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http://kimlab.io/brain-map/atlas/

Website to visualize and share anatomical labels. Franklin and Paxinos (FP) based anatomical labels in Allen Common Coordinate Framework (CCF). Cell type specific transgenic mice and MRI atlas were used to adjust and further segment labels. New segmentations were created in dorsal striatum using cortico-striatal connectivity data. Anatomical labels were digitized based on Allen ontology, and web-interface was created for easy visualization. These labels provide resource to isolate and identify mouse brain anatomical structures. Open source data sharing will facilitate further refinement of anatomical labels and integration of data interpretation within single anatomical platform.

Proper citation: Enhanced and Unified Anatomical Labeling for Common Mouse Brain Atlas (RRID:SCR_019267) Copy   

•   Source: SciCrunch Registry

http://www.med.unc.edu/bric/ideagroup/free-softwares/unc-infant-0-1-2-atlases

3 atlases dedicated for neonates, 1-year-olds, and 2-year-olds. Each atlas comprises a set of 3D images made up of the intensity model, tissue probability maps, and anatomical parcellation map. These atlases are constructed with the help of state-of-the-art infant MR segmentation and groupwise registration methods, on a set of longitudinal images acquired from 95 normal infants (56 males and 39 females) at neonate, 1-year-old, and 2-year-old.

Proper citation: UNC Infant 0-1-2 Atlases (RRID:SCR_002569) Copy   

•   Source: SciCrunch Registry

http://www.gensat.org/retina.jsp

Collection of images from cell type-specific protein expression in retina using BAC transgenic mice. Images from cell type-specific protein expression in retina using BAC transgenic mice from GENSAT project.

Proper citation: Retina Project (RRID:SCR_002884) Copy   

•   Source: SciCrunch Registry

http://zebrafinch.brainarchitecture.org/

Atlas of high resolution Nissl stained digital images of the brain of the zebra finch, the mainstay of songbird research. The cytoarchitectural high resolution photographs and atlas presented here aim at facilitating electrode placement, connectional studies, and cytoarchitectonic analysis. This initial atlas is not in stereotaxic coordinate space. It is intended to complement the stereotaxic atlases of Akutegawa and Konishi, and that of Nixdorf and Bischof. (Akutagawa E. and Konishi M., stereotaxic atalas of the brain of zebra finch, unpublished. and Nixdorf-Bergweiler B. E. and Bischof H. J., A Stereotaxic Atlas of the Brain Of the Zebra Finch, Taeniopygia Guttata, http://www.ncbi.nlm.nih.gov.) The zebra finch has proven to be the most widely used model organism for the study of the neurological and behavioral development of birdsong. A unique strength of this research area is its integrative nature, encompassing field studies and ethologically grounded behavioral biology, as well as neurophysiological and molecular levels of analysis. The availability of dimensionally accurate and detailed atlases and photographs of the brain of male and female animals, as well as of the brain during development, can be expected to play an important role in this research program. Traditionally, atlases for the zebra finch brain have only been available in printed format, with the limitation of low image resolution of the cell stained sections. The advantages of a digital atlas over a traditional paper-based atlas are three-fold. * The digital atlas can be viewed at multiple resolutions. At low magnification, it provides an overview of brain sections and regions, while at higher magnification, it shows exquisite details of the cytoarchitectural structure. * It allows digital re-slicing of the brain. The original photographs of brain were taken in certain selected planes of section. However, the brains are seldom sliced in exactly the same plane in real experiments. Re-slicing provides a useful atlas in user-chosen planes, which are otherwise unavailable in the paper-based version. * It can be made available on the internet. High resolution histological datasets can be independently evaluated in light of new experimental anatomical, physiological and molecular studies.

Proper citation: Zebrafinch Brain Architecture Project (RRID:SCR_004277) Copy   

•   Source: SciCrunch Registry

http://www.tbi-impact.org/?p=impact%2Fcalc&btn_calc=GO+TO+CALCULATOR

A calculator that calculates the prediction models for 6 month outcome after Traumatic Brain Injury. Based on extensive prognostic analysis the IMPACT investigators have developed prognostic models for predicting 6 month outcome in adult patients with moderate to severe head injury (Glasgow Coma Scale <=12) on admission. By entering the characteristics into the calculator, the models will provide an estimate of the expected outcome at 6 months. We present three models of increasing complexity (Core, Core + CT, Core + CT + Lab). These models were developed and validated in collaboration with the CRASH trial collaborators on large numbers of individual patient data (the IMPACT database). The models discriminate well, and are particularly suited for purposes of classification and characterization of large cohorts of patients. Extreme caution is required when applying the estimated prognosis to individual patients. The sequential prediction models may be used as an aid to estimate 6 month outcome in patients with severe or moderate traumatic brain injury (TBI). However, the prediction rule can only complement, never replace, clinical judgment and can therefore be used only as a decision-support system.

Proper citation: IMPACT Prognostic Calculator (RRID:SCR_004730) Copy   

•   Source: SciCrunch Registry

https://www.gaitor.org

Software suite to analyse gait trials collected with Experimental Dynamic Gait Arena for Rodents. Used for rodent gait analysis.

Proper citation: GAITOR Suite (RRID:SCR_023031) Copy   

•   Source: SciCrunch Registry

https://cells.ucsc.edu/

Web based tool to visualize gene expression and metadata annotation distribution throughout single cell dataset or multiple datasets. Interactive viewer for single cell expression. You can click on and hover over cells to get meta information, search for genes to color on and click clusters to show cluster specific marker genes.

Proper citation: UCSC Cell Browser (RRID:SCR_023293) Copy   

•   Source: SciCrunch Registry

http://becs.aalto.fi/en/research/bayes/drifter/

Model based Bayesian method for eliminating physiological noise from fMRI data. This algorithm uses image voxel analysis to isolate the cardiac and respiratory noise from the relevant data.

Proper citation: DRIFTER (RRID:SCR_014937) Copy   

•   Source: SciCrunch Registry

https://github.com/flatironinstitute/mountainsort

Neurophysiological spike sorting software.

Proper citation: MountainSort (RRID:SCR_017446) Copy   

•   Source: SciCrunch Registry

https://cloudreg.neurodata.io/

Software automated, terascale, cloud based image analysis pipeline for preprocessing and cross modal, nonlinear registration between volumetric datasets with artifacts. Automatic terabyte scale cross modal brain volume registration.

Proper citation: CloudReg (RRID:SCR_022795) Copy   

•   Source: SciCrunch Registry

https://github.com/danbider/lightning-pose

Software video centric package for direct video manipulation. Semi supervised animal pose estimation algorithm, Bayesian post processing approach and deep learning package. Improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools.

Proper citation: Lightning Pose (RRID:SCR_024480) Copy   

•   Source: SciCrunch Registry

https://kimlab.io/brain-map/epDevAtlas/

Suite of open access resources including 3D atlases of early postnatally developing mouse brain and mapped cell type density growth charts, which can be used as standalone resources or to implement data integration. Web platform can be utilized to analyze and visualize the spatiotemporal growth of GABAergic, microglial, and cortical layer-specific cell type densities in 3D. Morphologically averaged symmetric template brains serve as the basis reference space and coordinate system with an isotropic resolution of 20 μm (XYZ in coronal plane). Average transformations were conducted at 20 μm voxel resolution by interpolating high resolution serial two photon tomography images from primarily Vip-IRES-Cre;Ai14 mice at postnatal (P) ages P4, P6, P8, P10, P12, and P14. For all ages, anatomical labels from the P56 Allen Mouse Brain Common Coordinate Framework (Allen CCFv3) were iteratively down registered to each early postnatal time point in a non-linear manner, aided by manual parcellations of landmarks in 3D, consistent with the Allen Mouse Reference Atlas Ontology.

Proper citation: Early Postnatal Developmental Mouse Brain Atlas (RRID:SCR_024725) Copy   

•   Source: SciCrunch Registry

https://github.com/mcelotto/Feature_Info_Transfer

Software application as MATLAB scripts to compute measures of Feature-specific Information Transfer (FIT) and conditional FIT (cFIT). FIT quantifies direction and magnitude of information flow about specific feature S (such as feature of sensory stimulus) between simultaneously recorded brain regions X and Y. cFIT quantifies amount of directed feature information transmitted between regions X and Y that cannot be potentially routed through region Z.

Proper citation: Feature-specific Information Transfer scripts (RRID:SCR_024772) Copy   

•   Source: SciCrunch Registry

http://dx.doi.org/10.5281/zenodo.21157

A graphical source code file used for an automated motion detection and reward system for animal training (see comment for full paper title). It was designed on the LabVIEW programming system. Running the program requires the appropriate LabVIEW runtime software from National Instruments Corporation.

Proper citation: Monkey Motion (RRID:SCR_014285) Copy   

•   Source: SciCrunch Registry

https://www.c4r-nih.org

Portal provides information about nationwide study of more than 50,000 individuals to determine factors that predict disease severity and long-term health impacts of COVID-19.

Proper citation: Collaborative Cohort of Cohorts for COVID-19 Research (RRID:SCR_026322) Copy   

•   Source: SciCrunch Registry

https://github.com/tomcatsmith19/ArucoDetection

Automated rodent behavioral scoring system, complete with 3D design files and code/software. System monitors behavioral engagement using open-source software. 3D design files and necessary software has been made available, as well as code that can be used for data analysis.

Proper citation: ArUco (RRID:SCR_026572) Copy   

•   Source: SciCrunch Registry

https://github.com/Washington-University/HCPpipelines

Software package as set of tools, primarily shell scripts, for processing multi-modal, high-quality MRI images for the Human Connectome Project. Minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space.

Proper citation: HCP Pipelines (RRID:SCR_026575) Copy   

•   Source: SciCrunch Registry

https://github.com/Yonghao-Holden/TEProf3

Software pipeline to detect Transposable Elements transcripts. Used to identify TE-derived promoters and transcripts using transcriptomic data from multiple sources, including short-read RNA-seq data, long-read RNA-seq data and single cell RNA-seq data.

Proper citation: TEProf3 (RRID:SCR_027288) Copy   

•   Source: SciCrunch Registry

https://github.com/smorabit/hdWGCNA

Software R package for performing weighted gene co-expression network analysis in high dimensional transcriptomics data such as single-cell RNA-seq or spatial transcriptomics.

Proper citation: hdWGCNA (RRID:SCR_027496) Copy   

•   Source: SciCrunch Registry

https://neurojson.io/

Web application for human-readable, searchable neuroimaging datasets using universally accessible JSON format and URL-based RESTful APIs. NeuroJSON.io is built upon highly scalable document-store NoSQL database technologies, specifically, open-source Apache CouchDB engine, that can handle millions of datasets without major performance penalties. Provides fine-grained data search capabilities to allow users to find, preview and re-combine complex data records from public datasets before download.

Proper citation: NeuroJSON.io (RRID:SCR_027793) Copy   

•   Source: SciCrunch Registry