Cellular-resolution connectomics: challenges of dense neural circuit reconstruction

Helmstaedter, Moritz

doi:10.1038/nmeth.2476

Cited by 274 publications

(235 citation statements)

References 42 publications

Supporting

Mentioning

227

Contrasting

Unclassified

Order By: Relevance

“…This Massive Open Laboratory template could be generalized to a broad class of biomolecule design problems, including mechanistic dissection of current design rules (26), modeling of pseudoknots, engineering of RNA switches for cellular control (5,6), and 3D modeling and design, all assessed by high-throughput mapping (1,7,16,20,29,30). Other fields, such as taxonomy (31), astronomy (13), and neural mapping (32), are making pioneering efforts in internet-scale scientific discovery games. Our Massive Open Laboratory results suggest that integrating timely player-proposed experiments as part of the standard game play will be worthwhile challenges for such projects.…”

Section: Discussionmentioning

confidence: 99%

RNA design rules from a massive open laboratory

Lee¹,

Kladwang²,

Lee³

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

290

234

View full text Add to dashboard Cite

Significance Self-assembling RNA molecules play critical roles throughout biology and bioengineering. To accelerate progress in RNA design, we present EteRNA, the first internet-scale citizen science “game” scored by high-throughput experiments. A community of 37,000 nonexperts leveraged continuous remote laboratory feedback to learn new design rules that substantially improve the experimental accuracy of RNA structure designs. These rules, distilled by machine learning into a new automated algorithm EteRNABot, also significantly outperform prior algorithms in a gauntlet of independent tests. These results show that an online community can carry out large-scale experiments, hypothesis generation, and algorithm design to create practical advances in empirical science.

show abstract

Section: Discussionmentioning

confidence: 99%

RNA design rules from a massive open laboratory

Lee¹,

Kladwang²,

Lee³

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

290

234

View full text Add to dashboard Cite

show abstract

“…Microscale studies of structural connectivity depend on the development of techniques for automated histology (electron microscopy or light microscopy) and reconstruction that combine sensitivity with scalability (Kleinfeld et al 2011;Helmstaedter et al 2011;Helmstaedter 2013). While these techniques have not yet delivered any whole-brain wiring diagrams for complex organisms, they have been successfully deployed to map specific circuits in both invertebrate and vertebrate nervous systems.…”

Section: Microscalementioning

confidence: 99%

Micro-, Meso- and Macro-Connectomics of the Brain

Kennedy¹,

Essen²,

Christen³

2016

Research and Perspectives in Neurosciences

View full text Add to dashboard Cite

“…While this is still a major challenge for large animals such as primates (Helmstaedter 2013), acquisition of single-cell level connectomes for small animals, such as the Drosophila melanogaster (fruit fly), has seen rapid progress (Chiang et al 2011;Takemura et al 2013;Shinomiya et al 2011). Therefore, we suggest that the Drosophila is currently one of the best model animals for developing a high-resolution full brain computational model due to the availability of extensive neuron databases and neuroinformatics tools (Chiang et al 2011;Shinomiya et al 2011;Osumi-Sutherland et al 2012;Parekh and Ascoli 2013;Ukani et al fly brain may enable us to investigate how different subsystems in the brain integrate and how high-level behavior is carried out.…”

Section: Introductionmentioning

confidence: 99%

A single-cell level and connectome-derived computational model of the Drosophila brain

Huang

Wang

et al. 2018

Preprint

View full text Add to dashboard Cite

Computer simulations play an important role in testing hypotheses, integrating knowledge, and providing predictions of neural circuit functions. While considerable effort has been dedicated into simulating primate or rodent brains, the fruit fly (Drosophila melanogaster) is becoming a promising model animal in computational neuroscience for its small brain size, complex cognitive behavior, and abundancy of data available from genes to circuits.Moreover, several Drosophila connectome projects have generated a large number of neuronal images that account for a significant portion of the brain, making a systematic investigation of the whole brain circuit possible. Supported by FlyCircuit (http://www.flycircuit.tw), one of the largest Drosophila neuron image databases, we began a long-term project with the goal to construct a whole-brain spiking network model of the Drosophila brain. In this paper, we report the outcome of the first phase of the project. We developed the Flysim platform, which 1) identifies the polarity of each neuron arbor, 2) predicts connections between neurons, 3) translates morphology data from the database into physiology parameters for computational modeling, 4) reconstructs a brain-wide network model, which consists of 20,089 neurons and 1,044,020 synapses, and 5) performs computer simulations of the resting state. We compared the reconstructed brain network with a randomized brain network by shuffling the connections of each neuron. We found that the reconstructed brain can be easily stabilized by implementing synaptic short-term depression, while the randomized one exhibited seizure-like firing activity under the same treatment.Furthermore, the reconstructed Drosophila brain was structurally and dynamically more diverse than the randomized one and exhibited both Poisson-like and patterned firing activities. Despite being at its early stage of development, this single-cell level brain model allows us to study some of the fundamental properties of neural networks including network balance, critical behavior, long-term stability, and plasticity.All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

show abstract

Cellular-resolution connectomics: challenges of dense neural circuit reconstruction

Cited by 274 publications

References 42 publications

RNA design rules from a massive open laboratory

RNA design rules from a massive open laboratory

Micro-, Meso- and Macro-Connectomics of the Brain

A single-cell level and connectome-derived computational model of the Drosophila brain

Contact Info

Product

Resources

About