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https://github.com/mcmelo22/Licktech/tree/main

Lickometer system based on open-source hardware platform with user-friendly interface software, capable of simultaneously receiving data from eight automated cages with two drinking bottles each. Device to acquire high-quality and detailed data. Adaptable to new types of sensors or other neuroscience tools capable of measuring brain activity simultaneously to the behavior.

Proper citation: Lickometer Box (RRID:SCR_025248) Copy   

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https://github.com/bkntr/brainways

Open source software that automatically registers coronal slices and quantifies fluorescent markers. Python based, AI registration algorithm for slice matching to the Waxholm rat atlas. Slice quantification can be trained on any atlas, which allows use for other subjects such as mice, zebrafish, and humans. AI-based software for registration and analysis of fluorescent markers on coronal brain slices.

Proper citation: Brainways (RRID:SCR_024402) Copy   

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http://surfer.nmr.mgh.harvard.edu/

Open source software suite for processing and analyzing human brain MRI images. Used for reconstruction of brain cortical surface from structural MRI data, and overlay of functional MRI data onto reconstructed surface. Contains automatic structural imaging stream for processing cross sectional and longitudinal data. Provides anatomical analysis tools, including: representation of cortical surface between white and gray matter, representation of the pial surface, segmentation of white matter from rest of brain, skull stripping, B1 bias field correction, nonlinear registration of cortical surface of individual with stereotaxic atlas, labeling of regions of cortical surface, statistical analysis of group morphometry differences, and labeling of subcortical brain structures.Operating System: Linux, macOS.

Proper citation: FreeSurfer (RRID:SCR_001847) Copy   

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http://www.nitrc.org/projects/gamma_suite/

GAMMA suite is an open-source cross-platform data mining software package designed to analyze neuroimaging data. A neuroimaging study often focuses on biomarker detection and classification. We designed and implemented a Bayesian, multivariate, nonparametric suite of algorithms for analyzing neuroimaging data. The GAMMA suite can be used for brain morphometric analysis, lesion-deficit analysis, and functional MR data analysis.

Proper citation: GAMMA (RRID:SCR_009484) Copy   

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http://humanconnectome.org/connectome/connectomeDB.html

Data management platform that houses all data generated by the Human Connectome Project - image data, clinical evaluations, behavioral data and more. ConnectomeDB stores raw image data, as well as results of analysis and processing pipelines. Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. ConnectomeDB is designed to be a data-mining tool, that allows users to generate and test hypotheses based on groups of subjects. Using the ConnectomeDB interface, users can easily search, browse and filter large amounts of subject data, and download necessary files for many kinds of analysis. ConnectomeDB is designed to work seamlessly with Connectome Workbench, an interactive, multidimensional visualization platform designed specifically for handling connectivity data. De-identified data within ConnectomeDB is publicly accessible. Access to additional data may be available to qualified research investigators. ConnectomeDB is being hosted on a BlueArc storage platform housed at Washington University through the year 2020. This data platform is based on XNAT, an open-source image informatics software toolkit developed by the NRG at Washington University. ConnectomeDB itself is fully open source.

Proper citation: ConnectomeDB (RRID:SCR_004830) Copy   

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https://edspace.american.edu/openbehavior/

Repository of open source tools for behavioral neuroscience research. OpenBehavior features hardware (tools, devices, apparatuses), as well as software for data acquisition and analysis and for the investigation of animal behavior and cognition. Dedicated to accelerating research through promotion of collaboration and open source projects.

Proper citation: OpenBehavior (RRID:SCR_015938) Copy   

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http://toolkit.bcblab.com/

Software toolkit that provides several multi-modal tools to assess brain disconnections and remote effects of lesions. All modules are designed to process brain lesion data with a normalization algorithm, a module to estimate the probability and the severity of white matter disconnections, and a tool to build a map of the disconnected areas.

Proper citation: BCBtoolkit (RRID:SCR_015519) Copy   

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http://www.na-mic.org/

The National Alliance for Medical Image Computing (NA-MIC) is a multi-institutional, interdisciplinary team of computer scientists, software engineers, and medical investigators who develop computational tools for the analysis and visualization of medical image data. The purpose of the Center is to provide the infrastructure and environment for the development of computational algorithms and open-source technologies, and then oversee the training and dissemination of these tools to the medical research community. Electronic resources provided by NA-MIC include software, data, tutorials, presentations, and more.

Proper citation: National Alliance for Medical Image Computing (RRID:SCR_004460) Copy   

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http://scanimage.vidriotechnologies.com/

Open source software application for laser scanning microscopy, electrophysiology, laser scanning photostimulation, and other physiological methods focused on neurobiology. Used to control laser scanning microscopes without need for custom data acquisition hardware. Standard data acquisition boards are used to acquire data and control laser scanning. The tasks of signal integration and image processing are placed on the computer CPU. Multiple versions of ScanImage are available, each with their own features.

Proper citation: ScanImage (RRID:SCR_014307) Copy   

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https://www.nitrc.org/projects/gmac_2012/

Open-source software toolbox implemented multivariate spectral Granger Causality Analysis for studying brain connectivity using fMRI data. Available features are: fMRI data importing, network nodes definition, time series preprocessing, multivariate autoregressive modeling, spectral Granger causality indexes estimation, statistical significance assessment using surrogate data, network analysis and visualization of connectivity results. All functions are integrated into a graphical user interface developed in Matlab environment. Dependencies: Matlab, BIOSIG, SPM, MarsBar.

Proper citation: GMAC: A Matlab toolbox for spectral Granger causality analysis of fMRI data (RRID:SCR_009581) Copy   

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https://pmc.ncbi.nlm.nih.gov/articles/PMC10731520/

Cost-effective, compact foot-print, and open-source Raspberry Pi-based widefield imaging system. Used for close-proximity dual-brain cortical mesoscale functional-imaging to simultaneously observe activity in two head-fixed animals in staged social touch-like interaction. We provide all schematics, code, and protocols for a rail system where head-fixed mice are brought together to a distance where the macrovibrissae of each mouse make contact.

Proper citation: Meso-Py (RRID:SCR_026530) Copy   

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https://hnn.brown.edu/

Open source software package for circuit level interpretation of human EEG/MEG data. Software tool for interpreting cellular and network origin of human MEG/EEG data. Simulates electrical activity of neocortical cells and circuits that generate primary electrical currents underlying EEG/MEG recordings. Designed for researchers and clinicians, without computational neural modeling experience, to develop and test hypothesis on circuit origin of their data.

Proper citation: Human Neocortical Neurosolver (RRID:SCR_017437) Copy   

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http://econnectome.umn.edu/

An open-source MATLAB software package for imaging brain functional connectivity from electrophysiological signals. It provides interactive graphical interfaces for EEG/ECoG/MEG preprocessing, source estimation, connectivity analysis and visualization. Connectivity from EEG/ECoG/MEG can be mapped over sensor and source domains. This package is designed for use by researchers in neuroscience, psychology, cognitive science, clinical neurophysiology, neurology and other disciplines. The graphical interface-based platform requires little programming knowledge or experience with MATLAB. eConnectome is developed by the Biomedical Functional Imaging and Neuroengineering Laboratory at the University of Minnesota, directed by Dr. Bin He. The visualization module is jointly developed with Drs. Fabio Babiloni and Laura Astolfi at the University of Rome La Sapienza.

Proper citation: eConnectome (RRID:SCR_009618) Copy   

•   Source: SciCrunch Registry
  

http://neurosynth.org

Platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. It''s a website wrapped around a set of open-source Python and JavaScript packages. Neurosynth lets you run crude but useful analyses of fMRI data on a very large scale. You can: * Interactively visualize the results of over 3,000 term-based meta-analyses * Select specific locations in the human brain and view associated terms * Browse through the nearly 10,000 studies in the database Their ultimate goal is to enable dynamic real-time analysis, so that you''ll be able to select foci, tables, or entire studies for analysis and run a full-blown meta-analysis without leaving your browser. You''ll also be able to do things like upload entirely new images and obtain probabilistic estimates of the cognitive states most likely to be associated with the image.

Proper citation: NeuroSynth (RRID:SCR_006798) Copy   

•   Source: SciCrunch Registry
  

https://www.cmtk.org/

A Python-based open source toolkit for magnetic resonance connectome mapping, data management, sharing, visualization and analysis. The toolkit includes the connectome mapper (a full DMRI processing pipeline), a new file format for multi modal data and metadata, and a visualization application.

Proper citation: Connectome Mapping Toolkit (RRID:SCR_001644) Copy   

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http://vano.cellexplorer.org/

VANO is a Volume image object AnNOtation System for 3D multicolor image stacks, developed by Hanchuan Peng, Fuhui Long, and Gene Myers. VANO provides a well-coordinated way to annotate hundreds or thousands of 3D image objects. It combines 3D views of images and spread sheet neatly, and is just easy to manage 3D segmented image objects. It also lets you incorporate your segmentation priors, and lets you edit your segmentation results! This system has been used in building the first digital nuclei atlases of C. elegans at the post-embryonic stage (joint work with Stuart Kim lab, Stanford Univ), the single-neuron level fruit fly neuronal atlas of late embryos (with Chris Doe lab, Univ of Oregon, HHMI), and the compartment-level of digital map(s) of adult fruit fly brains (several labs at Janelia Farm, HHMI). VANO is cross-platform software. Currently the downloadable versions are for Windows (XP and Vista) and Mac (Intel-chip based, Leopard or Tiger OS). If you need VANO for different systems (such as 64bit or 32bit, Redhat Linux, Ubuntu, etc), you can either compile the software, or send an email to pengh (at) janelia.hhmi.org. VANO is Open-Source. You can download both the source code files and pre-complied versions at the Software Downloads page.

Proper citation: Volume image object AnNOtation System (RRID:SCR_003393) Copy   

•   Source: SciCrunch Registry
  

https://www.digitalpsych.org/mindlamp1.html

Core collects data to capture and consider the real-time lived experiences of patients. Uses open-source digital platform and mobile app for neuropsychiatric research and clinical care, to monitor, support, and improve brain health by collecting real-time data (like location, activity, heart rate via sensors), conducting digital assessments (surveys, cognitive tests), and delivering interventions (meditation, journaling, psychoeducation) to patients and clinicians. It helps study behavioral patterns, track symptoms, and personalize mental health treatment through features organized around Learn, Assess, Manage, and Prevent.

Proper citation: BIDMC Division of Digital Psychiatry LAMP platform Core Facility (RRID:SCR_027767) Copy   

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https://github.com/openconnectome/Rambo3D

A web and GPU enabled stand-alone app for viewing volumes at arbitrary cutting planes and zoom levels.

Proper citation: Rambo3D (RRID:SCR_006357) Copy   

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https://www.nitrc.org/projects/atpp

Integrated pipeline for tractography-based brain parcellation with automatic processing and massive parallel computing. ATPP offers a CLI version for parcellating multiple brain regions and a GUI version for parcellating a specific brain region. " ATPP completely follows the scientific cultural shift to open science, which aims at making scientific research including journal papers, lab notes, data, and, of course, workflow tools, accessible and transparent to all levels of society. ATPP is publicly accessible in Neuroimaging Informatics Tools and Resources Clearinghouse8 (NITRC) (https://www.nitrc.org/projects/atpp). Its source codes are hosted in GitHub9 (https://github.com/haililihai/ATPP_CLI; https://github.com/haililihai/ATPP_GUI), under the GNU generic purpose license version 310 (GPLv3), and are welcome to download and fork. The Digital Object Identifiers (DOIs) providing a persistent way to make digital data easily and uniquely citable was created from Zenodo11 platform with those GitHub repositories (ATPP CLI v2.0.0, doi: https://doi.org/10.5281/zenodo.239702; ATPP GUI v2.0.0, doi: https://doi.org/10.5281/zenodo.239705). "

Proper citation: Automatic Tractography-based Parcellation Pipeline (RRID:SCR_014815) Copy   

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https://broadinstitute.github.io/warp/docs/Pipelines/snm3C/README

Software open-source, cloud-optimized computational workflow for processing single-nucleus methylome and chromatin contact (snm3C) sequencing data. The workflow is designed to demultiplex and align raw sequencing reads, call chromatin contacts, and generate summary metrics.

Proper citation: snm3C Pipeline (RRID:SCR_025041) Copy   

•   Source: SciCrunch Registry