations search, we progressively lower memory 4 orders magnitude. This enables 1 mouse be fully processed in-memory on single server, at 67× scale with 870× less while having 78% higher automated yield than APP2, previous state art in performant reconstruction.

Language: Английский

Citations

0
Collaborative Augmented Reconstruction for Scaled Production of 3D Neuron Morphology in Mouse and Human Brains DOI Creative Commons
Hanchuan Peng, Lingli Zhang, Lei Huang

et al.

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: Oct. 26, 2023

Abstract Digital reconstruction of the intricate 3D morphology individual neurons from microscopic images is widely recognized as a crucial challenge in both research laboratories and large-scale scientific projects focusing on cell types brain anatomy. This task often fails conventional manual state-of-the-art automatic algorithms, even many which are based artificial intelligence (AI). It also critical but challenging to organize multiple neuroanatomists produce cross-validate biologically relevant agreeable reconstructions scaled data production. Here we propose an approach collaborative human augmented by AI. Specifically, have developed Collaborative Augmented Reconstruction (CAR) platform for neuron at scale. allows immersive interaction efficient collaborative-editing anatomy using variety client devices, such desktop workstations, virtual reality headsets, mobile phones, enabling users contribute anytime anywhere take advantage several AI-based automation tools. We tested CAR’s applicability mouse towards faithful Our indicate that CAR suitable generating tens thousands neuronal used our companion studies.

Language: Английский

Citations

0