{
  "abstract": "Microstate analysis starts with clustering and the meta-criterion is a heuristic to find an optimum cluster number. We address the following questions: (i) what number is found for non-cluster-forming dynamical systems, (ii) do centroids fall in random attractor regions, (iii) do EEG topographies form clusters or a single connected structure in sensor space? We find that (i) the meta-criterion suggests spurious optimal cluster numbers (4-8) with high confidence on different attractor geometries, (ii) cluster centroids reliably fall in the same attractor regions, (iii) topological analysis of dynamical systems and resting-state EEG suggests that all form a single connected structure in their respective phase space, not clusters. We conclude that the meta-criterion should be used with caution and its results should not be taken as representing a ground truth. Cluster numbers deviating from the meta-criterion should not be discarded. A more far-reaching implication is that evidence for the existence of clusters in resting-state EEG data is still lacking. Microstate clustering may correspond to the partitioning of a single connected structure.",
  "abstract_shown": true,
  "affiliations": [
    "University of New South Wales"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "F. von Wegner"
    },
    {
      "name": "G. Hermann"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cm546xfwdj550.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.06.749668",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.06.749668v1.full",
  "id": "cm546xfwdj550",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.06.749668v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "neuroscience"
    ],
    [
      "openalex",
      "1702|Advanced Clustering Algorithms Research"
    ]
  ],
  "openalex": "W7210283898",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.06.749668v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-06",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/cm546xfwdj550.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:56Z",
      "native_id": "10.64898/2026.09.06.749668",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.06.749668v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "Clustering without clusters: the meta-criterion and centroid reliability mistake continuous dynamics for discrete states",
  "title_text": "Clustering without clusters: the meta-criterion and centroid reliability mistake continuous dynamics for discrete states",
  "type": "preprint",
  "updated_at": "2026-10-30T12:21:56Z",
  "url": "https://research.draconitic.com/paper/cm546xfwdj550",
  "venue": "bioRxiv",
  "versions": []
}