Structure and Function of a Cubic Millimeter of Cortex: Crowdsourcing for Proofreading and Discovery
Structure and Function of a Cubic Millimeter of Cortex: Crowdsourcing for Proofreading and Discovery
批准号:
10025901
负责人:
Hyunjune SEBASTIAN SEUNG
金额:
$635.05万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-08-20 至 2024-08-19
关键词:
3-DimensionalAreaArtificial IntelligenceBrainCalciumCaringCellular biologyClassificationCodeCommunitiesComputer softwareContinuing EducationDataData SetDependenceDetectionEducational workshopElectron MicroscopyEngineeringEventFundingFutureHandHumanImageInfrastructureKnowledgeLearningLocationMachine LearningMental disordersMusNeurogliaNeuronsPythonsReproducibilityResearch PersonnelResourcesScienceSourceStimulusStructureSynapsesSystemTrainingUpdateVisualVisual CortexVisualizationWorkautomated algorithmautomated segmentationbasecell typecognitive loadconnectomecrowdsourcingdeep learningdesignheuristicsimaging Segmentationimprovedlarge datasetsmicroscopic imagingmillimetermouse modelonline communitypeerprogramsreconstructionrecruitresponsetoolvisual codingvolunteer
中文摘要
点击翻译按钮获取中文摘要
英文摘要
At the end of 2020, the IARPA MICrONS program will conclude with an automated reconstruction of all
neurons in a cubic millimeter of mouse visual cortex, along with the neurons’ synaptic connectivity and
calcium-imaged responses to video stimuli. We believe that this dataset could become the most widely used
resource in the field of cortical circuits, but more work is required to realize this potential. We propose to create
an online community called Pyr (pronounced “peer”) that takes the result of MICrONS as its starting point.
We propose to detect and correct the remaining errors in the automated segmentation through automated
algorithms and human proofreading working in tandem. Automated error detection and correction will utilize
hand-designed heuristics as well as deep learning and deep metric learning. Proofreading will be
crowdsourced to nonscientist volunteers, a concept pioneered by Eyewire, but updated to handle a 1000x
larger dataset and far more accurate artificial intelligence. We expect that Pyr will generate more cortical
connections than any previous study, by orders of magnitude. This information will be accompanied by
calcium-imaged visual responses of 80,000 neurons. With such an enormous and rich dataset, the primary
bottleneck will become scientific discovery. We propose to crowdsource discovery by assembling a community
of researchers who collaborate with Pyr and each other. Discovery infrastructure will include a “Science API”
that allows programmatic access to the primary and derived data through Python functions, an automated
system for “materializing” the connectome that makes the result of proofreading available to researchers with
essentially zero delay, and a versioning system will insure that analyses are reproducible. We will create a
framework enabling the community to contribute their own kinds of annotations, which will be included in
materialization. Finally, we will build interactive discovery tools that couple Science API queries with
visualization. We envision a community of researchers who will build upon the above discovery infrastructure,
creating and sharing analysis tools of their own. They will investigate diverse questions about cortical structure
and function, including many that we cannot foresee at all. In the future, Pyr could incorporate other cortical
datasets as they become available, with much less engineering effort than the original MICrONS dataset. As
with MICrONS, software will be developed in the open in public github repos. This software could be reused by
others to build systems similar to Pyr.
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DOI:
10.1038/s41592-021-01330-0
发表时间:
2022-01
期刊:
Nature methods
影响因子:
48
作者:
[Dorkenwald S, McKellar CE, Macrina T, Kemnitz N, Lee K, Lu R, Wu J, Popovych S, Mitchell E, Nehoran B, Jia Z, Bae JA, Mu S, Ih D, Castro M, Ogedengbe O, Halageri A, Kuehner K, Sterling AR, Ashwood Z, Zung J, Brittain D, Collman F, Schneider-Mizell C, Jordan C, Silversmith W, Baker C, Deutsch D, Encarnacion-Rivera L, Kumar S, Burke A, Bland D, Gager J, Hebditch J, Koolman S, Moore M, Morejohn S, Silverman B, Willie K, Willie R, Yu SC, Murthy M, Seung HS]
通讯作者:
Seung HS
DOI:
10.1016/j.cell.2022.01.023
发表时间:
2022-03-17
期刊:
CELL
影响因子:
64.5
作者:
[Turner, Nicholas L., Macrina, Thomas, Bae, J. Alexander, Yang, Runzhe, Wilson, Alyssa M., Schneider-Mizell, Casey, Lee, Kisuk, Lu, Ran, Wu, Jingpeng, Bodor, Agnes L., Bleckert, Adam A., Brittain, Derrick, Froudarakis, Emmanouil, Dorkenwald, Sven, Collman, Forrest, Kemnitz, Nico, Ih, Dodam, Silversmith, William M., Zung, Jonathan, Zlateski, Aleksandar, Tartavull, Ignacio, Yu, Szi-chieh, Popovych, Sergiy, Mu, Shang, Wong, William, Jordan, Chris S., Castro, Manuel, Buchanan, JoAnn, Bumbarger, Daniel J., Takeno, Marc, Torres, Russel, Mahalingam, Gayathri, Elabbady, Leila, Li, Yang, Cobos, Erick, Zhou, Pengcheng, Suckow, Shelby, Becker, Lynne, Paninski, Liam, Polleux, Franck, Reimer, Jacob, Tolias, Andreas S., Reid, R. Clay, da Costa, Nuno Macarico, Seung, H. Sebastian]
通讯作者:
Seung, H. Sebastian
DOI:
10.1038/s41467-023-44354-0
发表时间:
2024-01-04
期刊:
NATURE COMMUNICATIONS
影响因子:
16.6
作者:
[Popovych, Sergiy, Macrina, Thomas, Kemnitz, Nico, Castro, Manuel, Nehoran, Barak, Jia, Zhen, Bae, J. Alexander, Mitchell, Eric, Mu, Shang, Trautman, Eric T., Saalfeld, Stephan, Li, Kai, Seung, H. Sebastian]
通讯作者:
Seung, H. Sebastian
DOI:
10.7554/elife.73783
发表时间:
2021-12-01
期刊:
eLife
影响因子:
7.7
作者:
[Schneider-Mizell CM, Bodor AL, Collman F, Brittain D, Bleckert A, Dorkenwald S, Turner NL, Macrina T, Lee K, Lu R, Wu J, Zhuang J, Nandi A, Hu B, Buchanan J, Takeno MM, Torres R, Mahalingam G, Bumbarger DJ, Li Y, Chartrand T, Kemnitz N, Silversmith WM, Ih D, Zung J, Zlateski A, Tartavull I, Popovych S, Wong W, Castro M, Jordan CS, Froudarakis E, Becker L, Suckow S, Reimer J, Tolias AS, Anastassiou CA, Seung HS, Reid RC, Costa NMD]
通讯作者:
Costa NMD
CAVE: Connectome Annotation Versioning Engine.
CAVE:连接体注释版本控制引擎。
DOI:
10.1101/2023.07.26.550598
发表时间:
2023
期刊:
bioRxiv : the preprint server for biology
影响因子:
--
作者:
[Dorkenwald,Sven, Schneider-Mizell,CaseyM, Brittain,Derrick, Halageri,Akhilesh, Jordan,Chris, Kemnitz,Nico, Castro,ManualA, Silversmith,William, Maitin-Shephard,Jeremy, Troidl,Jakob, Pfister,Hanspeter, Gillet,Valentin, Xenes,Daniel, Bae,JA]
通讯作者:
Bae,JA
Data Science Core
-
批准号:10247579
-
项目类别:
-
资助金额:$45.41万
-
财政年份:2017
-
负责人:Hyunjune SEBASTIAN SEUNG
-
依托单位:
Project 4: Neuronal Interactions
-
批准号:10247571
-
项目类别:
-
资助金额:$36.45万
-
财政年份:2017
-
负责人:Hyunjune SEBASTIAN SEUNG
-
依托单位:
Data Science Core
-
批准号:9983197
-
项目类别:
-
资助金额:$45.41万
-
财政年份:2017
-
负责人:Hyunjune SEBASTIAN SEUNG
-
依托单位:
Project 4: Neuronal Interactions
-
批准号:9983182
-
项目类别:
-
资助金额:$37.34万
-
财政年份:2017
-
负责人:Hyunjune SEBASTIAN SEUNG
-
依托单位:
Retinal connectome: mobile game and crowdsourcing algorithms for EyeWire II
-
批准号:9330810
-
项目类别:
-
资助金额:$32.09万
-
财政年份:2016
-
负责人:Hyunjune SEBASTIAN SEUNG
-
依托单位:
Retinal connectome: mobile game and crowdsourcing algorithms for EyeWire II
-
批准号:9076876
-
项目类别:
-
资助金额:$32.09万
-
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负责人:Hyunjune SEBASTIAN SEUNG
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依托单位:
Plasticity of the Human Oculomotor Integrator through Real-Time Visual Feedback
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批准号:7017281
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项目类别:
-
资助金额:$8.24万
-
财政年份:2006
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负责人:Hyunjune SEBASTIAN SEUNG
-
依托单位:
MECHANISMS OF PERSISTENT NEURAL ACTIVITY
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批准号:6528606
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项目类别:
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资助金额:$27.3万
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财政年份:2000
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负责人:Hyunjune SEBASTIAN SEUNG
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财政年份:2000
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负责人:Hyunjune SEBASTIAN SEUNG
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MECHANISMS OF PERSISTENT NEURAL ACTIVITY
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批准号:6796155
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项目类别:
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资助金额:$30.66万
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财政年份:2000
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财政年份:2000
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负责人:Hyunjune SEBASTIAN SEUNG
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批准号:9444133
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资助金额:$36.45万
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财政年份:--
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负责人:Hyunjune SEBASTIAN SEUNG
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资助金额:$45.41万
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