A Practical Guide to Tuning Spiking Neuronal Dynamics for Computational Neuroscience and NeuroAI Research

[2506.08138] A Practical Guide to Tuning Spiking Neuronal Dynamics for Computational Neuroscience and NeuroAI Research Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Neural and Evolutionary Computing arXiv:2506.08138 (cs) [Submitted on 9 Jun 2025 ( v1 ), last revised 14 Aug 2026 (this version, v2)] Title: A Practical Guide to Tuning Spiking Neuronal Dynamics for Computational Neuroscience and NeuroAI Research Authors: William Gebhardt , Nathan McDonald , Clare Thiem , Jack Lombardi , Cory Merkel , Alexander G. Ororbia View a PDF of the paper titled A Practical Guide to Tuning Spiking Neuronal Dynamics for Computational Neuroscience and NeuroAI Research, by William Gebhardt and 5 other authors View PDF HTML (experimental) Abstract: In this work, we examine and study the 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 as well as how hyperparameter value settings affect model behavior. Beyond hyperparameters, we study and discuss other important design elements of SNNs -- the choice of input encoding, the construction of a neural assembly, and the setup for excitatory-inhibitory populations -- and how these impact neuronal dynamics. Comments: Expanded Version Subjects: Neural and Evolutionary Computing (cs.NE) ; Neurons and Cognition (q-bio.NC) Cite as: arXiv:2506.08138 [cs.NE] (or arXiv:2506.08138v2 [cs.NE] for this version) https://doi.org/10.48550/arXiv.2506.08138 Focus to learn more arXiv-issued DOI via DataCite Submission history From: William Gebhardt [ view email ] [v1] Mon, 9 Jun 2025 18:41:11 UTC (1,908 KB) [v2] Fri, 14 Aug 2026 19:15:26 UTC (1,803 KB) Full-text links: Access Paper: View a PDF of the paper titled A Practical Guide to Tuning Spiking Neuronal Dynamics for Computational Neuroscience and NeuroAI Research, by William Gebhardt and 5 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.NE < prev | next > new | recent | 2025-06 Change to browse by: cs q-bio q-bio.NC References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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