{
  "abstract": "Multielectrode-array recordings of the retina reveal neural population activity at cellular resolution, but relating recurring population states to stimulus timing and single-unit responses requires several linked analysis steps. We present PHASOR (Population HMM Analysis of Stimulus-locked Output in the Retina), a pipeline that combines stimulus-clock alignment, Fourier-based response classification, hidden Markov modeling with Chow-Liu tree emissions, model-order selection, and state visualization. We evaluated the workflow with synthetic populations and demonstrated its use in ten ex vivo recordings from three wild-type retinas (two male, one female) and one male rd1 retina, including 2 Hz full-field sinusoidal stimulation. Across ten synthetic datasets containing seven generative states, selected model orders ranged from seven to nine, with a mean of 7.9, matching the generative count exactly in three of the ten datasets. A representative confusion matrix showed a near one-to-one correspondence between generative and decoded states, with a single additional low-occupancy state, illustrating the distinction between recovering temporal structure and recovering the exact state count. In a representative retinal recording, response classes differed in stimulus phase and contrast dependence, and decoded states differed in occupancy, dwell time, and active-unit composition. Recordings during L-AP4 application, without projected stimulation, and in a photoreceptor-degenerate rd1 retina illustrated changes in the resulting population-state descriptions. PHASOR integrates established analysis methods into a reusable workflow for relating stimulus-associated population activity to functional response classes. The selected states provide a descriptive model of population activity; their number and correspondence to biological assemblies require separate validation.",
  "abstract_shown": true,
  "affiliations": [
    "SUNY Upstate Medical University"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "name": "M. J. Shaik"
    },
    {
      "name": "S. Chen"
    },
    {
      "name": "J. Jin"
    },
    {
      "affs": [
        0
      ],
      "name": "D. Babino"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dveza68fec0f1.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.27.762251",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.27.762251v1.full",
  "id": "dveza68fec0f1",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.27.762251v1",
  "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": null,
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.27.762251v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-27",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/dveza68fec0f1.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T00:21:26Z",
      "native_id": "10.64898/2026.10.27.762251",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.27.762251v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "PHASOR: An Open-Source Pipeline for Hidden Markov Model Analysis of Stimulus-Locked Retinal Multielectrode-Array Population Activity",
  "title_text": "PHASOR: An Open-Source Pipeline for Hidden Markov Model Analysis of Stimulus-Locked Retinal Multielectrode-Array Population Activity",
  "type": "preprint",
  "updated_at": "2026-11-04T12:20:54Z",
  "url": "https://research.draconitic.com/paper/dveza68fec0f1",
  "venue": "bioRxiv",
  "versions": []
}