{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-practical-guide-to-tuning-spiking-neuronal","title":"A Practical Guide to Tuning Spiking Neuronal Dynamics","arxiv_id":"2506.08138","date":"2025-06-09","proceeding":null,"authors":["William Gebhardt","Alexander G. Ororbia","Nathan McDonald","Clare Thiem","Jack Lombardi"],"abstract":"In this work, we examine fundamental elements of spiking neural networks (SNNs) as well as how to tune them. Concretely, we focus on two different foundational neuronal units utilized in SNNs -- the leaky integrate-and-fire (LIF) and the resonate-and-fire (RAF) neuron. We explore key equations and how hyperparameter values affect behavior. Beyond hyperparameters, we discuss other important design elements of SNNs -- the choice of input encoding and the setup for excitatory-inhibitory populations -- and how these impact LIF and RAF dynamics.","url_abs":"https://arxiv.org/abs/2506.08138v1","url_pdf":"https://arxiv.org/pdf/2506.08138v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-practical-guide-to-tuning-spiking-neuronal","repo_url":"https://github.com/naclab/snndynamicspracticalguide","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"jax","reach":null}],"tasks":[],"methods":[{"method_slug":"focus","method_name":"Focus"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}