A curated list of awesome neuroscience libraries, software, and resources for researchers and developers.
Awesome Neuroscience is a curated collection of software libraries, tools, datasets, and educational resources focused on neuroscience research and applications. It aggregates high-quality open-source projects and materials across programming languages like Python, MATLAB, and R to support computational modeling, neuroimaging analysis, and experimental neuroscience.
Neuroscience researchers, computational biologists, data scientists, and students seeking tools for brain data analysis, neural simulation, or neuroimaging. It's also valuable for developers building neuroscience applications or libraries.
It saves time by providing a vetted, centralized directory of neuroscience resources, eliminating the need to search scattered sources. The list is community-maintained, ensuring quality and relevance across multiple domains within neuroscience.
A curated list of awesome neuroscience libraries, software and any content related to the domain.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Aggregates libraries across Python, MATLAB, C++, JavaScript, and R, such as Nengo for brain modeling and EEGLAB for EEG analysis, ensuring relevance for diverse programming environments.
Includes ebooks, MOOCs like Harvard's neuroscience course, and blogs, providing comprehensive learning paths from introductory to advanced topics.
Highlights tools for specific domains like neuroimaging with Nilearn, spiking neural networks with Brian2, and experimental design with PsychoPy, catering to niche research needs.
Links to publicly available datasets, such as those in the Awesome Public Datasets list, supporting reproducible research and data-driven neuroscience projects.
As a community-driven list, it may not be regularly updated, leading to outdated links or missing the latest software releases and updates.
While it lists educational resources, it doesn't provide hands-on examples or tutorials, requiring users to navigate external sites for practical guidance.
Focuses primarily on open-source and academic tools, so users seeking commercial neuroscience software or advanced enterprise solutions might find it insufficient.