cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25378/janelia.12490373.v2
title: The Neuroanatomical Ultrastructure and Function of a Biological Ring Attractor - One color calcium imaging data

description: All one-color calcium imaging experiments of the ring neurons, R4d, are contained in this zip file. The directories are arranged first by cell type, then by the date of the experiment for that cell type. Each trial has its own .mat files, and each mat file features a matrix containing the raw DF/F signal at each time point for each region of interest (ROIaveMax) and a structure that contains the behavioral data (positionDat). <br><br>Analysis code can be found at https://github.com/DanTurner-Evans/BiologicalRingAttractor-Code<br>Related materials in the collection (https://doi.org/10.25378/janelia.c.5179721):Neuron skeletons and synapses: https://doi.org/10.25378/janelia.12497756<br>Kir perturbation calcium imaging data: https://doi.org/10.25378/janelia.12490325Shi perturbation calcium imaging data: https://doi.org/10.25378/janelia.12490313Two color calcium imaging data: https://doi.org/10.25378/janelia.12490274Behavioral data for the perturbation experiments: https://doi.org/10.25378/janelia.12490070<br><br>Dataset supports the publication:Turner-Evans, D. B., Jensen, K. T., Ali, S., Paterson, T., Sheridan, A., Ray, R. P., Wolff, T., Lauritzen, J. S., Rubin, G. M., Bock, D. D., & Jayaraman, V. (2020). The Neuroanatomical Ultrastructure and Function of a Biological Ring Attractor. Neuron, 108(1), 145-163.e10. https://doi.org/10.1016/j.neuron.2020.08.006<br>Abstract<br>Neural representations of head direction (HD) have been discovered in many species. Theoretical work has proposed that the dynamics associated with these representations are generated, maintained, and updated by recurrent network structures called ring attractors. We evaluated this theorized structure-function relationship by performing electron-microscopy-based circuit reconstruction and RNA profiling of identified cell types in the HD system of Drosophila melanogaster. We identified motifs that have been hypothesized to maintain the HD representation in darkness, update it when the animal turns, and tether it to visual cues. Functional studies provided support for the proposed roles of individual excitatory or inhibitory circuit elements in shaping activity. We also discovered recurrent connections between neuronal arbors with mixed pre- and postsynaptic specializations. Our results confirm that the Drosophila HD network contains the core components of a ring attractor while also revealing unpredicted structural features that might enhance the network’s computational power.
DOI: 10.25378/janelia.12497756
title: The Neuroanatomical Ultrastructure and Function of a Biological Ring Attractor - Electron microscopy reconstructions and synapses

description: The skeletons and synapses for the single, central complex Drosophila neurons featured in the <i>The Neuroanatomical Ultrastructure and Function of a Biological Ring Attractor</i> are pickled here. This data can also be obtained from the FAFB dataset (https://temca2data.org/), but is included here for convenience.<br>Analysis code can be found at https://github.com/KrisJensen/EMpaper<br>Related materials in the collection:One color calcium imaging data: https://doi.org/10.25378/janelia.12490373<br>Kir perturbation calcium imaging data: https://doi.org/10.25378/janelia.12490325Shi perturbation calcium imaging data: https://doi.org/10.25378/janelia.12490313Two color calcium imaging data: https://doi.org/10.25378/janelia.12490274Behavioral data for the perturbation experiments: https://doi.org/10.25378/janelia.12490070<br><br>Dataset supports the publication:Turner-Evans, D. B., Jensen, K. T., Ali, S., Paterson, T., Sheridan, A., Ray, R. P., Wolff, T., Lauritzen, J. S., Rubin, G. M., Bock, D. D., & Jayaraman, V. (2020). The Neuroanatomical Ultrastructure and Function of a Biological Ring Attractor. Neuron, 108(1), 145-163.e10. https://doi.org/10.1016/j.neuron.2020.08.006<br>Abstract<br>Neural representations of head direction (HD) have been discovered in many species. Theoretical work has proposed that the dynamics associated with these representations are generated, maintained, and updated by recurrent network structures called ring attractors. We evaluated this theorized structure-function relationship by performing electron-microscopy-based circuit reconstruction and RNA profiling of identified cell types in the HD system of Drosophila melanogaster. We identified motifs that have been hypothesized to maintain the HD representation in darkness, update it when the animal turns, and tether it to visual cues. Functional studies provided support for the proposed roles of individual excitatory or inhibitory circuit elements in shaping activity. We also discovered recurrent connections between neuronal arbors with mixed pre- and postsynaptic specializations. Our results confirm that the Drosophila HD network contains the core components of a ring attractor while also revealing unpredicted structural features that might enhance the network’s computational power.<br>
DOI: 10.25378/janelia.12497756.v1
title: pickled_neurons.tar.gz

description: The skeletons and synapses for the single, central complex Drosophila neurons featured in this paper are pickled here. This data can also be obtained from the FAFB dataset (https://temca2data.org/), but is included here for convenience.<br>
DOI: 10.25378/janelia.13118156
title: Segmentation of organelles in isotropic electron microscopy data of wild-type, immortalized breast cancer cell - SUM159 (jrc_sum159-1)

description: The cell interior contains hundreds of different organelle and macromolecular assemblies intricately organized relative to each other to meet any cellular demand. Obtaining a complete understanding of this organization is challenging and requires nanometer-level, three-dimensional reconstruction of whole cells. Even then, the immense size of datasets and large number of structures to be characterized requires generalizable, automatic methods. To overcome this challenge, we developed an analysis pipeline for comprehensively reconstructing and analyzing all known cellular organelles from entire cells imaged by focused ion beam scanning electron microscopy (FIB-SEM) at a near-isotropic size of 4 or 8 nm per voxel. The pipeline involved deep learning architectures trained on diverse samples for automatic reconstruction of 35 different cellular organelle classes - ranging from ER to microtubules to ribosomes - from multiple cell types. Automatic reconstructions were used to directly quantify various previously inaccessible metrics about these structures and their spatial interactions. We show that automatic organelle reconstructions can also be used to automatically register light and electron microscopy images for correlative studies. The data, computer code, and trained models are all shared through an open data and open source web platform OpenOrganelle, enabling scientists everywhere to query and further reconstruct the datasets.Sample: Wild-type SUM-159 cell, treated with 0.5 mM oleic acid for 45 mins prior to high pressure freezing to induce the formation of lipid droplets.Dataset ID: jrc_sum159-1EM Data DOI: 10.25378/janelia.13114352EM voxel size (nm): 4.0 x 4.0 x 4.0 (X, Y, Z)Segmentation voxel size (nm): 4.0 x 4.0 x 4.0 (X, Y, Z)Dataset URL: https://data.janelia.org/LzShCVisualization Website: https://openorganelle.janelia.org/datasets/jrc_sum159-1Publication: Heinrich et el., 2020Included in Dataset: manual annotations
DOI: 10.25378/janelia.5936218.v10
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v11
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v12
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v13
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v14
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v15
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v16
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs. Downloadable archives are publicly available at https://open.quiltdata.com/b/janelia-flylight-color-depth/tree/Color_Depth_MIPs_For_Download. <br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v17
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs. Downloadable archives are publicly available at https://open.quiltdata.com/b/janelia-flylight-color-depth/tree/Color_Depth_MIPs_For_Download. <br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v18
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs. Downloadable archives are publicly available at:<br>https://open.quiltdata.com/b/janelia-flylight-color-depth/tree/Color_Depth_MIPs_For_Download/ <br>For the construction of Janelia and VT GAL4 lines, see the below references.<br>
DOI: 10.25378/janelia.5936218.v19
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs. Downloadable archives are publicly available at:<br>https://open.quiltdata.com/b/janelia-flylight-color-depth/tree/Color_Depth_MIPs_For_Download/ <br>For the construction of Janelia and VT GAL4 lines, see the below references.<br>
DOI: 10.25378/janelia.5936218.v2
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v20
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs. Downloadable archives are publicly available at:<br>https://open.quiltdata.com/b/janelia-flylight-color-depth/tree/Color_Depth_MIPs_For_Download/ <br>For the construction of Janelia and VT GAL4 lines, see the below references.<br>
DOI: 10.25378/janelia.5936218.v3
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v4
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v5
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v6
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v7
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v8
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.5936218.v9
title: Gen1 Color Depth MIPs

description: Color depth MIP files for Gen1 GAL4 and LexA brains and VNCs.<br>For the construction of Janelia and VT GAL4 lines, see the below references.<br><br>
DOI: 10.25378/janelia.7149299.v1
title: Data S1A: Technical Drawings

description: Please contact innovation@janelia.hhmi.org or visit https://www.janelia.org/open-science/simview in order to obtain free access to this archive. The archive contains the blueprint of the adaptive multi-view light-sheet microscope for mouse imaging, including technical drawings for the microscope’s 77 types of custom mechanical components, assembly illustrations for the microscope’s 28 types of multi-part assemblies, and parts list of all custom and commercial mechanical microscope components<br>
DOI: 10.25378/janelia.7605824.v1
title: Longitudinal functional imaging data for the zebrafish embryonic spinal cord

description: Each data set in this archive includes a file named "profile.mat", which contains the time-dependent intensity signals of individual cells recorded by longitudinal calcium imaging (variable "profile_all", Ncells x Ntimepoints), their 3D spatial coordinates (variable "tracks_smoothed", Ncells x Ntimepoints x 3), their molecular identity (binary variable "mnx", NCell x 1), and their anatomical location in the developmental atlas of the spinal cord (variables "x": AP location, "y": LR location, "z": DV location, Nells x 1).<br><br>Data sets named "func_*" contain only the information described above.<br>Data sets named "islet_*" contain the information above, as well as information about neuron identity from islet1/2 staining (binary variable "islet" in "profile.mat", Ncell x 1).<br>Data sets named "lineage_*" contain the information above, as well as information about the birth time of each neuron (variable "birthtime" in "profile.mat", Ncell x 1). They furthermore include a file "dev_data.mat", which contains information on the 4D lineages of all cells in the swc format (variable "trackingM", nPoints x 10, columns represent cell_id, type, x, y, z, radius, parent_id, timepoint, confidence, lineage_id), and the cell identifier of leaf nodes corresponding to cells analyzed in the longitudinal functional imaging data (variable "leafID", NCell x 1).
DOI: 10.25378/janelia.7607411.v1
title: Functional imaging data for ablation experiments in the zebrafish embryonic spinal cord

description: Each data set in this archive includes a file named "profile.mat", which contains the time-dependent intensity signals of individual cells recorded by longitudinal calcium imaging (variable "profile_all", Ncells x Ntimepoints), their 3D spatial coordinates (variable "tracks_smoothed", Ncells x Ntimepoints x 3), their anatomical location in the developmental atlas of the spinal cord (variables "x": AP location, "y": LR location, "z": DV location, Nells x 1), and the absolute index of the most anterior segment imaged (variable "segOffset").<br><br>Data sets named "single_*" represent single-cut experiments and additionally contain information on the location of the transverse lesion (variable "segAblation").<br>Data sets named "double_*" represent double-cut experiments and additionally contain information on the locations of both transverse lesions (variables "segAblation_A", "segAblation_P").<br>The extensions "_before" and "_after" in the name of each experiment folder indicate whether the respective imaging session occurred before or after ablation, respectively.
DOI: 10.25378/janelia.12106809.v2
title: Raw data (behavior data) for Generation of stable heading representations in diverse visual scenes

description: Raw behavior data of all flies for the following paper.<br><br>Generation of stable heading representations in diverse visual scenes<br>Sung Soo Kim+, Ann M. Hermundstad, Sandro Romani, L. F. Abbott, Vivek Jayaraman+<br>Nature (2019) 576:126-131<br>Many animals rely on an internal heading representation when navigating in varied environments. How this representation is linked to the sensory cues that define different surroundings is unclear. In the fly brain, heading is represented by 'compass' neurons that innervate a ring-shaped structure known as the ellipsoid body. Each compass neuron receives inputs from 'ring' neurons that are selective for particular visual features; this combination provides an ideal substrate for the extraction of directional information from a visual scene. Here we combine two-photon calcium imaging and optogenetics in tethered flying flies with circuit modelling, and show how the correlated activity of compass and visual neurons drives plasticity, which flexibly transforms two-dimensional visual cues into a stable heading representation. We also describe how this plasticity enables the fly to convert a partial heading representation, established from orienting within part of a novel setting, into a complete heading representation. Our results provide mechanistic insight into the memory-related computations that are essential for flexible navigation in varied surroundings.<br><br>Additional materials found in this Collection: https://doi.org/10.25378/janelia.c.4932540<br><br>
DOI: 10.25378/janelia.12106824.v2
title: Analysis codes and pre-processed calcium imaging data for Generation of stable heading representations in diverse visual scenes

description: Analysis codes and pre-processed data to generate figures in the following paper.<br><br>Generation of stable heading representations in diverse visual scenes<br>Sung Soo Kim+, Ann M. Hermundstad, Sandro Romani, L. F. Abbott, Vivek Jayaraman+<br>Nature (2019) 576:126-131<br>Many animals rely on an internal heading representation when navigating in varied environments. How this representation is linked to the sensory cues that define different surroundings is unclear. In the fly brain, heading is represented by 'compass' neurons that innervate a ring-shaped structure known as the ellipsoid body. Each compass neuron receives inputs from 'ring' neurons that are selective for particular visual features; this combination provides an ideal substrate for the extraction of directional information from a visual scene. Here we combine two-photon calcium imaging and optogenetics in tethered flying flies with circuit modelling, and show how the correlated activity of compass and visual neurons drives plasticity, which flexibly transforms two-dimensional visual cues into a stable heading representation. We also describe how this plasticity enables the fly to convert a partial heading representation, established from orienting within part of a novel setting, into a complete heading representation. Our results provide mechanistic insight into the memory-related computations that are essential for flexible navigation in varied surroundings.<br><br>Additional materials found in this Collection: https://doi.org/10.25378/janelia.c.4932540<br><br>
DOI: 10.25378/janelia.12109227.v2
title: Raw calcium imaging data (5-2) for Generation of stable heading representations in diverse visual scenes

description: Two-photon imaging data for the following paper.<br><br>Generation of stable heading representations in diverse visual scenes<br>Sung Soo Kim+, Ann M. Hermundstad, Sandro Romani, L. F. Abbott, Vivek Jayaraman+<br>Nature (2019) 576:126-131<br>Many animals rely on an internal heading representation when navigating in varied environments. How this representation is linked to the sensory cues that define different surroundings is unclear. In the fly brain, heading is represented by 'compass' neurons that innervate a ring-shaped structure known as the ellipsoid body. Each compass neuron receives inputs from 'ring' neurons that are selective for particular visual features; this combination provides an ideal substrate for the extraction of directional information from a visual scene. Here we combine two-photon calcium imaging and optogenetics in tethered flying flies with circuit modelling, and show how the correlated activity of compass and visual neurons drives plasticity, which flexibly transforms two-dimensional visual cues into a stable heading representation. We also describe how this plasticity enables the fly to convert a partial heading representation, established from orienting within part of a novel setting, into a complete heading representation. Our results provide mechanistic insight into the memory-related computations that are essential for flexible navigation in varied surroundings.<br><br>Additional materials found in this Collection: https://doi.org/10.25378/janelia.c.4932540<br><br>
DOI: 10.25378/janelia.12110073.v2
title: Raw calcium imaging data (4-2) for Generation of stable heading representations in diverse visual scenes

description: Two-photon imaging data for the following paper.<br><br>Generation of stable heading representations in diverse visual scenes<br>Sung Soo Kim+, Ann M. Hermundstad, Sandro Romani, L. F. Abbott, Vivek Jayaraman+<br>Nature (2019) 576:126-131<br>Many animals rely on an internal heading representation when navigating in varied environments. How this representation is linked to the sensory cues that define different surroundings is unclear. In the fly brain, heading is represented by 'compass' neurons that innervate a ring-shaped structure known as the ellipsoid body. Each compass neuron receives inputs from 'ring' neurons that are selective for particular visual features; this combination provides an ideal substrate for the extraction of directional information from a visual scene. Here we combine two-photon calcium imaging and optogenetics in tethered flying flies with circuit modelling, and show how the correlated activity of compass and visual neurons drives plasticity, which flexibly transforms two-dimensional visual cues into a stable heading representation. We also describe how this plasticity enables the fly to convert a partial heading representation, established from orienting within part of a novel setting, into a complete heading representation. Our results provide mechanistic insight into the memory-related computations that are essential for flexible navigation in varied surroundings.<br><br>Additional materials found in this Collection: https://doi.org/10.25378/janelia.c.4932540<br><br><br>
DOI: 10.25378/janelia.12110076.v2
title: Raw calcium imaging data (5-1) for Generation of stable heading representations in diverse visual scenes

description: Two-photon imaging data for the following paper.<br><br>Generation of stable heading representations in diverse visual scenes<br>Sung Soo Kim+, Ann M. Hermundstad, Sandro Romani, L. F. Abbott, Vivek Jayaraman+<br>Nature (2019) 576:126-131<br>Many animals rely on an internal heading representation when navigating in varied environments. How this representation is linked to the sensory cues that define different surroundings is unclear. In the fly brain, heading is represented by 'compass' neurons that innervate a ring-shaped structure known as the ellipsoid body. Each compass neuron receives inputs from 'ring' neurons that are selective for particular visual features; this combination provides an ideal substrate for the extraction of directional information from a visual scene. Here we combine two-photon calcium imaging and optogenetics in tethered flying flies with circuit modelling, and show how the correlated activity of compass and visual neurons drives plasticity, which flexibly transforms two-dimensional visual cues into a stable heading representation. We also describe how this plasticity enables the fly to convert a partial heading representation, established from orienting within part of a novel setting, into a complete heading representation. Our results provide mechanistic insight into the memory-related computations that are essential for flexible navigation in varied surroundings.<br><br>Additional materials found in this Collection: https://doi.org/10.25378/janelia.c.4932540<br><br>