{
  "abstract": "Human quiet standing relies on vestibular, proprioceptive, and visual information whose contributions change with sensory context. Dynamic posturography characterizes this reweighting through responses to visual-scene and support-surface perturbations, but a compact mathematical account of how sensory reliability propagates from state estimation to postural action remains incomplete. We develop a minimal quiet-standing model in which sensory reliability is encoded by channel-specific precision parameters that weight sensory prediction errors. A one-link inverted pendulum receives vestibular, proprioceptive, and visual observations, estimates posture using an active-inference variational free-energy objective over temporally embedded states, and selects ankle torque by minimizing the same free-energy form under an upright sensory goal. Changes in sensory conditions enter the model only through the relative channel precisions; body dynamics, the action optimizer, and the upright goal prior are held fixed. A fixed-point analysis yields closed-form predictions: the perturbation-induced belief bias, each channels state-update contribution, and the resulting posture shifts are set by relative channel precisions, with a stability condition on the upright goal. Closed-loop simulations confirmed these predictions: reducing an unreliable channels precision reduced perturbation-driven postural shifts by approximately 82%, as predicted, with a matching decrease in that channels state-update contribution, identifying belief updating as the mechanism of reweighting. A graded reliability-to-precision mapping monotonically controlled sensory contribution, and reweighting required relative, channel-selective precision changes rather than a global reduction. These results provide a compact mathematical account of postural sensory reweighting as relative, context-selective precision control in a closed-loop multisensory system.",
  "abstract_shown": true,
  "affiliations": [
    "Kyushu Institute of Technology"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "J. Kobayashi"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/27m2v21pxgq8h.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.06.23.733972",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.06.23.733972v3.full",
  "id": "27m2v21pxgq8h",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.06.23.733972v3",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "neuroscience"
    ],
    [
      "openalex",
      "2805|Embodied and Extended Cognition"
    ]
  ],
  "openalex": "W7166595530",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.06.23.733972v3.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-06-23",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/27m2v21pxgq8h.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:43Z",
      "native_id": "10.64898/2026.06.23.733972",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.06.23.733972v4"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "A Mathematical Model of Reliability-Dependent Sensory Reweighting in Quiet Standing",
  "title_text": "A Mathematical Model of Reliability-Dependent Sensory Reweighting in Quiet Standing",
  "type": "preprint",
  "updated_at": "2026-11-08T00:20:56Z",
  "url": "https://research.draconitic.com/paper/27m2v21pxgq8h",
  "venue": "bioRxiv",
  "versions": []
}