@article {65832, title = {Automatic Detection of Synaptic Partners in a Whole-Brain Drosophila EM Dataset}, journal = {Nature Methods}, volume = {18}, year = {2021}, month = {2021 Jul 1}, pages = {771-4}, abstract = {

The study of neural circuits requires the reconstruction of neurons and the identification of synaptic connections between them. To scale the reconstruction to the size of whole-brain datasets, semi-automatic methods are needed to solve those tasks. Here, we present an automatic method for synaptic partner identification in insect brains, which uses convolutional neural networks to identify post-synaptic sites and their pre-synaptic partners. The networks can be trained from human generated point annotations alone and requires only simple post-processing to obtain final predictions. We used our method to extract 244 million putative synaptic partners in the fifty-teravoxel full adult fly brain (FAFB) electron microscopy (EM) dataset and evaluated its accuracy on 146,643 synapses from 702 neurons with a total cable length of 312 mm in four different brain regions. The predicted synaptic connections can be used together with a neuron segmentation to infer a connectivity graph with high accuracy: 96\% of edges between connected neurons are correctly classified as weakly connected (less than five synapses) and strongly connected (at least five synapses). Our synaptic partner predictions for the FAFB dataset are publicly available, together with a query library allowing automatic retrieval of up- and downstream neurons.

}, doi = {10.1038/s41592-021-01183-7}, author = {Buhmann, Julia and Sheridan, Arlo and Gerhard, Stephan and Krause, Renate and Nguyen, Tri and Heinrich, Larissa and Schlegel, Philipp and Lee, Wei-Chung Allen and Wilson, Rachel and Saalfeld, Stephan and Jefferis, Gregory and Bock, Davi and Turaga, Srinivas and Cook, Matthew and Funke, Jan} } @article {67219, title = {Community-based benchmarking improves spike rate inference from two-photon calcium imaging data}, journal = {PLOS Computational Biology}, volume = {14}, year = {2018}, month = {Sep-05-2019}, pages = {e1006157}, abstract = {

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the\ spikefinder\ challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.

}, doi = {10.1371/journal.pcbi.1006157}, url = {https://journals.plos.org/ploscompbiol/article?rev=2\&id=10.1371/journal.pcbi.1006157}, author = {Berens, Philipp and Freeman, Jeremy and Deneux, Thomas and Chenkov, Nikolay and McColgan, Thomas and Speiser, Artur and Macke, Jakob H. and Turaga, Srinivas C. and Mineault, Patrick and Rupprecht, Peter and Gerhard, Stephan and Friedrich, Rainer W. and Friedrich, Johannes and Paninski, Liam and Pachitariu, Marius and Harris, Kenneth D. and Bolte, Ben and Machado, Timothy A. and Ringach, Dario and Stone, Jasmine and Rogerson, Luke E. and Sofroniew, Nicolas J. and Reimer, Jacob and Froudarakis, Emmanouil and Euler, Thomas and Rom{\'a}n Ros{\'o}n, Miroslav and Theis, Lucas and Tolias, Andreas S. and Bethge, Matthias}, editor = {Bush, Daniel} } @article {48836, title = {Community-based benchmarking improves spike inference from two-photon calcium imaging data.}, journal = {PLoS Computational Biology}, volume = {14}, year = {2017}, month = {2018 May 21}, pages = {e1006157}, abstract = {

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.

}, doi = {10.1371/journal.pcbi.1006157}, author = {Berens, Philipp and Freeman, Jeremy and Deneux, Thomas and Chenkov, Nicolay and McColgan, Thomas and Speiser, Artur and Macke, Jakob H and Turaga, Srinivas C and Mineault, Patrick and Rupprecht, Peter and Gerhard, Stephan and Friedrich, Rainer W and Friedrich, Johannes and Paninski, Liam and Pachitariu, Marius and Harris, Kenneth D and Bolte, Ben and Machado, Timothy A and Ringach, Dario and etal} } @article {48888, title = {Conserved neural circuit structure across Drosophila larva development revealed by comparative connectomics.}, journal = {eLife}, volume = {6}, year = {2017}, month = {2017 Oct 23}, pages = {e29089}, abstract = {

During postembryonic development, the nervous system must adapt to a growing body. How changes in neuronal structure and connectivity contribute to the maintenance of appropriate circuit function remains unclear. In a previous paper (Schneider-Mizell et al., 2016), we measured the cellular neuroanatomy underlying synaptic connectivity in Drosophila. Here, we examined how neuronal morphology and connectivity change between 1st instar and 3rd instar larval stages using serial section electron microscopy. We reconstructed nociceptive circuits in a larva of each stage and found consistent topographically arranged connectivity between identified neurons. Five-fold increases in each size, number of terminal dendritic branches, and total number of synaptic inputs were accompanied by cell-type specific connectivity changes that preserved the fraction of total synaptic input associated with each presynaptic partner. We propose that precise patterns of structural growth act to conserve the computational function of a circuit, for example determining the location of a dangerous stimulus.

}, issn = {2050-084X}, doi = {10.7554/eLife.29089}, author = {Gerhard, Stephan and Andrade, Ingrid and Fetter, Richard D and Cardona, Albert and Schneider-Mizell, Casey M} } @article {47421, title = {Astrocytic glutamate transport regulates a Drosophila CNS synapse that lacks astrocyte ensheathment.}, journal = {The Journal of Comparative Neurology}, volume = {524}, year = {2016}, month = {2016 Apr 12}, pages = {1979-98}, abstract = {

Anatomical, molecular, and physiological interactions between astrocytes and neuronal synapses regulate information processing in the brain. The fruit fly Drosophila melanogaster has become a valuable experimental system for genetic manipulation of the nervous system and has enormous potential for elucidating mechanisms that mediate neuron-glia interactions. Here, we show the first electrophysiological recordings from Drosophila astrocytes and characterize their spatial and physiological relationship with particular synapses. Astrocyte intrinsic properties were found to be strongly analogous to those of vertebrate astrocytes, including a passive current-voltage relationship, low membrane resistance, high capacitance, and dye-coupling to local astrocytes. Responses to optogenetic stimulation of glutamatergic pre-motor neurons were correlated directly with anatomy using serial electron microscopy reconstructions of homologous identified neurons and surrounding astrocytic processes. Robust bidirectional communication was present: neuronal activation triggered astrocytic glutamate transport via Eaat1, and blocking Eaat1 extended glutamatergic interneuron-evoked inhibitory post-synaptic currents in motor neurons. The neuronal synapses were always located within a micron of an astrocytic process, but none were ensheathed by those processes. Thus, fly astrocytes can modulate fast synaptic transmission via neurotransmitter transport within these anatomical parameters. This article is protected by copyright. All rights reserved.

}, issn = {1096-9861}, doi = {10.1002/cne.24016}, author = {MacNamee, Sarah E and Liu, Kendra E and Gerhard, Stephan and Tran, Cathy T and Fetter, Richard D and Cardona, Albert and Tolbert, Leslie P and Oland, Lynne A} } @article {47062, title = {Quantitative neuroanatomy for connectomics in Drosophila.}, journal = {eLife}, year = {2016}, month = {2016 Mar 18}, pages = {e12059}, abstract = {

Neuronal circuit mapping using electron microscopy demands laborious proofreading or reconciliation of multiple independent reconstructions. Here, we describe new methods to apply quantitative arbor and network context to iteratively proofread and reconstruct circuits and create anatomically enriched wiring diagrams. We measured the morphological underpinnings of connectivity in new and existing reconstructions of\ Drosophila\ sensorimotor (larva) and visual (adult) systems. Synaptic inputs were preferentially located on numerous small, microtubule-free {\textquoteright}twigs{\textquoteright} which branch off a single microtubule-containing {\textquoteright}backbone{\textquoteright}. Omission of individual twigs accounted for 96\% of errors. However, the synapses of highly connected neurons were distributed across multiple twigs. Thus, the robustness of a strong connection to detailed twig anatomy was associated with robustness to reconstruction error. By comparing iterative reconstruction to the consensus of multiple reconstructions, we show that our method overcomes the need for redundant effort through the discovery and application of relationships between cellular neuroanatomy and synaptic connectivity.

}, doi = {10.7554/eLife.12059}, author = {Schneider-Mizell, Casey M. and Gerhard, Stephan and Longair, Mark and Kazimiers, Tom and Li, Feng and Zwart, Maarten and Champion, Andrew and Midgley, Frank and Fetter, Richard D and Saalfeld, Stephan and Cardona, Albert} }