{
  "abstract": "We examined whether and how tactile EEG experiments could be done through self-assessments by participants at home or through online experiments with consumer-grade mobile EEG devices. As a first step towards this aim, we performed a Flanker task in an online scenario with a MUSE headband and similarly a conventional lab experiment with a standard EEG device. Five undergraduate students participated in a visual flanker experiment and associated ERP components were recorded with either a standard 32-channel EEG System or a 4-channel MUSE EEG headband. In addition, we performed a 2-minutes resting state recording. Resting state brain oscillations measured with the Muse device revealed a similar pattern as with a standard EEG machine, however, strength of alpha oscillations was significantly reduced. For the Flanker task, in the Muse data, the stimulus-locked ERP components were less visible as compared to standard EEG, still the N200 was clearly expressed for the correct trials. Interestingly, in the incorrect trials, time-locked to the response there was the same negative Ne component visible as for the standard experiment. Our results reveal that the Muse device is suitable to obtain event-related potentials – even from interpolated electrode channels. Advanced preprocessing and artifact removal algorithms specifically targeting such devices with only a few and peripheral channels might help to better isolate ERP components of interest. It remains the challenge to develop devices and procedures for online tactile testing.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "name": "Ben Godde"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/33x5bg4jys64y.bib",
  "cited_by": 0,
  "doi": "10.31234/osf.io/b48kn_v2",
  "fulltext_url": null,
  "id": "33x5bg4jys64y",
  "issns": [],
  "landing_url": "https://osf.io/preprints/psyarxiv/b48kn_v2/",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "bepress",
      "Cognitive Neuroscience"
    ],
    [
      "bepress",
      "Neuroscience"
    ],
    [
      "openalex",
      "2805|EEG and Brain-Computer Interfaces"
    ]
  ],
  "openalex": "W7223987157",
  "pdf_url": "https://osf.io/b48kn/download",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-27",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/33x5bg4jys64y.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:58Z",
      "native_id": "b48kn",
      "source": "osf",
      "url": "https://osf.io/preprints/psyarxiv/b48kn_v2/"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "bepress:Cognitive Neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "Evaluating the mobile MUSE EEG headband for studying resting state EEG and event-related potentials",
  "title_text": "Evaluating the mobile MUSE EEG headband for studying resting state EEG and event-related potentials",
  "type": "preprint",
  "updated_at": "2026-10-30T12:18:58Z",
  "url": "https://research.draconitic.com/paper/33x5bg4jys64y",
  "venue": "PsyArXiv",
  "versions": []
}