{
  "abstract": "Understanding the neural basis of human cognition requires measuring not only localized brain activity but also how functional interactions between brain regions change in response to different cognitive demands. Event-related fMRI is an efficient design for linking trial-wise behavioral and computational variables to brain activity, but comparable methods for examining their effects on functional connectivity remain limited. Here, we introduce a regression-based beta-series modeling (BSM) framework that leverages single-trial response estimates from event-related fMRI to quantify how task-related variables modulate functional connectivity. By modeling the interaction between regional activity and task-related variables, this framework provides a statistical approach for testing connectivity modulation by both continuous and categorical variables. We evaluated this approach using comprehensive simulations across several experimental conditions and signal qualities. The regression-based BSM approach can sensitively detect ground-truth effects with well-controlled false-positive rates. Compared with generalized psychophysiological interaction, BSM achieved comparable performance across most conditions while demonstrating improved statistical power under lower signal-to-noise conditions. We further validated the approach using empirical event-related fMRI data. Distinct trial-wise cognitive variables selectively modulated functional connectivity during their corresponding trial epochs, demonstrating the temporal specificity and flexibility of the approach. Together, these findings demonstrate that regression-based BSM provides a flexible framework for examining task-modulated functional connectivity in event-related fMRI, with applications ranging from conventional experimental manipulations to continuous computational model-derived variables.",
  "abstract_shown": true,
  "affiliations": [
    "University of Iowa"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "K. Hwang"
    },
    {
      "name": "S. E. Stokes"
    },
    {
      "name": "S. C. Leach"
    },
    {
      "name": "J. Jiang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6qyhhn9p27ppq.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.07.15.738746",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.07.15.738746v2.full",
  "id": "6qyhhn9p27ppq",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.07.15.738746v2",
  "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|Functional Brain Connectivity Studies"
    ]
  ],
  "openalex": "W7169870418",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.07.15.738746v2.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-07-15",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6qyhhn9p27ppq.ris",
  "sources": [
    {
      "first_seen": "2026-11-13T00:25:17Z",
      "native_id": "10.64898/2026.07.15.738746",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.07.15.738746v2"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "Estimating trial-wise modulation of functional connectivity using event-related fMRI",
  "title_text": "Estimating trial-wise modulation of functional connectivity using event-related fMRI",
  "type": "preprint",
  "updated_at": "2026-11-13T12:20:46Z",
  "url": "https://research.draconitic.com/paper/6qyhhn9p27ppq",
  "venue": "bioRxiv",
  "versions": []
}