Abstract
We introduce NeuroXiv ( neuroxiv.org ), a large-scale, AI-powered database that provides detailed 3D morphologies of individual neurons mapped to a standard brain atlas, designed to support a wide array of dynamic, interactive neuroscience applications. NeuroXiv offers a comprehensive collection of 175,149 atlas-oriented reconstructed morphologies of individual neurons derived from more than 518 mouse brains, classified into 292 distinct types and mapped into the Common Coordinate Framework Version 3 (CCFv3). Different from conventional static brain atlases that are often limited to data-browsing, NeuroXiv allows interactive analyses as well as uploading and databasing custom neuron morphologies, which are mapped to the brain atlas for objective comparisons. Powered by a cutting-edge AI engine (AIPOM), NeuroXiv enables dynamic, user-specific analysis and data mining. We specifically developed a mixture-of-experts algorithm to harness the capabilities of multiple large language models. We also developed a client program to achieve more than 10 times better performance compared to a typical server-side setup. We demonstrate NeuroXiv’s scalability, efficiency, flexibility, openness, and robustness through various applications.
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Abstract
We introduce NeuroXiv (neuroxiv.org), a large-scale, AI-powered database that provides detailed 3D morphologies of individual neurons mapped to a standard brain atlas, designed to support a wide array of dynamic, interactive neuroscience applications. NeuroXiv offers a comprehensive collection of 175,149 atlas-oriented reconstructed morphologies of individual neurons derived from more than 518 mouse brains, classified into 292 distinct types and mapped into the Common Coordinate Framework Version 3 (CCFv3). Different from conventional static brain atlases that are often limited to data-browsing, NeuroXiv allows interactive analyses as well as uploading and databasing custom neuron morphologies, which are mapped to the brain atlas for objective comparisons. Powered by a cutting-edge AI engine (AIPOM), NeuroXiv enables dynamic, user-specific analysis and data mining. We specifically developed a mixture-of-experts algorithm to harness the capabilities of multiple large language models. We also developed a client program to achieve more than 10 times better performance compared to a typical server-side setup. We demonstrate NeuroXiv’s scalability, efficiency, flexibility, openness, and robustness through various applications.
Competing Interest Statement
The authors have declared no competing interest.
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