Automatic discovery of cell types and microcircuitry from neural connectomics
@article{Jonas2015AutomaticDO, title={Automatic discovery of cell types and microcircuitry from neural connectomics}, author={Eric Jonas and Konrad Paul Kording}, journal={eLife}, year={2015}, volume={4} }
Neural connectomics has begun producing massive amounts of data, necessitating new analysis methods to discover the biological and computational structure. It has long been assumed that discovering neuron types and their relation to microcircuitry is crucial to understanding neural function. Here we developed a non-parametric Bayesian technique that identifies neuron types and microcircuitry patterns in connectomics data. It combines the information traditionally used by biologists in a…
Figures from this paper
56 Citations
Quantitative neuroanatomy for connectomics in Drosophila
- BiologyeLife
- 2016
New methods to apply quantitative arbor and network context to iteratively proofread and reconstruct circuits and create anatomically enriched wiring diagrams are described and it is shown that this method overcomes the need for redundant effort.
Prediction of a cell-type specific mouse mesoconnectome using gene expression data
- BiologybioRxiv
- 2019
A prediction pipeline is demonstrated that can be used to perform multimodal data integration to improve the accuracy of the predicted mesoconnectome and support other neuroscience use cases.
Circuit analysis of the Drosophila brain using connectivity-based neuronal classification reveals organization of key information processing pathways
- BiologybioRxiv
- 2022
The fruit fly neural circuit presented here captures the latent stochastic patterns of network connectivity and provides a fundamental parts list for reverse-engineering brain computation and results in testable hypotheses on the relationship between neural architecture and behavior.
Learning cellular morphology with neural networks
- Biology, Computer ScienceNature Communications
- 2019
This work introduces cellular morphology neural networks (CMNs), based on multi-view projections sampled from automatically reconstructed cellular fragments of arbitrary size and shape, and successfully automate a range of morphological analysis tasks.
Quantitative neuroanatomy for connectomics in Drosophila
- BiologybioRxiv
- 2016
New methods to apply quantitative arbor and network context to iteratively proofread and reconstruct circuits and create anatomically-enriched wiring diagrams are described and it is shown that this method overcomes the need for redundant effort.
Automated synaptic connectivity inference for volume electron microscopy
- BiologyNature Methods
- 2017
The SyConn framework, which uses deep convolutional neural networks and random forest classifiers to infer a richly annotated synaptic connectivity matrix from manual neurite skeleton reconstructions, is developed, which finds that basal-ganglia cell types with high firing rates in vivo had higher densities of mitochondria and vesicles and that synapse sizes and quantities scaled systematically, depending on the innervated postsynaptic cell types.
Prediction of a Cell-Class-Specific Mouse Mesoconnectome Using Gene Expression Data
- BiologyNeuroinformatics
- 2020
A prediction workflow is demonstrated that can be used to perform multimodal data integration to improve the accuracy of the predicted mesoconnectome and support other neuroscience use cases.
The diversity of GABAergic neurons and neural communication elements
- BiologyNature Reviews Neuroscience
- 2019
It is posited that cardinal interneuron types can be defined by their synaptic communication properties, which are encoded in key transcriptional signatures, and a framework in which cell types are transcriptionally defined communication elements with characteristic input–output properties is proposed.
Learning cellular morphology with neural networks
- Biology, Computer SciencebioRxiv
- 2018
This work introduces cellular morphology neural networks (CMNs), based on multi-view projections sampled from automatically reconstructed cellular fragments of arbitrary size and shape, and demonstrates that CMNs can be used to identify subcellular compartments and the cell types of neuron reconstructions.
References
SHOWING 1-10 OF 60 REFERENCES
Connectomic reconstruction of the inner plexiform layer in the mouse retina
- BiologyNature
- 2013
Circuit motifs that emerge from the data indicate a functional mechanism for a known cellular response in a ganglion cell that detects localized motion, and predict that another ganglions cell is motion sensitive.
Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits
- BiologyProceedings of the National Academy of Sciences
- 2012
It is found that random alignment of axonal and dendritic arbors provides a sufficient foundation for specific functional connectivity to emerge in local neural microcircuits, suggesting that chemospecific steering and aligning of the arbors may occur for some types of connections.
Structural Properties of the Caenorhabditis elegans Neuronal Network
- BiologyPLoS Comput. Biol.
- 2011
The wiring diagram reported here can help in understanding the mechanistic basis of behavior by generating predictions about future experiments involving genetic perturbations, laser ablations, or monitoring propagation of neuronal activity in response to stimulation.
A hierarchical structure of cortical interneuron electrical diversity revealed by automated statistical analysis.
- BiologyCerebral cortex
- 2013
A quantitative, statistical analysis of a database of nearly five hundred neurons manually annotated according to the PING nomenclature showed that the partitioning into different e-types is indeed the major component of data variability.
Comparison Between Supervised and Unsupervised Classifications of Neuronal Cell Types: A Case Study
- Computer Science, BiologyDevelopmental neurobiology
- 2011
In the study of neural circuits, it becomes essential to discern the different neuronal cell types that build the circuit. Traditionally, neuronal cell types have been classified using qualitative…
Cell-type identity: a key to unlocking the function of neocortical circuits
- BiologyCurrent Opinion in Neurobiology
- 2009
Characterization of neocortical principal cells and interneurons by network interactions and extracellular features.
- BiologyJournal of neurophysiology
- 2004
High-density parallel recordings of neuronal activity, determination of their physical location and their classification into pyramidal and interneuron classes provide the necessary tools for local circuit analysis.
The structure of the nervous system of the nematode Caenorhabditis elegans.
- BiologyPhilosophical transactions of the Royal Society of London. Series B, Biological sciences
- 1986
The structure and connectivity of the nervous system of the nematode Caenorhabditis elegans has been deduced from reconstructions of electron micrographs of serial sections. The hermaphrodite nervous…