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387 results for “axon”
Dataset: Axon Enterprise, Inc. (AXON) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Data and code for behavioral analysis of: Structural and Molecular Properties of Insect Type II Motor Axon Terminals.
<p>Data and code for behavioral analysis of: Structural and Molecular Properties of Insect Type II Motor Axon Terminals.</p> <p>v1.2: typos corrected and all files available in a single .zip file for download</p>
Dataset of Axon Segmentation and Centerlines, Acquired using a Two-photon Microscope in the Live Mouse Cortex
<p>This dataset contains 20 images of real axons that were published previously in Bass et al (2017). This subset dataset has been added labels of binary images for segmentation of the axons, and of centerline for tracing of the axons.</p> <p>We provide the following:</p> <ul> <li>Images-MAX: 2D images of axons (.png)</li> <li>Images-TIFF: 3D images of axons (.tiff)</li> <li>Labels-binary: Manual segmentation of the axons as binary images (.png)</li> <li>Labels-tracing: Manual tracing of the axons (.swc)</li> </ul> <p>This data was collected in the live mouse cortex, using a two-photon microscope, with a 40x objective, at zoom 4, and with a resolution of 512 × 512 pixels, 0.147 <em>μ</em>m per pixel for the <em>x</em>, <em>y</em> planes, and 1 <em>μ</em>m for the <em>z</em> plane. . </p> <p><strong>Please cite the following papers when using this dataset:</strong></p> <p>T. Dai, M. Dubois, K. Arulkumaran, J. Campbell, B. Billot, C. Bass, Z. Uslu, V. De Paola, C. Clopath, and A. A. Bharath. Deep reinforcement learning for subpixel neural tracking. <em>Medical Imaging with Deep Learning</em>. 2019.</p> <p>Bass C, Helkkula P, De Paola V, Clopath C, Bharath AA. Detection of axonal synapses in 3D two-photon images. Giniger E, ed. <em>PLoS ONE</em>. 2017;12(9):e0183309. doi:10.1371/journal.pone.0183309.</p>
Histological validation of per-bundle water diffusion metrics within a region of fiber crossing following axonal degeneration
<p>Interactive plots showing the correlation between histological parameters of optic nerves and chiasm, and metrics derived from diffusion MRI in a rat model of unilateral retinal ischemia.</p> <p> </p> <p>There are two .html files, each containing an interactive figure, one for data pertaining to the optic nerve, the other for the chiasm. The left panel shows the correlation matrix. Click on any cell to see the corresponding scatter plot on the right panel. </p>
Long-range axonal projections analyses of the mouse brain
<p>Accompanying data and analyses of the article <a href="https://doi.org/10.1101/2024.10.04.616605">"Generating brain-wide connectome using synthetic axonal morphologies"</a>. The code to reproduce the figures is available at <a href="https://github.com/Remy2506/axon_projection_figures">this repository</a>.</p> <p>Main contents:</p> <ul> <li><strong>SEU_morphs.zip, peng_2021_morphs.zip, ML_morphs.zip: </strong>input morphologies from various sources (novel morphologies collected by H. Peng, Southeast University, <a href="https://www.nature.com/articles/s41586-021-03941-1">Peng et al. 2021</a>, <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754285/">Winnubst et al. 2019</a>) after <a href="https://github.com/BlueBrain/morphology-workflows"><em>morphology-workflows</em> <em>Repair</em></a> post-processing steps.</li> <li><strong>atlas</strong>: atlas of the mouse brain used (enhanced version of Allen Brain CCFv3)</li> <li><strong>out_a_p</strong>: output of the <a href="https://github.com/BlueBrain/axon-projection">axon projection</a> anaylsis and clustering on the 3601 morphologies of the dataset. <ul> <li>axon_lengths_12.csv, axon_terminals_12.csv: the lengths of axons in each subregion where they terminate, and terminals, at hierarchy level 12 from the brain hierarchy.</li> <li>clustering_output.csv: output of the GMM clustering.</li> <li>config_a_p.cfg: configuration file used to produce this analysis, with running the axonal projection code.</li> </ul> </li> <li><strong>circuit</strong>: contains files describing the circuit synthesized with Blue Brain's <em>circuit-build*.</em> <ul> <li>bioname: parameters used to synthesize the circuit (regions to synthesize, cell densities per region, location of axons to graft...).</li> <li>sonata: files that contain nodes and edges of the circuit.</li> <li>auxiliary: various cell collections from the synthesized cells, filtered by region. Cell collections are to be read with <a href="https://github.com/BlueBrain/voxcell/tree/main">Voxcell.</a></li> <li>conn_mat.h5: the connectivity matrices obtained for the case where MOp5 long-range axons were synthesized, computed with <a href="https://github.com/BlueBrain/ConnectomeUtilities/tree/main">ConnectomeUtilities.</a>Contains connectivity matrices for the synthesized LRAs, biological LRAs, and grafted local axons.</li> </ul> </li> <li><strong>local_axons</strong>: biological local axons that are grafted to the synthesized dendrites that do not have synthesized long-range axons.</li> <li><strong>synthesized_MOp5_LRAs</strong>: 1695 synthesized cells with long-range axons of the MOp5 region, in the atlas reference frame. </li> <li><strong>out_a_p_synth_MOp5</strong>: axonal projection analysis of the synthesized MOp5 axons.</li> <li><strong>synthesized_isocortex_cells</strong>: all synthesized cells of the isocortex region, except MOp5 cells. They are in h5 format, which takes less space than asc and swc. The h5 format can be read and converted for instance with <a href="https://github.com/BlueBrain/MorphIO">MorphIO</a>.</li> <li><strong>synthesized_isocortex_LRAs</strong>: 21680 synthesized cells with long-range axons of the isocortex regions for which a GMM cluster was created. </li> </ul> <p>Additional files:</p> <ul> <li>flatmap_both.nrrd: file used to generate a flat map visualization of the mouse isocortex, shown in the article.</li> <li>config_a_s.cfg: configuration file used to synthesize the long-range axons with the <a href="https://github.com/BlueBrain/axon-synthesis">axon-synthesis</a> code.</li> <li>target_pts: tufts common ancestors for the synthesized MOp5 axons.</li> <li>brain_atlas.zip: a lightweight version of the mouse brain atlas for the synthesis code example.</li> </ul> <p>*<em>These softwares might not be open-source at the time of publication of this data, but a public link will be provided as soon as they are.</em></p>
Predicting the distribution of serotonergic axons: A supercomputing simulation of reflected fractional Brownian motion in a 3D-mouse brain model
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CA3 axonal calcium imaging
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Noninvasive quantification of axon radii using diffusion MRI
<p>Axon size plays a crucial role in determining conductance velocity and, consequently, in the the timing and synchronization of neural activation. Noninvasive measurement of axon radii could have significant impact on the understanding of healthy and diseased neural processes. However, until now, accurate axon radius mapping has eluded in vivo neuroimaging, mainly due to a lack of sensitivity of the MRI signal to micron-sized axons. Here, we show how -- when confounding factors such as extra-axonal water and axonal orientation dispersion are eliminated -- heavily diffusion-weighted MRI signals becomes sensitive to axon radii. However, diffusion MRI is only capable of estimating a single metric representing the entire axon radius distribution within a voxel that emphasizes the largest axons. Our findings, both in rodents and humans, enable noninvasive mapping of critical information on axon radii, as well as resolve the long-standing debate on whether axon radii can be quantified.</p>
Involvement of the optic nerve in mutated CSF1R-induced hereditary diffuse leukoencephalopathy with axonal spheroids
<p><strong>Figure 1:</strong> Family pedigree. The arrow indicates the proband (present patient). Her mother developed a motor disorder at 40 years of age and died at 60 years of age. Her grandparents, father, brothers, sisters, and daughters were not affected.</p> <p><strong>Figure 2: Brain MRI, DWI, DTI, and MRS images. T2/Flair showed multifocal periventricular white matter lesions (A, B, and C), without enhancement (D). DWI shows high-signal intensities in periventricular white matters and corpus callosum (E, F). DTI shows decreased numbers of corpus callosum fibers, while subcortical arcuate fibers are spared (G). MRS shows increased Cho levels, while NAA levels are decreased in the white matter lesions (H, I).</strong></p> <p><strong>Figure 3: </strong>Optic nerves on MRI, showing that bilateral optic nerves are injured (red arrows). </p> <p><strong>Figure 4: </strong>OCT shows that the right peripapillary retinal nerve fiber layer (pRNFL) is atrophic in the temporal quadrant, and the left pRNFL is thinning in the temporal superior quadrants. Green represents pRNFL thickness, which is within normal limits; yellow represents pRNFL thickness, which is below borderline; red represents pRNFL thickness, which is below normal limits.</p> <p><strong>Figure 5:</strong> VEP shows reduced bilateral P100 amplitudes, although P100 latencies are normal in both eyes.</p> <p><strong>Figure 6:</strong> Visual fields in the right eye are partially missing in the upper right, lower right, and lower left quadrants, especially in the lower right quadrant. Visual fields in the left eye are partially missing in the four quadrants, especially in the upper left and lower right quadrants.</p> <p><strong>Figure 7:</strong> Gene analysis of <em>CSF1R</em>. The sequencing result from exon 18 of <em>CSF1R</em> (NM_005211.3) indicates a heterozygous c.2345 G>A (p.782Arg>His) substitution in the patient.</p>
Dataset of Axonal Synapses, Acquired using a Two-photon Microscope in the Live Mouse Cortex
<p>This Dataset consists of TIFF 100 images, split in 20 test and 80 training images, of axons with their synapses (boutons) labelled. The labels are in form of ground-truth binary images of the same size, in which the corresponding synapses have been labelled as boxes.</p> <p>This data was collected in the live mouse cortex, using a two-photon microscope, with a 40x objective, at zoom 4, with a resolution of 512 x 512 x 0.147 microns per pixel, and a Point Spread Function characterised by a Full Width at Half Maximum (FWHM) values of 0.45 x 0.45 x 2.5 microns (x, y, z). </p> <p> </p> <p><strong>Please cite the following paper when using this dataset:</strong></p> <p>Bass C, Helkkula P, De Paola V, Clopath C, Bharath AA. Detection of axonal synapses in 3D two-photon images. Giniger E, ed. <em>PLoS ONE</em>. 2017;12(9):e0183309. doi:10.1371/journal.pone.0183309.</p> <p> </p>
Mechanical stimulation prevents impairment of axon growth and overcompensates microtubules destabilization in cellular models of Alzheimer's disease related Tau pathology
<p>Data and metadata associated to a publication 10.3389/fmed.2025.1519628</p>
An axonal brake on striatal dopamine output by cholinergic interneurons
<h3><strong>ABSTRACT</strong></h3> <p>Depolarisation of distal axons is necessary for somatic action potentials to be translated into axonal neurotransmitter release. Here, we show that activation of striatal cholinergic interneurons (ChIs) and nicotinic receptors (nAChRs) on mouse DA axons transiently prevents the release of dopamine (DA) by subsequent stimuli for ~100 ms. Previous studies have shown that nAChRs on DA axons can drive ectopic action potentials in DA axons to trigger DA release. We demonstrate <em>ex vivo </em>that a lower level of activation of ChIs is needed to suppress DA release than to trigger it, an effect that is not due to DA depletion, but to restricted re-activation of DA axons. This axonal brake on DA output is stronger and more persistent in dorsal than ventral striatum. <em>In vivo</em>, we reveal a predominant depression of DA release by endogenous acetylcholine, as antagonism of nAChRs in dorsal striatum conversely elevated tonic DA detected with optic-fibre photometry of GRAB<sub>DA2m</sub> sensor and promoted conditioned place-preference. Our findings reveal that ChIs acting via nAChRs limit activation of DA axons by subsequent DA neuron activity, uncoupling DA axons from ascending action potentials and generating a dynamic inverse scaling of DA release according to ChI activity.</p> <p> </p> <h3><strong>FILE DESCRIPTIONS</strong></h3> <p>This repository contains the following files:</p> <ul> <li>Key Resources Table (.xlsx) - Table containing details on key resources (antibodies, mouse lines, virus strains, and software), and the persistent identifiers for protocols and code used and generated in this study. </li> <li>Source Data Folder (.zip): <ul> <li>_README_Source_Data (.txt) with detailed information about each dataset.</li> <li>Individual tabular datasets corresponding to panels shown in the Main Figures 1 to 5 (.csv).</li> <li>Excel spreadsheet containing all tabular datasets plotted in Main Figures 1 to 5 (.xlsx)</li> </ul> </li> <li>Supplementary Data Folder (.zip): <ul> <li>_README_Supplementary_Data (.txt) with detailed information about each dataset.</li> <li>Individual tabular datasets corresponding to panels shown in the Supplementary Figures 1 to 6 (.csv).</li> <li>Excel spreadsheet containing all tabular datasets plotted in Supplementary Figures 1 to 6 (.xlsx)</li> </ul> </li> </ul>
Dataset: Towards a representative reference for MRI-based human axon radius assessment using light microscopy
<p>Dataset for: Towards a representative reference for MRI-based human axon radius assessment using light microscopy</p>
Responses to axonal current injection in cortical layer 5 pyramidal neurons
<p>Patch-clamp recordings in cortical layer 5 pyramidal neurons performed by Wenqin Hu. A current pulse is either injected in the soma or in an axonal bleb and recorded simultaneously in the axonal bleb or the soma, respectively.</p> <p>The data are related to figure 7 of the paper: Hu, W., & Bean, B. P. (2018). Differential control of axonal and somatic resting potential by voltage-dependent conductances in cortical layer 5 pyramidal neurons. <em>Neuron</em>, <em>97</em>(6), 1315-1326.</p> <p> </p>
Data for: Chronic stress hinders sensory axon regeneration via impairing mitochondrial cristae and OXPHOS
<p>Spinal cord injury (SCI) often leads to physical limitations, chronic pain, significant life changes, and social isolation, increasing the risk of chronic psychological stress such as anxiety and depression. Despite the recognition of the negative effects of chronic stress on SCI recovery, the mechanisms linking stress and regeneration are not fully understood. In this study, we examined the impact of chronic stress on primary sensory axon regeneration in a mouse model of preconditioning lesions. Our findings showed that chronic stress caused mitochondrial damage and energy crisis within primary sensory neurons, hindering the regrowth of their central axons. The stress hormone corticosterone was identified as a critical factor in this process, impacting satellite glial cells instead of neurons by suppressing Kir4.1 expression and leading to increased neuronal hyperactivity and elevated ROS levels. These high levels of ROS altered the shape of the mitochondrial cristae and disrupted ATP production, which is essential for powering axonal regeneration. Our results highlight the importance of addressing psychological stress in SCI patients to promote sensory-motor rehabilitation.</p>
Axonal mRNA localization in response to neurotrophin treatment
<p>This file contains the required processed data required to implement the code located at https://github.com/RLuisier/AxonLoc that related to the manuscript Axonal mRNA localization in response to neurotrophin treatment by Luisier et al. 2023.</p>
Data from: Electrical imaging of cortical and spinal axons using high-density microelectrode arrays
<div> <div> <div> <p>Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. </p> <p>Complementary-metal-oxide-semiconductor (CMOS) -based high-density microelectrode arrays (HD-MEAs) have been designed to record extracellular action potentials from neuronal cultures and allow tracking axonal signals across hundreds of microelectrodes. Thanks to a low-noise CMOS-design, HD-MEAs enable detection of APs across entire arbors of cortical axons. HD-MEAs provide noninvasive access to axonal action potentials and impose no constraints on the duration of the recording sessions. Here we present extracellular electrical activity recorded from rat's primary neurons using CMOS-based HD-MEA system (MaxWell Biosystems AG). Datasets comprise electrophysiological recordings obtained from primary motor and cortical neurons. Recorded signals were up-sampled to 200 kHz following the Whitaker-Shannon interpolation formula. Recorded signals were spike-sorted and spike-trigger averaged across an entire array (26400 electrodes). Such signal representation is referred to as 'axonal electrical image'. </p> </div> </div> </div>
Positive and biphasic extracellular waveforms correspond to return currents and axonal spikes - dataset
<p>Dataset used in Someck et al., 2023, "Positive and biphasic extracellular waveforms correspond to return currents and axonal spikes." Structure contains 9160 units. Details and code are available at https://github.com/EranStarkLab/NonNegativeSpikes.</p>
Data files for Axonal transport of autophagosomes is regulated by dynein activators JIP3/JIP4 and ARF/RAB GTPases
<p>Supporting data files for <strong>Axonal transport of autophagosomes is regulated by dynein activators JIP3/JIP4 and ARF/RAB GTPases</strong></p>
Noninvasive quantification of axon radii using diffusion MRI
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.