Abstract Over the past several decades, the ability to record from large populations of neurons (e.g., multi-electrode arrays, neuropixels, calcium imaging) has increased exponentially, opening new avenues for understanding the brain. While these data promise a qualitatively different view of brain activity than was previously possible, interpreting them will require the development of new analytical tools. A framework is provided by the tools of dynamical systems, which offer the means to uncover coordinated time-varying activation patterns expressed across an interconnected network of recorded neurons, and to characterize how these patterns relate to behavior. This framework has provided fundamental new insights into information processing in cortical circuits, including those underlying motor, sensory, and cognitive processes. However, analytical approaches to uncovering dynamics have typically been developed and tested in specific brain areas, for limited behaviors, in restricted behavioral settings. We are addressing the challenge of generalized applicability to diverse brain areas through a powerful new open-source toolkit for automated discovery of neural population dynamics. Our approach, AutoLFADS, uses recurrent neural networks to uncover dynamics and allows straightforward application to data from different brain areas and behaviors. We have now validated the generalizability of AutoLFADS using electrophysiology data from monkeys and rats, and two-photon imaging data from mice. Our objective in this supplement is to enable neuroscientist of from a variety of backgrounds to easily and robustly our powerful tools for modeling the dynamics of large populations of neurons. The specific aims of this supplement are 1) technical development to increase the flexibility of AutoLFADS and decrease its computational requirements, to facilitate broad dissemination, and 2) working directly with end users to increase adoption and lower barriers to entry, first through usability case studies with individual labs, and then through virtual workshops, office hours, and one-on-one sessions with interested end users. All generated content (code, documentation, tutorial notebooks, workshop videos) will be made freely available online. Through the aims of this supplement, we will produce a powerful, general, and easy-to-use resource for neuroscientists to probe the dynamics of large neural populations. In line with the goals of the BRAIN initiative, the resulting tools will be uniquely suited to help advance our understanding of the complex, nonlinear, and nonintuitive activity of large neural populations that underlies brain function and behavior.