A weighted model of perception and decision-making between targets of finite size

[2608.27670] A weighted model of perception and decision-making between targets of finite size Skip to main content Search Submit Donate Log in Quantitative Biology > Neurons and Cognition arXiv:2608.27670 (q-bio) [Submitted on 27 Aug 2026] Title: A weighted model of perception and decision-making between targets of finite size Authors: W. Christopher Strickland , Andrew J. Bernoff View PDF HTML (experimental) Abstract: Recent research grounded in experiments has connected neural ring models of vision to how animals navigate a complex landscape of attractive targets. In this paper we investigate the mathematical and biological implications of a three-stage model where animals pre-process visual stimuli to identify a discrete set of targets, process this input to select the dominant targets, and then post-process this information to navigate the landscape. Incorporating finite target sizes and a neural density allows consistent target acquisition and pursuit reflecting what is seen in nature. Mathematically, we show this model corresponds to an energy minimization problem, simplifying both its analysis and numerical implementation. Biologically, we argue that the model is physiologically motivated, reproduces experimental observations, and presents a fairly direct pathway to decoding neural geometry via empirical data. Our results also demonstrate an analysis pipeline for future model extensions and suggest specific avenues for experimental research to test and parameterize our quantitative framework. Subjects: Neurons and Cognition (q-bio.NC) ; Dynamical Systems (math.DS); Biological Physics (physics.bio-ph) MSC classes: 37N25 Cite as: arXiv:2608.27670 [q-bio.NC] (or arXiv:2608.27670v1 [q-bio.NC] for this version) https://doi.org/10.48550/arXiv.2608.27670 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Andrew Bernoff [ view email ] [v1] Thu, 27 Aug 2026 19:56:54 UTC (15,073 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Current browse context: q-bio.NC < prev | next > new | recent | 2026-08 Change to browse by: math math.DS physics physics.bio-ph q-bio References & Citations SciX Google Scholar Semantic Scholar export BibTeX citation 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)

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