Project Summary Experiments aimed at discovering how the brain works generate vast amounts of data that span multiple scales: from interactions between individual molecules to waves of electrical activity across the entire brain. Computational modeling provides a way to integrate and make sense of these data. Through the parent grant U24EB028998 we are developing and disseminating NetPyNE, a tool for data-driven multiscale modeling of brain circuits. This tool provides both a programmatic and graphical high-level interface to the widely-used NEURON simulator that facilitates the development, parallel simulation, optimization and analysis of biophysically detailed neuronal circuits. NetPyNE is unique compared to other neural circuit modeling tools (e.g. NEST, Brian) in incorporating NEURON's molecular reaction-diffusion (RxD) module, which allows for detailed simulation of intracellular and extracellular chemical signaling linked to electrophysiology. Significant progress has been made towards achieving the parent grant goal of transforming NetPyNE into a solid and well-tested tool with a fully-featured GUI, and widely disseminating the tool among the scientific community. This is evidenced through a growing user base -- the tool has been used to develop at least 97 models from over 40 institutions worldwide, and has contributed to over 30 peer-reviewed publications. NetPyNE has also been integrated or interfaced with multiple standards, tools and platforms in the community including the NeuroML and SONATA, the Open Source Brain, EBRAINS and The Neuroscience Gateway (NSG), HNN, SciUnit/SciDash, LFPy and coreNEURON tools. The goal of this supplement is to enhance NetPyNE's interoperability by transforming a proof-of-concept interface between NetPyNE and The Virtual Brain (TVB) into a robust, user-friendly, scalable and efficient software that is portable across three cloud environments (EBRAINS, The Neuroscience Gateway and Google Cloud, via NIH STRIDES). TVB is the worldwide reference tool for simulating macroscale whole-brain network models derived from multi modal MRI (anatomical, functional and diffusion) and EEG datasets. The TVB-NetPyNE interface therefore achieves a new milestone for multiscale modeling: linking molecular chemical signaling to whole-brain network dynamics. Through this supplement we will also increase user adoption and community engagement of both NetPyNE and the TVB-NetPyNE interface through 1) documentation, tutorials and example workflows; 2) dissemination and training via workshops and courses; and 3) following software engineering and sharing best practices. This project broadens the potential user base of NetPyNE by attracting new users from the TVB and cloud platform communities, and more generally, clinicians and researchers working with MRI, EEG and MEG data. TVB has been downloaded over 38,000 times, and has been used to construct and simulate over 1000 individual, connectome-based brain network models and contribu...